gibberellin seed germination experiment

Seed Priming with Gibberellin Regulates the Germination of Cotton Seeds Under Low-Temperature Conditions

• Published: 24 January 2022
• Volume 42 , pages 319–334, ( 2023 )

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• Jun Xia 2 , 4   na1 ,
• Xianzhe Hao 2   na1 ,
• Tangang Wang 3 ,
• Huiqin Li 3 ,
• Xiaojuan Shi 2 ,
• Yongchang Liu   ORCID: orcid.org/0000-0002-9135-3877 1 &
• Honghai Luo 2  

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Exogenous substances play an important role in the response of cotton to low-temperature conditions during the germination stage, but little is known about the mechanism involved. To fill this knowledge gap, experiments were conducted to clarify the effects of the application of exogenous substances on the germination, storage substances, endogenous hormones and activities of antioxidant enzymes after gibberellin (GA 3 ) treatment under low-temperature conditions. The results showed that in XinLuZao65 (L) under low-temperature conditions, all exogenous substances tested increased the germination potential (GP) and germination index (GI) and decreased the mean time of germination (MTG), but GA 3 , 2,4-epibrassinolide (EBR), methyl jasmonate, fluridone, and salicylic acid elevated the germination rate in this variety. In XinHai35 (H) at 12 °C, exogenous substances increased the GI and decreased the MTG, but only EBR, hydrogen sulfide, and nitric oxide decreased the GP of this variety, whereas exogenous GA 3 had the best effect on seed germination at low temperature. After exogenous GA 3 and low-temperature treatment, the activities of superoxide dismutase and lipase, the contents of maize riboside, GA 3 and indole-acetic acid in cotton seeds were higher than those in the control, while the peroxidase (POD), catalase (CAT), and amylase activities and the contents of abscisic acid (ABA), malondialdehyde, hydrogen peroxide (H 2 O 2 ), starch, total sugars and total proteins were lower than those of the control. Correlation analysis revealed that ABA, adipose, CAT, H 2 O 2 , POD, GA 3 and GA 3 /ABA were the main factors affecting the germination of cotton seeds at low temperature. Therefore, exogenous GA 3 regulates the balance of endogenous hormones, enhances the activities of key enzymes, and reduces the accumulation of active oxygen, thereby accelerating the metabolism and conversion of materials and improving the low-temperature tolerance of cotton seeds during the germination stage.

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Acknowledgements

This research was supported by the Program of Youth Science and Technology Innovation Leader of The Xinjiang Production and Construction Corps (No. 2017CB005); The Third Division Tumushuke City Science and Technology of The Xinjiang Production and Construction Corps (No. YJ2019CX01); The National Natural Science Foundation of China (No. 31960439).

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Jun Xia and Xianzhe Hao have contributed equally to this work.

Authors and Affiliations

College of Chemistry and Bioengineering, Hunan University of Science and Engineering, Yongzhou, 425199, Hunan, China

Yongchang Liu

Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, Shihezi University, Shihezi, 832003, Xinjiang, China

Jun Xia, Xianzhe Hao, Xiaojuan Shi & Honghai Luo

Agricultural Science Institute of the Third Division of Xinjiang Production and Construction Corps, Tumushuke, 843806, Xinjiang, China

Tangang Wang & Huiqin Li

Shaanxi Agricultural Technology Promotion Station, Xi’an, 710003, China

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HL and JX designed the experiments; JX and XH performed the experiments and collected the data; HL, YL, HL, XS, TW, and JX analysed the data and prepared the manuscript; and all authors contributed to and approved the manuscript.

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Correspondence to Yongchang Liu or Honghai Luo .

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Xia, J., Hao, X., Wang, T. et al. Seed Priming with Gibberellin Regulates the Germination of Cotton Seeds Under Low-Temperature Conditions. J Plant Growth Regul 42 , 319–334 (2023). https://doi.org/10.1007/s00344-021-10549-2

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Received : 12 January 2021

Accepted : 23 November 2021

Published : 24 January 2022

Issue Date : January 2023

DOI : https://doi.org/10.1007/s00344-021-10549-2

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Gibberellin

Series: Springer Protocols Handbooks > Book: Practical Handbook on Agricultural Microbiology

Protocol | DOI: 10.1007/978-1-0716-1724-3_36

• C. G. Bhakta Institute of Biotechnology, Uka Tarsadia University, Surat, Gujarat, India
• Department of Microbiology, Naran Lala College of Professional and Applied Sciences, Navsari, Gujarat, India

The phytohormone, Gibberellin (GA) has a regulatory role in seed germination, stem elongation, leaf expansion, pollen maturation, development of flowers, fruits and seeds. Crop breeding programs have increased crop productivity by introducing GA

The phytohormone, Gibberellin (GA) has a regulatory role in seed germination, stem elongation, leaf expansion, pollen maturation, development of flowers, fruits and seeds. Crop breeding programs have increased crop productivity by introducing GA synthesis or response genes to produce high-yielding crops. Plant to plant, species to species, either plant or microbes types, and concentration of GAs vary. Researchers can estimate and identify the type of GAs by spectrophotometric and chromatographic methods.

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Transcriptome analysis revealed the regulation of gibberellin and the establishment of photosynthetic system promote rapid seed germination and early growth of seedling in pearl millet

• Bingchao Wu 1 ,
• Min Sun 1 ,
• Huan Zhang 1 ,
• Dan Yang 1 ,
• Chuang Lin 1 ,
• Imran Khan 1 ,
• Xiaoshan Wang 1 ,
• Xinquan Zhang 1 ,
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• Linkai Huang   ORCID: orcid.org/0000-0001-6622-5841 1  

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Seed germination is the most important stage for the formation of a new plant. This process starts when the dry seed begins to absorb water and ends when the radicle protrudes. The germination rate of seed from different species varies. The rapid germination of seed from species that grow on marginal land allows seedlings to compete with surrounding species, which is also the guarantee of normal plant development and high yield. Pearl millet is an important cereal crop that is used worldwide, and it can also be used to extract bioethanol. Previous germination experiments have shown that pearl millet has a fast seed germination rate, but the molecular mechanisms behind pearl millet are unclear. Therefore, this study explored the expression patterns of genes involved in pearl millet growth from the germination of dry seed to the early growth stages.

Through the germination test and the measurement of the seedling radicle length, we found that pearl millet seed germinated after 24 h of swelling of the dry seed. Using transcriptome sequencing, we characterized the gene expression patterns of dry seed, water imbibed seed, germ and radicle, and found more differentially expressed genes (DEGs) in radicle than germ. Further analysis showed that different genome clusters function specifically at different tissues and time periods. Weighted gene co-expression network analysis (WGCNA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that many genes that positively regulate plant growth and development are highly enriched and expressed, especially the gibberellin signaling pathway, which can promote seed germination. We speculated that the activation of these key genes promotes the germination of pearl millet seed and the growth of seedlings. To verify this, we measured the content of gibberellin and found that the gibberellin content after seed imbibition rose sharply and remained at a high level.

Conclusions

In this study, we identified the key genes that participated in the regulation of seed germination and seedling growth. The activation of key genes in these pathways may contribute to the rapid germination and growth of seed and seedlings in pearl millet. These results provided new insight into accelerating the germination rate and seedling growth of species with slow germination.

Seed germination is a complicated physiological process that is affected by both the internal development of the seed and changes in the external environment [ 1 ]. Germination begins with the absorption of water by seed and ends with the initiation of hypocotyl elongation [ 1 ]. After seed germination, growth begins with the appearance of the radicle and continues with seedling growth [ 2 ]. In order to avoid competition for land with crops, bioenergy crops are usually planted on marginal land where resources are very limited. Plants in this environment tend to compete for sunlight, air, and water. Due to the fragility of seedling in early growth stages, their swiftness and robustness will impact later development and yield [ 3 ]. Therefore, the rapid germination of seed is very important because it can improve the ability of plants to compete with other species in the field. Moreover, the rapid germination of seed involves many physiological and biochemical reactions, which are often controlled by genes. It is necessary to understand how rapid seed germination occurs in order to improve the scale of plant cultivation and economic benefits, as well as provide a reference accelerating germination of species with slow seed germination.

Fossil fuels have been used for a long time to fulfill the demand for energy and their use still dominates the market; however, the negative effects of fossil fuels cannot be ignored. Fossil fuels pose an obvious risk to environmental governance and energy security; therefore, a major portion of the world’s population has shifted their attention from fossil fuels to bioenergy [ 4 ]. Pearl millet ( Pennisetum glaucum (L.) R. Br.), an important cereal/bioenergy crop contributes to a variety of application worldwide. Pearl millet is widely planted and has fast growth, high yield, and strong resistance to various environmental stressors. Pearl millet contains easy-to-extract fermented sugars, with up to 243 kg ha −1 of fermentable sugar output [ 5 ], that can be used to produce bioethanol; thus, many researchers regard it to have the potential for bioenergy production [ 6 , 7 , 8 ]. In addition, pearl millet is one of the parents of the important energy plant known as hybridized Pennisetum , and it is the sixth most predominant cereal crop in the world [ 9 ]. Through our germination experiments, we found that the seed germination and seedling growth rate of pearl millet is extremely fast, significantly faster than maize ( Zea mays L.), rice ( Oryza sativa L.), orchardgrass ( Dactylis glomerata L.), and switchgrass ( Panicum virgatum L.; Additional file 1 : Figure S1 and Additional file 2 : Table S1). Although pearl millet is considered a crop with fast seed germination, the reason behind its fast germination rate is still unknown.

Plant hormones, including gibberellic acid (GA), auxin, and cytokinins (CTKs), are organic signaling molecules that are produced by via metabolic pathways in plants and they actively participate in various physiological processes. Plant hormones can function at the place of synthesis and can also be transported to distant parts of the plant [ 10 ]. Plant hormones can act independently or in coordination with each other to regulate the growth and development of plants [ 11 ]. Many studies have found that abnormalities in their synthesis pathways or signal transduction pathways will cause defects in plant growth and development [ 12 ]. Among these hormones, abscisic acid (ABA) and GA are the dominant factors related to seed dormancy and germination, respectively [ 13 ]. ABA promotes seed dormancy, while GA helps the seed to break dormancy, promoting germination [ 14 , 15 ]. A previous study has reported that the lower GA content in the seed of mutant ga1 , which had blocked GA synthesis, had incomplete germination even under normal conditions [ 16 ]. Another study revealed that fast-growing switchgrass seedlings accumulated higher GA content than slow-growing seedlings [ 17 ]. Auxin mainly regulates the development of plant leaves and roots [ 18 , 19 ]. Some studies have found that auxin can maintain root stem cells by inducing the accumulation of transcription factor PLT1/2 [ 20 ]. In addition, auxin can induce the growth of adventitious roots in rice [ 21 ]. CTKs are involved in the development of plant roots. The overexpression of CTK A response factors can promote the growth of Arabidopsis roots [ 22 ], which has also been observed in rice [ 23 ]. Some evidence has shown that the growth of adventitious roots in rice significantly decreases after treatment with inhibitors of CTK synthesis, indicating that CTKs behave like auxin and are involved in regulating the development of adventitious roots [ 24 ]. However, whether these hormones regulate the seed germination and seedling growth of pearl millet through signal transduction pathways is still unknown.

The growth of plants is inseparable from photosynthesis, and the factors that affect photosynthesis may also influence the growth and development of plants [ 25 ]. Previously, it has been described that increasing the daily light integral (DLI) within a certain range can improve the growth of plants, promote the accumulation of nutrients, and accelerate the developmental process [ 26 , 27 ]. As an important part of the photosynthetic system, photosynthetic antenna proteins contain different pigments and have varied absorption characteristics for different light, thus increasing the efficiency of photosynthesis [ 28 ]. The early growth rate of pearl millet seedlings is very rapid, so we can speculate that this is closely related to the sufficient energy supply of pearl millet seedlings. However, it remains unknown whether or not the photosynthetic system has been formed and activated at this stage.

Transcriptome sequencing technology has become an effective means to understand the relationship between gene expression patterns and phenotypes [ 29 , 30 , 31 , 32 ]. Transcriptome sequencing at different time points, tissues of germinated seed, and seedling growth in pearl millet will help us to identify the key genes involved at this stage. For example, a study on the transcriptome dynamics of leaves during the germination of corn seed found that gene clusters involved in hormonal metabolism and signal transduction have different expressions at different time points [ 33 ]. In this study, we conducted a seed germination experiment and found that pearl millet seed germinated at ≤ 24 h after imbibition, and the radicle elongation was faster than that of the germ. Based on the transcriptome data, there were more DEGs in the radicle than in the germ. A WGCNA was performed on all DEGs, which revealed that different gene clusters were time and tissue specific. Finally, we found that the high expression of key genes involved in hormone signal transduction, photosynthesis, photosynthesis-antenna proteins, and the brassinosteroid synthesis pathway may be related to the rapid germination and growth of seed and seedling in pearl millet. The sharp increase of GA content after seed imbibition confirmed the activation of the gibberellin signal transduction pathway and resulted in rapid seed germination. These results provide a reference for accelerating the seed germination of species with slow seed germination and seedling growth.

The germination rate and seedling growth is extremely fast in pearl millet

In our studies on seed germination, we found that pearl millet seedling grew very rapidly under suitable temperature and light conditions (Fig.  1 , Additional file 1 : Figure S1 and Additional file 2 : Table S1). We speculated that a series of rapid physiological and biochemical reactions occurred during the very early stage of seedling development. In order to determine the reasons for the rapid germination rate, we focused on five time points in the early germination period: (1) the dry seed, (2) 2 h after imbibition (HAI; still in seed form), (3) 24 HAI (radicle and germ appeared), (4) 36 HAI, and 48 HAI. We measured the length of the germ and radicle of seedling at 24, 36, and 48 HAI to characterize the growth rate of seedling.

Changes of pearl millet seed after imbibition. a Morphological changes of pearl millet seed from dry seed to seedling. b The lengths of germ and radicle at different time points. Different lowercase letters indicate significant difference at P  < 0.05

The results showed that the germination rate in pearl millet seed is very rapid (Fig.  1 , Additional file 2 : Table S2). At ≤ 24 h after seed imbibition, the length of the germ and radicle reached the germination standard, and growth rate of the radicle was faster than that of the germ, especially during the period from 24 to 36 h (Fig.  1 a). From 24 to 48 h, the seedlings experienced very rapid growth and there were significant differences in the germ length and radicle length between time points (Fig.  1 b). These results suggested that the pearl millet seed gained some advantages after imbibition, allowing the seed to rapidly germinate and grow. This indicates that we can study the transcriptome differences during this period, which will provide insight into the mechanism of pearl millet seed germination and seedling growth.

More DEGs in the radicle than the germ

Through transcriptome sequencing, a total of 810,182,656 raw reads were generated from 24 samples, ranging from 34,402,297 to 42,543,864 reads. The original data have been uploaded to the NCBI database under project number PRJNA670183. After filtering the original data, we obtained 779,909,975 clean data, ranging from 33,395,607 to 41,346,841 clean reads. The GC content of all samples ranged from 52.57 to 57.59%, the Q20 ranged from 96.93 to 98.04%, and the Q30 ranged from 92.01 to 94.66% (Additional file 2 : Table S3), indicating a high sequencing quality and that the obtained data can be used for subsequent analyses.

We used the full-length transcriptome sequence of pearl millet as a reference sequence for alignment and the calculation of gene expression [ 8 ]. Great consistency between different biological replicates of each sample is a prerequisite to ensure the reliability of subsequent bioinformatics analysis results. Therefore, we calculated Pearson's correlation coefficient for different samples and found that the three biological replicates between each sample were strongly correlated, and the correlation coefficients were all greater than 0.9 ( P value < 0.01) (Additional file 1 : Figure S2, Additional file 2 : Table S4). In order to understand the dynamics of gene expression changes in the seed, germ, and radicle at different time points, we divided the 16 comparison groups into four categories for DEGs (Table 1 ). A total of 29,514 DEGs were identified in the germ, of which only 58 genes were shared among all time points, whereas a total of 30,263 DEGs were identified in the radicle, of which only 30 genes were shared among all time points (Fig.  2 ). It is worth noting that in both the radicle and the germ, in the 24 HAI and 2 HAI comparison groups (24 HAIG:2 HAIS and 24 HAIR:2 HAIS), there were more down-regulated genes than up-regulated genes and the total number of DEGs was the largest, whereas all other comparison groups had more up-regulated genes than down-regulated genes. This may indicate that gene expression is very strong at 2 HAIS. We also found that the number of DEGs in the radicle was greater than that in the germ in other comparison groups, except for in the 24 HAI:2 HAI and the 48 HAI:36HAI comparison group after seed imbibition. This indicated that the gene expression in the radicle was more active than the germ, which may explain why the radicle appeared earlier than the germ and the faster growth rate. Because the elongation of the radicle was significantly greater than that of the germ at 36 HAI compared with 24 HAI, we investigated the DEGs of the germ and the radicle in the 36 HAI:24 HAI groups, and found that there were 6644 DEGs in the radicle, which was higher than 3447 DEGs in the germ. Then, we compared the germ and radicle at three time points and found that the number of DEGs between the radicle and germ was 12,697 in the 36 HAIG:36 HAIR group, which was significantly higher than the 7239 and 8546 of 24 HAI and 48 HAI. This may explain why the elongation of the radicle is much greater than that of the germ at 36 HAI.

Overlap of differentially expressed genes in different comparison groups: a germ, b radicle

The regulation mechanism of seed germination is specific at different stages

To better identify the DEGs related to different time points and their expression trends in the radicle and germ, the standardized expression data of 24,307 genes were analyzed using a gene co-expression network analysis from 24 samples (three biological replicates). A total of 19 modules, which is a cluster of highly related genes, were generated, with each color representing a module (Fig.  3 a, b). We found four modules with specific time or tissue expression: “midnightblue”, “cyan”, “turquoise”, and “brown” (Fig.  3 c). The brown module contains 1409 genes that are mainly expressed in dry seed; the turquoise module contains 5577 genes that are mainly expressed at 2 HAIS. The midnight blue module contains 902 genes that are mainly expressed in germ at 24, 36, and 48 HAI, and the cyan module contains 4498 genes that are mainly expressed in the radicle at 36 and 48 HAI.

Weighted gene co-expression network analysis (WGCNA) results of DEGs. a Cluster dendrogram. b Module–trait relationships. c Expression heat map and expression level of genes in the module. d KEGG enrichment of genes in the module

In order to further understand the biological functions of these four modules, we performed a KEGG analysis on the genes in these four modules (Fig.  3 d). The genes in the brown module are significantly enriched in alanine, aspartate, and glutamate metabolism (ko00250); pyrimidine metabolism (ko00240); valine, leucine, and isoleucine degradation (ko00280); and RNA polymerase (ko03020). The genes in the turquois module are significantly enriched in 13 pathways including plant hormone signal transduction (ko04075) and MAPK signaling pathway-plant (ko04016). The genes in the midnight blue module are enriched in 11 pathways such as photosynthesis-antenna proteins (ko00196); porphyrin and chlorophyll metabolism (ko00860); photosynthesis (ko00195); carbon metabolism (ko01200); and carbon fixation in photosynthetic organisms (ko00710). The genes in the cyan module are significantly enriched in 17 pathways including phenylpropanoid biosynthesis (ko00940), flavonoid biosynthesis (ko00941), and brassinosteroid biosynthesis (ko00905) (Fig.  3 d, Additional file 2 : Table S4). It is worth noting that there are few pathways shared by genes in the four modules (Additional file 1 : Figure S3, Additional file 2 : Table S5). The turquoise and cyan modules shared two pathways: taurine and hypotaurine metabolism (ko00430) and tryptophan metabolism (ko00380). Similarly, the midnight blue and cyan modules shared two pathways: biosynthesis of secondary metabolites (ko01110) and metabolic pathways (ko01100). The brown module did not share pathways with any module. The above results indicated that the function of genes in the module had strong tissue and time specificity, and different genes function at different stages, indicating that exploring the regulation mechanism of each stage can help us better understand the reasons for rapid germination in pearl millet seed.

Functional analysis of candidate genes related to seed germination and seedling growth

The signal transduction of ga, auxin, and cytokinin promotes the rapid germination of pearl millet seed.

GA is a type of diterpene compound that plays an important role in the growth and development of plants, and numerous studies have shown that it regulates the process of seed germination. When GA works through the signal transduction pathway, the receptor GID1 first senses gibberellin, and then combines with the DELLA protein to form a GID1/GA/DELLA complex, which relieves the inhibition of DELLA on key downstream regulatory factors such as PIF3 and PIF4, and then regulates various biological processes [ 34 , 35 ]. Our results found that the expression of two GID1 genes (i1_LQ_LWC_c23529/f1p0/1967 and i2_LQ_LWC_c18562/f1p4/2746) reached the highest level 2 HAI, and the same expression trend was also observed in the two PIF3 genes (i2_LQ_LWC_c21636/f1p4 /2470 and i2_LQ_LWC_c36807/f1p4/2205) and three PIF4 genes (i0_LQ_LWC_c2048/f1p68/923, i1_LQ_LWC_c35538/f1p6/1792 and i2_LQ_LWC_c83983/f1p0/2153) (Fig.  4 b). Considering that GA is the main hormone related to seed germination, and the signal transduction pathway of this hormone is highly active, we determined the GA content in the early stage after seed imbibition. We found that the content of GA in dry seed was the lowest, began to increase after imbibition, and reached the highest level at 4 HAIS. The difference between every two time points was extremely significant ( P  < 0.01) (Fig.  5 , Additional file 2 : Table S6), indicating that a large amount of GA was synthesized immediately after seed imbibition and the downstream signal transduction pathway was also stimulated to promote rapid seed germination.

The expression pattern of key genes in hormone signal transduction pathway. a The pathway in auxin signal transduction. b The pathway in gibberellin signal transduction. c The pathway in cytokinin signal transduction. The red rectangle indicates that the gene is enriched in the pathway. The expression data are the TPM values of the samples, red color indicates upregulated expression, and blue indicates downregulated expression

Gibberellin content at different time points. ** Indicates significant difference at P  < 0.01

Auxin was the earliest discovered plant hormone. It is a general term for a class of compounds that include indole acetic acid (IAA) and have similar physiological effects as indole acetic acid. Auxin is involved in many biological and physiological processes including growth and development of roots and leaves [ 18 , 20 , 36 , 37 ]. In the current study, we found that the TIR1 gene (i5_LQ_LWC_c8187/f1p3/5450) and two ARFs genes (i2_LQ_LWC_c82062/f1p4/3002 and i2_LQ_LWC_c126242/f1p4/2422) were highly expressed at 2 HAIS. In addition, some studies have shown that the downstream gene, GH3 , of this pathway was up-regulated by auxin, but it involved the degradation of auxin, so it resulted in negative feedback on auxin [ 38 ]. It is generally believed that GH3 plays an important role in auxin homeostasis [ 38 ]. SAUR is thought to be involved in auxin-regulated cell expansion, and it has also been found to be highly expressed in hypocotyl elongation [ 39 , 40 ]. We found that two GH3 genes (i2_HQ_LWC_c98146/f9p2/2256 and i2_LQ_LWC_c131239/f1p1/2110) and two SAUR genes (i1_LQ_LWC_c13114/f1p10/1086 and i1_LQ_LWC_c13186/f1p28/1222) have similar expression patterns (Fig.  4 a).

CTKs are involved in the regulation of plant cell division, growth, and development of tissues and organs. The signal transduction pathway of CTKs is first sensed by the histidine receptor kinase CRE1 (AHK2_3_4) to autophosphorylate histidine, and then the phosphate group is transferred to the aspartic acid residue in the self-receptive region. Then the phosphate group on the aspartic acid residue of the receptor is transferred to the histidine residue of the cytoplasmic histidine phosphorylation transfer protein (AHP). Finally, the phosphorylated histidine transfer protein enters the nucleus and transfers phosphate groups to A or B response factors (ARRs), among which B response factors (ARR-B) have transcription factor activity and can initiate downstream gene expression after phosphorylation [ 41 , 42 , 43 ]. Our research found that the expression levels of three CRE1 genes (i4_HQ_LWC_c31467/f3p1/4211, i4_LQ_LWC_c5323/f1p3/4657 and i4_LQ_LWC_c16458/f1p0/4224) and three ARR-B genes (i2_HQ_LWC_c64881/f4p3/2784, i2_HQ_LWC_c72282/f2p2/2653 and i3_HQ_LWC_c29456/f2p0/3081) peaked at 2 HAIS (Fig.  4 c).

We found that in the signal transduction pathways of GA, auxin, and CTKs, the expression level of genes reached the highest level at 2 HAIS in pearl millet. Therefore, we speculated that after the seed absorb water for a short time, the hormone signal transduction in the seed becomes active, which promoted the germination of pearl millet seed.

The formation of the photosynthetic system promotes the rapid growth of pearl millet seedlings

Photosynthesis plays a very important role in the growth and development of plants. It includes two light reactions: Photosystem I and Photosystem II. Photosystem I mostly produce negative oxidation–reduction reactions in nature, and to a large extent determines the amount of global enthalpy in the living system. Photosystem II produces an oxidant with a redox potential that is sufficient to oxidize H 2 O, which is a very abundant substrate that can ensure an almost unlimited source of electrons for life on Earth [ 44 ]. Both systems are multi-subunit supramolecular complexes, including a core complex and a peripheral antenna system [ 44 , 45 ]. In plants, the peripheral antennas are all made up of the light-harvesting complex (LHC). LHCIs (Lhca) and the PSI core form a PSI–LHCI complex, and LHCIIs (Lhcb) and the PSII core form a PSII–LHCII complex. The antenna system has a different pigment composition; therefore, it has different light absorption characteristics [ 28 ]. The light-harvesting complex (LHCII) in PSII is the most abundant membrane protein on Earth. It participates in the first step of photosynthesis, absorbs and transmits solar energy for photosynthesis on the chloroplast membrane, and plays a role in regulating photosynthesis and photoprotection [ 46 , 47 ]. Our results found that in the photosynthetic pathway, a total of 23 genes had the highest expression levels at 36 HAIG (Fig.  6 a). In the photosynthesis-antenna protein pathway, in addition to LHCA5, the other four light-harvesting complexes in LHCI ( LHCA1 , i0_LQ_LWC_c2012/f1p117/375; LHCA2 , i1_LQ_LWC_c27204/f1p0/1130; LHCA3 , i1_HQ_LWC_c39810/f24p5/1138; LHCA4 , i1_LQ_LWC_c34601/f1p0/1459) were significantly enriched and had the highest expression at 36 HAI in the germ. LHCB1 (i1_LQ_LWC_c19196/f1p0/1725, i1_LQ_LWC_c40686/f1p0/1092, and i1_LQ_LWC_c42565/f1p0/1078), LHCB4 (i1_HQ_LWC_c36891/f14p0/1217), and LHCB5 (i1_LQ_LWC_c26257/f1p0/1255) in LHCII also showed the same expression pattern (Fig.  6 b). These results showed that the genes involved in photosynthesis and antenna protein genes in the germ were highly expressed at 36 HAI. The increased expression levels allowed the plant to generate a lot of energy for growth and utilization, and the antenna protein system promoted the transmission of solar energy and improved the effectiveness of photosynthesis. Therefore, we speculated that the rapid formation of the photosynthetic system helped the pearl millet to more effectively produce energy for growth and development, which is an important reason for the rapid growth of the seedlings in pearl millet.

Heat map of genes expression related to light pathway. a The genes in the photosynthetic pathway. b The genes in the photosynthesis-antenna proteins pathway. The expression data are the TPM values of the samples, red color indicates upregulated expression, and blue indicates downregulated expression

Brassinosteroids promote radicle elongation

Brassinosteroids (BRs) are widely distributed plant hormones that play an important role in almost all of the growth processes of plants, including regulating the elongation and division of cells [ 48 ]. In rice that lacks BRs, its growth and development is affected, resulting in stunted growth [ 49 ]. The BR-insensitive mutants of Arabidopsis thaliana showed many defects during growth and development, including short plants and reduced apical dominance [ 48 ]. The interaction of BRs and auxin mediated by BRX (BREVIS RADIX) in Arabidopsis roots is necessary for optimal root growth. The phenotype of the brx mutant is caused by the lack of root-specific BRs. This defect affects approximately 15% of the root gene expression levels of all Arabidopsis genes, but the expression levels of these genes can be restored by BR treatment [ 50 ], suggesting that the normal level of BRs is essential for the development of plants, especially roots.

We found that the key enzymes in the biosynthetic pathway of BRs include CPD (i2_HQ_LWC_c41220/f2p0/2056 and i2_LQ_LWC_c11071/f1p0/2085), DET (i3_LQ_LWC_c34585/f1p1/4026), and CYP92A6 (i1_LQ_LWC_c8195/f1p3/1783 and i1_LQ_LWC_c36100/f1p0/1831), which were all enriched and expressed in the radicle (Additional file 1 : Figure S4). In addition, D2 (i1_LQ_LWC_c2765/f2p1/2032) and CYP734A1 (i2_LQ_LWC_c108886/f1p0/2200), which inactivate BRs through hydroxylation to maintain the steady state of BRs, also had higher expression levels in the radicle (Additional file 1 : Figure S4). The genes that synthesize BRs and maintain BR homeostasis in the radicle were very active, which ensured normal level of BRs. We speculated that this may explain why the elongation of the radicle was significantly higher than that of the germ.

Our results showed that individual pearl millet seed reached the germination standard at slightly different times under the same environmental conditions. However, nearly all seeds reached the germination standard 24 HAI. Therefore, pearl millet can be regarded as a species that is representative of plants with rapid seed germination. Translating these findings to the field, the rapid germination of pearl millet may allow it to not be easily eroded or encroached upon by weeds. In order to explore the growth rate of pearl millet seedlings, we measured the length of germ and radicle at 24, 36, and 48 HAI. The result showed that there were extremely significant differences between each time point, and the average germ and radicle lengths reached 12.4 mm and 20.5 mm at 48 HAI, respectively (Additional file 2 : Table S2). Switchgrass, another plant that can be used as a biofuel, reaches 20–30 mm tall in seedlings after 10 days of growth [ 11 ]. The growth rate of pearl millet seedlings is much faster than that of switchgrass. Therefore, pearl millet can also be regarded as representative of rapid seedling growth.

In previous studies, many researchers have reported that GA can promote seed germination [ 51 , 52 , 53 ]. A previous study found that the LOL1/bZIP58 complex in rice can promote the synthesis of gibberellins and enhance the germination rate and speed of rice seed [ 54 ]. The Arabidopsis GA deletion mutant ga1 cannot germinate without the application of exogenous GA [ 16 , 55 ]. In the signal transduction pathway of GA, the DELLA protein is the main suppressor, which binds to key downstream regulatory factors to inhibit the signal transduction of GA [ 34 ]. A previous study found that DELLA protein enhanced the degradation of PIF3, inhibiting the elongation of the hypocotyl of Arabidopsis [ 35 ]. In addition to promoting seed germination, GA can also promote root growth by degrading DELLA protein [ 56 ]. In this study, we found that the GA signal transduction pathway was very active at 2 HAI, especially the genes GID1 , PIF3 , and PIF4 , which were highly expressed, while the inhibitory DELLA protein gene was not expressed. In addition, we measured the GA content of pearl millet seed in the early stage after imbibition and found that a large amount of GA was accumulated. In fact, the GA content accumulated by pearl millet was much higher than that in switchgrass [ 17 ]. Considering the slow germination of switchgrass seed, we speculate that the large amount of GA was accumulated in the early stage after seed imbibition and is one of the reasons for the rapid germination of pearl millet seed.

In addition, to promote leaf and root development, auxin plays an active role in plant growth and development, such as regulating tissue differentiation, organogenesis, morphogenesis, apical dominance, and flowering period [ 57 , 58 , 59 , 60 ]. A recent study has shown that auxin stimulates the abscisic acid signals to induce seed dormancy [ 61 ]. Therefore, the balance of auxin content is essential for seed germination and seedling development. In our study, we found that GH3 , which promotes the degradation of auxin, was highly expressed in the auxin signal transduction pathway. The expression of this gene was induced by auxin and had negative feedback regulation. We speculated that this gene promotes the maintenance of a balanced level of auxin, which neither promotes seed dormancy nor hinders other aspects of plant growth and development.

CTKs play a major role in plant growth including promoting cell division, inducing bud differentiation, removing apical advantages, and enhancing plant resistance. Many studies have also found that CTKs efficiently promotes seed development, increases the seed setting rate, and breaks seed dormancy [ 62 ]. The earliest discovered and purified CTKs was zeatin, which was isolated from immature corn seed [ 63 ]. In the process of seed germination, GA cannot reach the point of action due to cell compartment barriers, but CTKs can change the permeability of the membrane to promote GA to function [ 62 ]. In this study, we found that after 2 HAI, the CTKs signal transduction pathway was very active, and the receptor kinase CRE1 and class B response factor ARR-B genes were highly expressed. In addition, the biosynthetic pathway of zeatin was also significantly enriched at this stage (Additional file 2 : Table S5). Zeatin is the main active ingredient of CTKs and its biosynthesis allows for CTKs to function. Therefore, we speculate that the activation of the zeatin biosynthesis pathway and the signal transduction pathway of CTKs may promote the rapid germination of pearl millet seed.

Previous studies have reported that during the germination of tobacco and Arabidopsis seed, the release of dormancy involves the light/gibberellin pathway and results in testa rupture [ 10 , 64 , 65 ]. In our study, in addition to the abovementioned GA-related pathways, light-related pathways have also been detected. Ferredoxin, which acts as a regulator, can improve the efficiency of the dark reaction [ 66 ]. We determined the expression level of gene petF (i0_HQ_LWC_c109/f3p0/774, i0_LQ_LWC_c1036/f1p0/698, and i1_LQ_LWC_c26510/f1p0/1231), which encodes ferredoxin and found that it was very active in germ, showing a peak at 36 HAI. At the same time, the photosystem subunits are highly expressed (Fig.  6 ), which all play an important role in photosynthesis. For example, the PSI-H subunit (i0_LQ_LWC_c641/f1p0/737) is necessary for the transition of the energy state in the light system, which is a dynamic mechanism for plants to quickly respond to changes in light [ 67 ]. The PSI-D subunit in Arabidopsis is encoded by the PsaD gene (i0_HQ_LWC_c150/f3p0/679 and i0_LQ_LWC_c1898/f1p2/916). The PsaD mutant is seedling-lethal in Arabidopsis , illustrating that PsaD plays an important role in maintaining the stability of Photosystem I [ 68 ]. In addition, studies have shown that Photosystem II oxygen-promoting protein 2 ( PsbP , i1_LQ_LWC_c42560/f1p4/1019 and i1_LQ_LWC_c38928/f1p0/1053) and Photosystem II oxygen-promoting protein 3 ( PsbQ , i0_LQ_LWC_c1522/f1p0/888) have specific and important roles in coordinating the activity of the donor and acceptor sides of PSII and stabilizing the active form of the PSII-light-harvesting complex II (LHCII) supercomplex [ 69 ]. We speculate that the formation of the photosynthetic system at the early seedling stage provides sufficient energy for seedling development, which accelerates the growth of seedlings in pearl millet.

The germination experiments conducted in this study showed that the germination and seedling growth rate of pearl millet are rapid. Under suitable temperature and light conditions, seed can germinate at 24 HAI. In addition, seedlings experienced rapid growth during 24–36 HAI. Therefore, we regard pearl millet as a representative plant for rapid seed germination and seedling growth. The WGCNA analysis showed that the functions of different gene clusters were highly organized and time specific, indicating that different genes were involved in the regulation of seed germination, as well as the growth of the germ and radicle. The KEGG enrichment analysis showed that differential expression of key genes in the GA, auxin, and CTK signal transduction pathways, photosynthesis, photosynthesis-antenna proteins, and brassinosteroids biosynthesis pathway regulated the germination and growth of pearl millet seedlings. This study provided a reference for accelerating seed germination and the growth and development of seedlings. Our findings can be used as a transcriptome data resource for comparison and analysis in future studies.

Plant materials

The seed of pearl millet cv. “Tifleaf 3” were used in our study and provided by key Laboratory Department of Grassland Science, Sichuan Agricultural University (Wenjiang, Sichuan, China). For the experiment, 200 seeds with uniform size and shape, and without damage were randomly selected. First, 30 seeds were randomly selected as the dry seed group (seed), and the remaining 170 seeds were soaked in distilled water and shaken at 200 rpm for 10 min to fully imbibe. Then 170 seeds were putted in a petri dish with a double-layer filter paper as a germination bed and all of them were maintained in an incubator at 30 °C/25 °C (day/night) with a photoperiod of 16 h/8 h (day/night). After 2 h, 30 seeds were randomly selected as the 2 h after seed imbibition group (2HAIS). Further, seedlings have been formed after 24, 36 and 48 h seed imbibition. Thirty individual plants were randomly selected to measure the length of germ and radicle, respectively. After the measurement, the germ and radicle were separated as the 24, 36 and 48 h germ groups (24HAIG, 36HAIG and 48HIAG) and the radicle group (24HAIR, 36HAIR and 48HAIR). Finally, all the above materials were stored in liquid nitrogen for subsequent RNA extraction. The germination test of maize inbred line B73, rice cv. “Nipponbare”, switchgrass cv. “Alamo” and orchardgrass cv. “Dianbei” seeds was carried out under the same culture conditions and the same naming rules as above were used. The germinated seeds were counted every 24 h. The germination time of 50% of the seeds in the petri dish and the germination time of all the remaining seeds were recorded.

RNA extraction and transcriptome sequencing

Total RNA was extracted using the Direct-zol™ RNA MiniPrep Kit (Zymo Research Co.), following the manufacturer’s instructions. After that, RNA purity, concentration and integrity were detected via the NanoPhotometer ® spectrophotometer (IMPLEN, CA, USA), Qubit ® RNA Assay Kit in Qubit ® 2.0 Fluorometer (Life Technologies, CA, USA) and Nano 6000 Assay Kit and Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA).

A total of 3 μg RNA from each sample as a sequencing input material, and the detailed method refers to our previous research [ 70 , 71 ]. First strand cDNA synthesis was implemented by using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H-), and second strand cDNA synthesis was implemented by using mixture containing DNA Polymerase I and RNase H. Total 24 sequencing libraries were generated using NEBNext ® Ultra™ RNA Library Prep Kit for Illumina ® (NEB, USA) [ 72 ]. In order to ensure the quality of bio-analysis, raw reads containing adapters and low quality must be filtered to obtain clean reads for subsequent analysis. The filter criteria are as follows: (1) remove reads with adapters. (2) Remove N ( N means that the base type cannot be determined) is greater than 10% of reads. (3) Remove low-quality reads (reads with Q phred  ≤ 20 bases accounting for more than 50% of the entire read length). At the same time, the GC content of clean reads, and the values of Q 20 and Q 30 were also calculated.

Quantification of gene expression level and identification of DEGs

We use the Pacbio full-length transcriptome data of pearl millet as a reference sequence for analysis [ 8 ]. The classic transcriptome data processing includes two steps: sequence alignment and transcription abundance calculation. This process uses two software, TopHat2 and Cufflinks, but the combination of these two software needs high requirements on computer hardware and is very time-consuming. Here we used kallisto software for a new RNA sequence quantization method, which is close to the best in speed and accuracy [ 73 , 74 ]. The analysis method refers to the description in the article, briefly, using the cDNA data of the reference sequence to construct an index, and then to identify and quantify the transcript. The expression abundance of genes is expressed by transcripts per million (TPM). The calculation formula of this method is: TPM i  = ( N i / L i ) * 1,000,000/sum ( N i / L i +……+ N m / L m ). N i : the number of reads mapped to gene i ; L i : the total length of the exons of gene i . By ensured the same total TPM in each sample, this method can reflect the true expression level of genes more accurately [ 75 ]. In order to ensure the accuracy and reliability of the experiment, we filtered out the genes with the maximum TPM less than 5 in the 24 samples. The differential gene identification software used with kallisto software is an R package called sleuth, which can quickly and accurately calculate the differentially expressed genes [ 76 ]. Genes with log2 (Group1/Group2) ≥ 1 and the Q value < 0.05 obtained by Sleuth software are considered to be differentially expressed.

WGCNA analysis and gene function annotation

Due to the large number of sampling points in this study, we used R software to perform WGCNA [ 77 ]. 24,307 genes were selected for WGCNA analysis. They were screened out by two conditions: (1) In all samples, there was a TPM value greater than 5; (2) The absolute value of log2 (Group1/Group2) ≥ 1 in at least one comparison group. The three key parameters are set as follows: (1) Soft threshold power is 17; (2) MinModuleSize is 30; (3) MergeCutHeight is 0.15. For functional annotations of genes, refer to the annotations in the pearl millet Pacbio full-length transcriptome [ 8 ]. For the genes in the modules, we use KOBAS software for KEGG enrichment analysis [ 78 ].

GA content determination

We used the same sampling method and strategy like RNA-seq to obtain samples to measure the GA content, the difference is that two time points 4 and 6 h after seed imbibition were added. Using the same naming rules, the samples at the two time points were named 4HAIS and 6HIAS. We used enzyme-linked immunosorbent assay to determine the content of GA [ 79 ]. The Plant Gibberellic Acid (GA) ELISA Kit is provided by Shanghai Enzyme-Linked Biology Company. The experimental method was carried out strictly in accordance with the instructions. Three biological replicates and three technical replicates were measured for each sample.

Availability of data and materials

The raw sequence data have been deposited in the NCBI database: PRJNA670183 ( https://www.ncbi.nlm.nih.gov/sra/PRJNA670183 ).

Abbreviations

Kyoto Encyclopedia of Genes and Genomes

Abscisic acid

Gibberellin

Daily light integral

Differently expressed genes

Weighted gene co-expression network analysis

National Center for Biotechnology Information

Indole acetic acid

Light-harvesting complex

Brassinosteroids

Complementary DNA

RNA sequencing

Transcripts per million

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Acknowledgements

The author would like to thank Novogene Bioinformatics Co., Ltd. (Beijing, China) for its assistance in sequencing and the BMK Cloud platform ( http://www.biocloud.net ) for completing part of the data analysis.

This work was supported by National Project on Sci-Tec Foundation Resources Survey (2017FY100602), the Sichuan Province Research grant (2021YFYZ0013), the Modern Agro-industry Technology Research System (CARS-34) and Modern Agricultural Industry System Sichuan Forage Innovation Team (SCCXTD-2020-16).

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BW and LH designed research studies; BW and MS conducted experiments, acquired data, and analyzed data; BW, DY, and HZ wrote the manuscript; XW, IK, YY, GN and GF revised the manuscript; XZ, ZL and YP provided plant materials. All authors read and approved the final manuscript.

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Additional file 1: figure s1..

Morphological changes of four other plants seed from dry seed to seedling. Figure S2. Correlation between different samples. Figure S3. Pathways shared among the four modules. Figure S4. Heat map of genes expression related to brassinosteroid biosynthesis.

Additional file 2: Table S1.

Germination time of different plant seed. Table S2. Length of germ and radicle in different time points. Table S3. Summary of raw sequencing data quality. Table S4. Correlation coefficient between biological replicates of different samples. Table S5. Pathways of gene enrichment in the four modules. Table S6. Gibberellin content at different time points. Table S7. The original reads counts value of the genes.

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Wu, B., Sun, M., Zhang, H. et al. Transcriptome analysis revealed the regulation of gibberellin and the establishment of photosynthetic system promote rapid seed germination and early growth of seedling in pearl millet. Biotechnol Biofuels 14 , 94 (2021). https://doi.org/10.1186/s13068-021-01946-6

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• Published: 06 April 2023

Gibberellin and abscisic acid transporters facilitate endodermal suberin formation in Arabidopsis

• Jenia Binenbaum   ORCID: orcid.org/0000-0003-4724-3563 1 ,
• Nikolai Wulff   ORCID: orcid.org/0000-0002-7524-104X 2 ,
• Lucie Camut 3 ,
• Kristian Kiradjiev   ORCID: orcid.org/0000-0002-4716-0330 4 , 5 ,
• Moran Anfang 1 ,
• Iris Tal 1 ,
• Himabindu Vasuki   ORCID: orcid.org/0000-0002-7106-3506 1 , 6 ,
• Yuqin Zhang 1 ,
• Lali Sakvarelidze-Achard 3 ,
• Jean-Michel Davière 3 ,
• Dagmar Ripper 7 ,
• Esther Carrera   ORCID: orcid.org/0000-0002-3454-7552 8 ,
• Ekaterina Manasherova 9 ,
• Shir Ben Yaakov 1 ,
• Shani Lazary 1 ,
• Chengyao Hua 2 ,
• Vlastimil Novak   ORCID: orcid.org/0000-0001-7890-4593 10 ,
• Christoph Crocoll   ORCID: orcid.org/0000-0003-2754-3518 2 ,
• Roy Weinstain 1 ,
• Hagai Cohen 9 ,
• Laura Ragni   ORCID: orcid.org/0000-0002-3651-8966 7 ,
• Asaph Aharoni   ORCID: orcid.org/0000-0002-6077-1590 6 ,
• Leah R. Band   ORCID: orcid.org/0000-0002-6979-1117 4 , 5 ,
• Patrick Achard   ORCID: orcid.org/0000-0003-0520-7839 3 ,
• Hussam Hassan Nour-Eldin   ORCID: orcid.org/0000-0001-6660-0509 2 &
• Eilon Shani   ORCID: orcid.org/0000-0002-1262-350X 1  

Nature Plants volume  9 ,  pages 785–802 ( 2023 ) Cite this article

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• Gibberellins
• Plant genetics
• Plant molecular biology
• Plant physiology

The plant hormone gibberellin (GA) regulates multiple developmental processes. It accumulates in the root elongating endodermis, but how it moves into this cell file and the significance of this accumulation are unclear. Here we identify three NITRATE TRANSPORTER1/PEPTIDE TRANSPORTER (NPF) transporters required for GA and abscisic acid (ABA) translocation. We demonstrate that NPF2.14 is a subcellular GA/ABA transporter, presumably the first to be identified in plants, facilitating GA and ABA accumulation in the root endodermis to regulate suberization. Further, NPF2.12 and NPF2.13, closely related proteins, are plasma membrane-localized GA and ABA importers that facilitate shoot-to-root GA 12 translocation, regulating endodermal hormone accumulation. This work reveals that GA is required for root suberization and that GA and ABA can act non-antagonistically. We demonstrate how the clade of transporters mediates hormone flow with cell-file-specific vacuolar storage at the phloem unloading zone, and slow release of hormone to induce suberin formation in the maturation zone.

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All the data supporting the findings of this study are available within the Article and its Supplementary Information . Source data are provided with this paper. The python code used to produce the model results is available at: https://gitlab.com/leahband/ga_aba_transport_rootcrosssection_model .

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Acknowledgements

We thank D. Binenbaum for the illustrations and P. Hedden (Rothamsted Research) for sharing pGA3ox1-4:GUS seeds. This work was supported by grants from the Israel Science Foundation (2378/19 and 3419/20 to E.S.), the Human Frontier Science Program (HFSP—RGY0075/2015 and HFSP—LIY000540/2020 to E.S., H.H.N.-E. and L.R.B.), Danmarks Grundforskningsfond (DNRF99 to H.H.N.-E.), the European Research Council (757683-RobustHormoneTrans to E.S.), the Constantiner Travel Fellowship (to J.B.), the Centre National de la Recherche Scientifique (to L.S-A. J-M.D. and P.A.) and the French Ministry of Research and Higher Education studentship (to L.C.).

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Jenia Binenbaum, Moran Anfang, Iris Tal, Himabindu Vasuki, Yuqin Zhang, Shir Ben Yaakov, Shani Lazary, Roy Weinstain & Eilon Shani

DynaMo Center of Excellence, Department of Plant and Environmental Sciences, University of Copenhagen, Frederiksberg, Denmark

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Contributions

J.B. performed the research and wrote the manuscript. N.W. performed the oocyte transporter assays. L.C., L.S-A., J-M.D. and P.A. carried out long-distance transport assays. K.K. performed the mathematical modelling. I.T. assisted in cloning overexpression and reporter lines. H.V. and A.A. quantified root GA and ABA content. M.A. helped with genotyping T-DNA mutant lines and profiling suberin patterning. Y.Z. helped with npf mutant identification. D.R. and L.R. assisted in cross-sectioning and staining. E.C. quantified hormone content in the phloem sap. E.M. and H.C. performed suberin monomer quantifications. S.L. and R.W. synthesized fluorescently tagged hormones. S.B.Y. carried out the qPCR and created hormone-treated reporter lines. V.N. and C.C. helped with nitrate and hormone quantification in oocyte assays, respectively. C.H. carried out hormone competition transport assays. L.R.B., P.A., H.H.N.-E. and ES designed and supervised the work and edited the manuscript. All authors discussed the results and commented on the manuscript.

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Correspondence to Leah R. Band , Patrick Achard , Hussam Hassan Nour-Eldin or Eilon Shani .

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Binenbaum, J., Wulff, N., Camut, L. et al. Gibberellin and abscisic acid transporters facilitate endodermal suberin formation in Arabidopsis . Nat. Plants 9 , 785–802 (2023). https://doi.org/10.1038/s41477-023-01391-3

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Plant Development and Crop Yield: The Role of Gibberellins

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Gibberellins have been classically related to a few key developmental processes, thus being essential for the accurate unfolding of plant genetic programs. After more than a century of research, over one hundred different gibberellins have been described. There is a continuously increasing interest in gibberellins research because of their relevant role in the so-called "Green Revolution", as well as their current and possible applications in crop improvement. The functions attributed to gibberellins have been traditionally restricted to the regulation of plant stature, seed germination, and flowering. Nonetheless, research in the last years has shown that these functions extend to many other relevant processes. In this review, the current knowledge on gibberellins homeostasis and mode of action is briefly outlined, while specific attention is focused on the many different responses in which gibberellins take part. Thus, those genes and proteins identified as being involved in the regulation of gibberellin responses in model and non-model species are highlighted. The present review aims to provide a comprehensive picture of the state-of-the-art perception of gibberellins molecular biology and its effects on plant development. This picture might be helpful to enhance our current understanding of gibberellins biology and provide the know-how for the development of more accurate research and breeding programs.

1. Introduction

Phytohormones are a chemically diverse set of compounds that regulate plant development at micromolar concentrations. Hormone synthesis, transport, and degradation are tightly controlled because minor variations of their levels in tissues can have a huge impact on plant responses as they play important roles in the regulation of gene expression or the activity of other hormones.

Gibberellins (GAs) can be included as one of the five classical hormones, along with auxins, cytokinins, abscisic acid, and ethylene [ 1 ]. Each of these groups of hormones is associated with specific plant traits and physiological responses. In the case of GAs, they have been usually associated with the regulation of plant stature [ 2 ] and seed dormancy [ 3 ]. However, results in recent years have shown that this might be an oversimplification, and GAs (as well as the rest of phytohormones) have direct or indirect effects on the regulation of many plant traits. GAs were key elements in the Green Revolution that took place within the second half of the 20th century, and many of the plant varieties with improved agronomical traits (dwarf phenotypes, increased biomass) showed to be related to GA activity and signaling [ 4 ]. However, the potential innovation of GA is far from exhausted and they can be again the leader of a new Green revolution [ 5 ] increasing yield and improving nitrogen-use efficiency all at once [ 6 ].

In the present review, an update on the recent findings concerning the many facets of development in which GA take part is intended. Besides, we also focus on the current and potential applications of GA in crop production, highlighting the relevance of these compounds as regulatory agents in agriculture. The emphasis is on the distinct effects of these hormones in plant responses through the modulation of gene expression and the agronomical impact of GA and related compounds. Those genes and proteins identified within the GA signaling cascades are underlined due to their potential interest as targets for future breeding programs. By gathering information from different species, our aim is to integrate molecular data that might help in the development of conceptual models regarding GA activity. However, as it will be shown, the variability in the responses in different species, the diversity of GA-related compounds, and the lack of specific research in some fields hinder the development of such models except for particular processes. Nonetheless, we hope that this review might be useful for researchers and growers in the definition of their strategies.

2. History of Gibberellins Research

GAs are a type of phytohormones first uncovered in the early 20th century [ 7 ] during the study of a common rice disease known as bakanae , which causes significant losses every year [ 8 ]. The causing agent of this condition is the fungus Fusarium fujikuroi , an ascomycete that spreads through water and infects the seeds. The infected plants are characterized by a very thin and elongated stem, resulting in a somehow ridiculous ("foolish") aspect. An over-accumulation of GA produced by the fungus during seed infection is the reason underlying this phenotype, which also concurs with etiolation and infertility [ 9 ]. During the 1950s, efforts conducted by Japanese scientists led to the isolation of gibberellin A 1 , gibberellin A 2 , gibberellin A 3 (later known as gibberellic acid), and gibberellin A 4 [ 10 , 11 ]. Within the same period, the normal phenotype of maize dwarf mutants was restored after GA 3 application [ 12 ]. Further investigation guided the characterization of new GAs in plants, fungi, and bacteria (reviewed in [ 13 ]).

GAs have had a huge relevance due to their direct impact on agricultural performance. The characterization of dwarf varieties of wheat and rice showed the implication of GA in the resulting phenotypes of these plants. This short stature turned out to be an interesting agronomic trait for several crops as it reduced the risk of lodging, while providing more compact ornamentals [ 14 ]. In this way, GA modulation played a key role in the Green Revolution because of the increase in grain yield, harvest index of these varieties, and improved stress resistance to wind and rain due to their compactness [ 15 ]. A deeper comprehension of GA molecular activity and its application to accurate breeding programs may help to ease the path for new advances in crop management and a better and more sustainable food production [ 16 ].

Fundamental molecular aspects of GA synthesis, homeostasis, and signaling have been described in the last years, although several issues concerning transport or interactions with other phytohormones are still not fully elucidated [ 17 ]. GAs are acid diterpenoids derived from the terpenes route. The amount of bioactive GAs in plant tissues is determined by the activity of specific oxidases. The C 20 -GA-oxidases (i.e., GA20ox) and C 19 -GA-oxidases (i.e., GA3ox) act as rate-limiting enzymes within the last steps of the synthesis process, and their activity increases the pool of active GAs acting on intermediate or non-biologically active GAs. On the other hand, active GAs can be deactivated by other specific oxidases, mainly C 20 -GA-2-oxidases and C 19 -GA-2-oxidases (GA2ox). Balance between the activity of these different types of enzymes determines the GA content in plants, thus establishing these oxidases as the main targets for the GA regulation exerted by other compounds, genes, or phytohormones. However, a more detailed view of GA synthesis and homeostasis was recently reviewed [ 17 ].

The nuclear receptor GIBBERELLIN-INSENSITIVE DWARF1 (GID1) is responsible for the perception of GA. The GA–GID1 interaction enables the ubiquitination and degradation of DELLA proteins, which act as repressors of GA signaling. DELLA proteins belong to the GRAS family (based on the designation of GIBBERELLIC-ACID INSENSITIVE, [G]AI, REPRESSOR OF GA, [R]GA [A]ND SCARECROW, [S]CR), and the molecular mechanisms enabling them to block GA signaling have been already described [ 18 ]. Overall, a continuous balance between GA perception and DELLAs degradation governs the genetic responses to these phytohormones.

3. Vegetative Development

The ability of GA to control different aspects of plant development has driven a continuous effort to unravel the molecular mechanisms controlling these responses. In this section, we highlight relevant results recently achieved in GA research that have led to the identification of many genes and proteins in both model and non-model species. A detailed list of the identified genes in these and other processes and their activating or inhibiting role in GA signaling can be found in the Supplemental Tables (S1 and S2) .

3.1. Shoot Elongation

Shoot growth and development, major agronomical traits, are of great relevance for plant yield, architecture, and overall performance, and the activity of GA is believed to directly influence both processes ( Figure 1 ). At the molecular level, GA favors plant elongation through cell growth regulation. According to the mechanisms elucidated in Festuca arundinacea , GA application promotes the transcription of xyloglucan endotransglycosylase (XET), α and β-expansins [ 19 ]. Besides, DELLA proteins physically interact with prefoldins and, after DELLA degradation induced by GA, free prefoldins are able to bind β-tubulins and stabilize them, thus affecting microtubules orientation and the direction of cell expansion [ 20 ]. Indeed, recent data suggest a close relationship between prefoldin activity and GA signaling. Expression analysis in the shoot apex of a prefoldin sextuple mutant of Arabidopsis showed the upregulation of the GA2ox gene in plants growing under short-day photoperiod. In contrast, the analysis revealed a reduced expression of PHYTOCHROME-INTERACTING FACTOR 4 (PIF4), a transcription factor (TF) closely related to GA responses (see below) and involved in the control of auxin-related genes [ 21 ]. Therefore, although more research is needed, there seems to be a close link between GA and prefoldins, that might help govern cell expansion and division. This results in the expansion of the cells in a GA-driven fashion.

Schematic representation of the GA-related signaling involved in the process of shoot elongation. Yellow and grey background indicate light and dark conditions, respectively. Arrows indicate activation and blunt-end lines indicate repression or inhibition. See text for details and references. ARF6: auxin response factor 6, BZR1: brassinazole-resistant 1, ERF11: ethylene response factor 11, EUI: elongated uppermost internode, GA: gibberellins, GA2OX: gibberellin 2-oxidase, GI: gigantea, H3k27me3: 3 methylation of lysine 27 in histone 3, HBI1: homolog of bee2 interacting with ibh 1, MADS57: MADS box transcription factor 57, PFD: Prefoldins, PHYB: phytochrome B, RGA: repressor of GA, PIF4: phytochrome-interacting factor 4, PIF4-TCP: phytochrome-interacting factor 4-teosinte branched 1–cycloidea–pcf, PKL: pickle, PRE6: paclobutrazol resistance 6, SLR1: slender rice 1, XET: xyloglucan endotransglycosylase.

The ability of GAs to control shoot elongation has been shown in agronomical relevant species such as rice. In this species, stem elongation and tiller number are regulated by the GA-induced degradation of SLENDER RICE 1 (SLR1), a DELLA protein that binds to tiller regulator MONOCULUM 1 (MOC1) preventing its degradation [ 22 ]. Furthermore, GA prevents interaction between SLR1 and KNOTTED1-LIKE HOMEBOX (KNOX) allowing panicle development [ 23 ]. Plant height, internode elongation, and panicle development are controlled by OsMADS57 , a MADS-box gene that acts as a key regulator by repressing the expression of the cytochrome P450 monooxygenase ELONGATED UPPERMOST INTERNODE ( EUI ) and OsGA2ox3 and, therefore, allowing GA accumulation [ 24 ]. It has been recently shown that a module comprising the F-box protein DWARF3 and the microRNA miR528 affects plant height in rice by modulating GA and Abscisic Acid (ABA) homeostasis [ 25 ]. In addition, the ELONGATED INTERNODE ( EI ) gene in tomato, which causes dwarfism, is related to the GA metabolic pathway as it encodes the GA2ox7 gene, a catabolic enzyme within this pathway [ 26 ]. It has been shown that GA is also a key plant hormone controlling shoot elongation in carrot [ 2 , 27 ].

GA gradients are directly related to the elongation of roots and dark-grown hypocotyls in Arabidopsis, as seen with the use of a FRET-based biosensor [ 28 ]. As above mentioned, cooperative action of DELLA and light degrades PIF4 through the phytochrome B action, which is activated by ABA to prevent shoot growth [ 29 ]. However, under dark conditions and exogenous application of GA, PIF4 activates genes related to cell elongation [ 30 ]. Indeed, GA signaling and activity seem to depend on the plant circadian clock [ 31 ]. In line with this, DELLA proteins are stabilized during the daytime by GIGANTEA (GI), while GI degradation during nighttime allows GA activity. This finding suggests that GI is the key regulator of the circadian clock in hypocotyl elongation [ 32 ]. PIF3, PIF4, and PIF5 [ 30 , 33 ] activate several downstream genes that result in hypocotyl elongation, and at the same time lead to a positive feedback that drives the accumulation of GAs [ 28 ]. In addition to activating the brassinosteroid-related TF BRASSINAZOLE RESISTANT 1 ( BZR1 ) [ 34 ], GA induces PIF expression and degrades the RGA DELLA proteins, allowing the activity of the auxin-response factor ARF6. In dark conditions, recruitment of PICKLE (PKL) by PIF and BZR1 blocks the accumulation of H3K27me3 marks and permits the activation of growth-related genes [ 35 ]. Cellular growth and hypocotyl elongation are also promoted by PIF, BZR1, and ARF in Arabidopsis [ 36 ] but in an apparently independent manner [ 37 ]. Hypocotyl elongation in response to high temperatures has been found to be regulated through GA, at the posttranscriptional level by regulating the PIF4 activity in Arabidopsis [ 38 ] or GA 12 transport from root to shoot in tomato, which seems relevant in the integration of day-night temperature oscillations [ 39 ]. PIF4 activates GA3ox and interacts with TEOSINTE BRANCHED 1, CYCLOIDEA, PCF (TCP) TCP15/14, which enhances the expression of GA20ox , to promote hypocotyl elongation through HOMOLOG OF BEE2 INTERACTING WITH IBH-1 ( HBI1 ) and PACLOBUTRAZOL RESISTANCE 6 ( PRE6 ), among other genes. The role played by GA in the plant’s ability to adapt its growth patterns to changes in environmental temperature [ 40 ], suggests additional roles of GA in the response to outer cues.

An interaction of GA and ultraviolet-B light (UV-B) on shoot elongation has also been reported [ 41 ]. UV-B eases the cooperation between CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1) and ELONGATED HYPOCOTYL 5 (HY5) to promote the accumulation of the RGA (DELLA) protein that leads to inhibition of hypocotyl elongation [ 42 ]. In addition, UV-B induces PIF4 and PIF5 degradation, thus reducing hypocotyl elongation [ 43 ]. These results show that light quality is also sensed and transduced in specific responses through GA-linked signaling routes.

The link between GA and light has also been shown to relate to the shade avoidance response. Under normal light conditions, CRYPTOCHROME 1 (CRY1) allows STENOFOLIA (STF) and DELLA accumulation and reduces GA levels in soybean and Arabidopsis [ 44 , 45 ]. However, in dark conditions CRY1 is inactive, allowing the GA-guided degradation of the DELLA proteins and the expression of genes activated by the released PIFs, which promote hypocotyl elongation [ 46 ]. GA also promotes shade-induced stem elongation as a manifestation of shade avoidance response in rice [ 47 ]. A shade-tolerant mutant of perennial ryegrass also supports the role of GA in this process, as it showed a reduced GA biosynthesis rate in the dark [ 48 ].

The complex framework of the GA effect on shoot elongation also involves the crosstalk of GAs with other phytohormones. The ETHYLENE-RESPONSIVE FACTOR 11 (ERF11) controls hypocotyl elongation by two independent but complementary pathways, repressing DELLA proteins and promoting the biosynthesis of GA, the latter via repression of ethylene biosynthesis genes [ 49 ]. In different species such as Scirpus mucronatus [ 50 ] and maize [ 51 ], ABA seems to inhibit shoot growth. In rice, strigolactones regulate shoot length by affecting GA homeostasis [ 52 ]. Other phytohormones, such as auxin and BRs, are involved in hypocotyl elongation through their interaction with GA [ 53 ].

Therefore, modulation of GA levels emerges as a key mechanism in the integration of outer (temperature, light quality) and inner cues (circadian clock) involved in shoot development, providing a connection with specific responses such as cell expansion and division.

3.2. Xylogenesis and Cellulose Production

The development of the secondary cell wall in plants as well as the formation of xylem, also referred to as secondary growth, are related processes that strongly influence growth and performance. Indeed, due to the direct relationship between xylogenesis and the production of wood and biomass, xylogenesis is an economically desirable process, particularly in trees. The proposed relationship of GA with cell and plant elongation also enables a role for these compounds in wood production, in order to help plants maintain large architectures. Accordingly, the proposed antagonistic relation of GA and ABA is also found in these processes, as the latter inhibits both shoot elongation and xylogenesis [ 54 , 55 ]. In recent years, it has been found that GA promotes cambial activity [ 56 ] and xylogenesis in trees [ 55 , 57 ]. Furthermore, the expression of three CELLULOSE SYNTHASE ( CESA ) genes in Eucalyptus ( CESA3 , CESA4 , and CESA7 ), which are involved in xylem development, was induced by GA treatment [ 58 ]. Similarly, in birch, application of GA promoted xylem development and induced the expression of genes related to xylogenesis and cellulose production, such as MYB , CESA , and PHENYLALANINE AMMONIA-LYASE ( PAL ) [ 59 ]. Transgenic approaches showed an increase in secondary growth in plants overexpressing GA-related biosynthesis and signaling genes [ 60 ], while biomass production in poplar has been enhanced by the overexpression of the GA20ox gene [ 61 ]. In hybrid aspen, other wood traits, such as cell xylem length, have been shown to be positively modulated by GA [ 57 , 62 ]. Tian et al. (2016) [ 63 ] also reported modifications of wood properties in Populus by GA-responsive lncRNAs.

This xylogenesis-promoting effect of GA is not restricted to woody species as it has also been described in carrot [ 27 ], cotton [ 64 ], or celery [ 65 ]. Indeed, xylem proliferation is suppressed in tomato mutants with altered GA signaling [ 66 ]. The ability of GA to modulate xylem proliferation needs further exploration but, in the same manner as plant height control, it is a potential strategy to increase biomass production and optimize wood yield.

3.3. Root Development

Continuous root growth is essential for plants to explore the soil for nutrients and to provide physical support for the constant growth of the aerial parts. The three-dimensional structure of the root (root system architecture) drastically influences such functions. GA seems to have several relevant roles in root development from meristem development [ 67 ] to root nodulation for nitrogen fixation [ 68 , 69 ].

Historically, it was accepted that GAs were promoters of root growth. However, as it will be stated, the effect of GA on rooting responses is highly dependent on the species under study. The GA gradient between the apical division and the elongation zones in the root is strongly related to the fast growth of both roots and shoots in the dark [ 28 ]. The longitudinal GA gradient of growing roots is a result of differential GA biosynthesis and cellular permeability [ 70 ]. After germination, GA represses RGA and ARABIDOPSIS RESPONSE REGULATOR 1 ( ARR1 ). Stabilization of PIN transporter proteins due to the downregulation of SHORT HYPOCOTYL 2 ( SHY2 ), caused by the repression of ARR1 , promotes elongation of the root [ 71 ]. On the other hand, ARR1 recruits DELLA proteins to reduce the GA effect and maintain the root meristem status [ 72 ]. Additionally, GA promotes root meristem cell divisions and enhances root growth [ 73 ], and GA is required for primary root growth in rice which is inhibited by GA deactivation [ 74 ]. Moreover, if GA supply from shoot to root stops, a biosynthesis feedback regulation mechanism is activated to ensure the optimal quantity of GA to maintain root growth [ 75 ]. Nevertheless, some evidence suggests that GA-induced root elongation produces thinner roots in carrot or Pseudostellaria heterophylla [ 27 , 76 ]. In sweet potato, whose agronomical profitability depends on its ability to transform adventitious roots in storage organs, the addition of GA promotes root lignification and reduces starch accumulation, thus preventing the shift from root to storage-root organ [ 77 ]. Similarly, in Gladiolus hybridus , GA prevents starch synthesis and corm development via GhSUS2 activation [ 78 ]. On the other hand, in Panax ginseng and yam, GA promotes secondary growth of storage roots [ 79 , 80 ]. It has been suggested that a high ABA/GA ratio promotes tuber development, while GA preponderance delays tuber formation [ 81 ]. GA also promotes root growth by increasing the indole-3-acetic acid (IAA) content and reducing the synthesis of flavonols, which inhibit polar auxin transport [ 82 ]. Nevertheless, the relationship between GA and root growth is not always straightforward. There are many species in which they have minor effects [ 83 ], no effect, or even inhibitory effects [ 84 ]. However, the model discovered in Arabidopsis seems to prevail for most species. Therefore, it seems clear that GA affects root development and architecture beyond root length.

A promoting activity of GA on adventitious rooting has been suggested in oak and cherry [ 85 , 86 ]. Nonetheless, most studies on other species, such as tobacco [ 87 ], Populus [ 88 ], and Pinus radiata [ 89 ], point in the opposite direction. In hybrid aspen and Arabidopsis, GA inhibits adventitious rooting by affecting auxin transport [ 90 ]. The induction of adventitious roots depends on the ability of tissues to generate an auxin gradient, which relies on the auxin transport machinery. The inhibition of that transport by GA seems to underlie their inhibitory effect on this process. Adventitious rooting is inhibited in poplar transgenic plants overexpressing the histone deacetylase PtHDT902 , which increases GA biosynthesis [ 91 ]. In line with this, adventitious rooting was improved when GA content was lowered by the overexpression of the GA2ox gene [ 92 ] or by the treatment with the GA biosynthesis inhibitor Paclobutrazol (PBZ) [ 93 , 94 ]. The analyses performed with the tomato GA mutant procera , which exhibits a loss of in vitro organogenic capacity to form shoots and roots, suggest that DELLA protein loss of function affects the cell-fate acquisition competence rather than the induction phase of the adventitious rooting process [ 95 ]. Interestingly, fruit development responses to exogenous auxin are enhanced in this mutant [ 96 ]. Therefore, results suggest that root developmental processes are affected by the crosstalk between GA and auxin. Indole-3-butyric acid (IBA) treatment inhibits GA synthesis in mung bean [ 97 ] and GA can have a negative effect on the adventitious rooting stimulated by IBA in apple tree [ 98 ]. It has been suggested that during adventitious root formation, the expression of PIN genes, which are auxin transporters, is repressed by GA [ 99 ]. The body of evidence for GA’s impact on adventitious rooting seems to indicate that this process is inhibited by GA in most species, although the effect seems to be species-specific. More research is needed to clarify the role of GA in rooting and their complex interaction with the auxin signaling and transport machinery.

In the case of lateral roots, results are also somehow contradictory. In Populus , the addition of GA promotes lateral root formation [ 88 ], but inhibits lateral root primordia initiation through interactions with auxin [ 100 ]. On the other hand, studies in rice revealed that the addition of exogenous GA 3 reduces the number of lateral roots [ 92 ].

Therefore, GA seems to play a positive role in root growth and an inhibitory role in the development of adventitious roots, although the effect might be species specific and no unambiguous role can be attributed so far.

3.4. Other Vegetative Processes

Plants are able to react to physical interactions, and specific responses to contact stimuli are known as thigmomorphogenesis. Activation of the GA2ox7 catabolic gene through mechanical contact leads to changes in plant morphology. This mechanism also enhances both biotic and abiotic stress resistance in plants, and the induced changes can be reversed by exogenous GA application, at least in Arabidopsis [ 101 ].

Meristems are a complex set of undifferentiated cells which by means of controlled divisions and positional cues give rise to new tissues. The shoot apical meristem (SAM) needs a low GA content to function properly. It has been reported that the KNOX-induced activity of GA2ox leads to the oxidative deactivation of GA allowing the normal functions of SAM [ 102 ]. The positive effect of GA in the axillary meristem formation has been reported in garlic [ 103 ]; however, a dual role of GA in bud break and bud dormancy has also been reported. In grapevine, GA synthesis leads to bud dormancy release [ 104 ], while in hybrid poplar bud break is allowed by the MADS12 TF induced downregulation of the GA2ox gene [ 105 ]. Thus, low GA content seems necessary for normal SAM function, while high levels induce the development of axillary buds. Moreover, modification of GA content and signaling affects tree branching, and hence can be used to modulate tree crown characteristics (reviewed in [ 60 ]). Therefore, adjustment of GA levels can be used to modify plant architecture, enabling their use for fine-tuned agronomic production.

Trichome emergence and formation are also modulated by GA [ 106 , 107 ]. Trichomes, protruded single epidermal cells, have many functions in plants, but are particularly relevant in stress responses. The activity of GA is also needed for cotton fiber elongation in ovule cultures, a particular type of trichomes [ 108 ]. Noteworthy, several feedback mechanisms ensure the fine-tuned control of GA on the formation of these organs. In Arabidopsis, GA promotes trichome development, a process controlled by GLABROUS INFLORESCENCE STEM ( GIS ), which may act upstream or downstream of SPINDLY (SPY), a negative regulator of GA signaling [ 109 ]. On the other hand, trichome formation is repressed by TEMPRANILLO (TEM), an inhibitor of GA biosynthesis genes and its related transporter NITRATE TRANSPORTER/NITRATE PEPTIDE FAMILY (NPF). TEM prevents the GA-induced expression of GLABROUS 1 ( GL1 ), GL3 , ENHANCER OF GLABRA3 ( EGL3 ), and TRANSPARENT TESTA GLABROUS1 (TTG1) genes [ 110 ]. Moreover, the histone acetyltransferase 1 (HAT1) TF is a negative regulator of trichome initiation which acts through a negative feedback loop. GA induces the expression of HAT1 that in turn represses GA biosynthesis [ 111 ]. In Populus tomentosa , GA acts coordinately with miR319a/TCP to control trichome formation, directly impacting defenses against herbivores [ 112 ]. Traditionally, it was assumed that GA has a negative role in the defense of plants against biotic stresses [ 17 ]. Once a plant is colonized by a pathogen, GA activity seems to worsen the effects. However, herbivory is a major biotic stress for plants and GA can help to avoid this stress through the induction of trichome formation.

Leaf senescence is a complex process regulated by many factors, including GA, with light and age of the plant playing a central role. The effect of GA in this process varies according to the species under study, suggesting an intricate relation with internal and external cues. In Arabidopsis, GA-induced degradation of DELLA allows the activity of NAC-LIKE ACTIVATED BY AP3/PI (NAP) leading to leaf senescence and chlorophyll degradation [ 113 ]. Foliar senescence is postponed by GA in a way apparently independent of light in Alstromeria [ 114 ]. In Chinese flowering cabbage, a rapidly senescing vegetable, leaf senescence is delayed due to the TCP-induced activation of GA biosynthesis [ 115 ], while exogenous GA treatment postpones the process by inhibiting the expression of the BrWRKY6 TF [ 116 ]. In contrast, PIF4 interacts with the GA signaling pathway accelerating leaf senescence in maize [ 117 ] and Arabidopsis [ 118 ]. In Arabidopsis, early leaf senescence is also induced by the GA-driven activation of SENESCENCE ASSOCIATED GENE ( SAG ), WRKY45 [ 119 ], and WRKY75 [ 120 ] genes, in an age-related process. The divergence of results does not allow to unequivocally assert the direction of foliar senescence after GA application. More studies are necessary to elucidate the role of GA in this process.

4. Reproductive Development

The relevance of GA in plant performance extends beyond their influence on growth and biomass yield. They also impact several reproductive-related processes, such as flowering and fruit formation. Due to the relevance of these processes for plant productivity, the related molecular mechanisms have been widely studied, particularly in crops, and many of the genes involved in these relevant traits have been outlined ( Figure 2 ).

Schematic representation of the GA-related signaling involved in flowering and the development of the flower tissues. Arrows indicate activation and blunt-end lines indicate repression or inhibition. Orange box represents the GA flowering pathway, the blue box the vernalization flowering pathway, the yellow box the photoperiod flowering pathway and green box the aging flowering pathway. Grey boxes represent meristem identity genes and floral integrator genes. See text for details and references. ABA: abscisic acid, AP1/3: apetala 1/3, BBX24: B-box domain protein 24, CPS: ent -copalyl diphosphate synthase, CO: constans, DAD1: defective anther dehiscence 1, FLC: flowering locus C, FT: flowering locus T, FUL: fruitfull, GA2OX: GA2-oxidase, GA20OX: GA20-oxidase, GAI: gibberellic acid insensitive, JA: jasmonates, JAZ1: jasmonate zim domain, LFY: leafy, MYB: MYB domain protein, MYC2: transcription factor MYC2, NCED: nine-cis-epoxycarotenoid dioxygenase 2, SAUR63: auxin-responsive protein saur63, SAW1: swollen anther wall 1, SEP: sepallata, SLR1: slender rice 1, SPL: squamosa promoter binding protein-like, SOC1: suppressor of overexpression of CO1, SVP: short vegetative phase, TCP15: teosinte branched 1–cycloidea–pcf, TEM: tempranillo, TFL1: terminal flower 1, TPS11/12: terpene synthase 11/12, VRN1-GA: vernalization 1-GA, ZIP: HD-zipper family.

4.1. Flowering

In Arabidopsis, flowering is restrained by the joint action of several repressor proteins, including SHORT VEGETATIVE PHASE (SVP), FLOWERING LOCUS C (FLC), and Early Flowering 3 (ELF3). GA inhibits the expression of SVP and ELF3 , through the action of the GAI ASSOCIATED FACTOR 1-TOPLESS RELATED (GAF1-TPR) complex, allowing the transcription of the floral integrator SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 ( SOC1 ) and the leaf-derived mobile signal FLOWERING LOCUS T ( FT ) and the transition to the flowering process [ 121 , 122 , 123 ]. On the other hand, when days are too short, activation of SVP by PHOSPHORYLETHANOLAMINE CYTIDYLYLTRANSFERASE 1 (PECT1) reduces GA levels through the repression of GA20ox and inhibits floral transition of the shoot apex [ 124 , 125 ]. Under short-day conditions, GA activates SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 3 ( SPL3 ) via SOC1 and enhances the expression of LEAFY ( LFY ), which induces flowering by activation of APETALA 1 ( AP1 ) and FRUITFULL ( FUL ) [ 126 , 127 ]. In non-flowering promoting conditions, other genes of the SPL family have a key role in floral induction. This aging-dependent flowering pathway is mediated by miR156 in response to GA. SPL15 interacts with SOC1 to activate FUL and promote floral primordia development [ 128 ]. The indirect modulation of SPL genes by GA through miR156 has also been reported in Chinese chestnut [ 129 ]. On the other hand, under long-day conditions in Arabidopsis, DELLA prevents flowering by physically interacting with the photoperiod-related TF CONSTANS (CO), blocking its activity. Although GA signaling does not directly regulate CO levels, it mediates flowering by repressing the transcriptional activity of CO, the master regulator of the photoperiod flowering pathway, thus establishing a direct link between this route and GA [ 130 ]. Furthermore, histone deacetylation is required during the transition from vegetative growth in short days to flowering in long days which depends on photoperiod and intervenes in the GA signaling pathway [ 131 ]. In Chrysanthemum, flowering time and photoperiod are influenced by the BBX24 gene, which inhibits the expression of the flowering promoters CO , FT , and SOC1 genes as well as the GA biosynthesis genes GA20ox and GA3ox [ 132 ]. Similarly, in Arabidopsis, TEM1 and TEM2 genes link photoperiod and GA-dependent flowering of plants under short and long days by regulating the expression of genes ( GA3ox1 and GA3ox2 ) involved in GA biosynthesis [ 133 ].

Similar results have been found in other non-model species. LFY and SOC1 , involved in floral meristem determinacy, are upregulated by GA in Jatropha curcas and chrysanthemums [ 134 , 135 ], although the induction seems more relevant in the latter. In J. curcas , the floral identity genes AP3 , PISTILLATA ( PI ), and SEPALLATA ( SEP ) SEP1-3 are activated by exogenous GA 3 addition [ 134 ]. The application of exogenous GA 3 to induce tree peony reflowering inhibits GA2ox , together with ZIP and NCED , and at the same time promotes the expression of ent -copalyl diphosphate synthase ( CPS ). Upregulation of CPS increases endogenous GA 3 level and reduces ABA content, suggesting that changes in ABA/GA balance allow bud dormancy release and reflowering in autumn [ 136 , 137 ].

The relevance of GA extends to flowering regulation through the vernalization pathway [ 138 ]. VERNALIZATION 1 ( VRN1 ) gene promotes GA biosynthesis and favors the induction of flowering in Winter canola [ 139 ], Pak Choi [ 140 ], or cereal crops [ 141 ]. In addition, wheat spike development, via SOC1 , is induced by GA under short days but only in presence of VRN1 [ 142 ]. Moreover, GA plays a relevant role in the regulation of the flowering of cereal crops [ 141 , 143 ]. Thus, GA emerges as a potential target for flowering and crop yield modulation.

However, there seem to be some species-specific features concerning the flowering-promoting activity of GA. Indeed, the inhibitory effect of GA on flowering has been reported in several perennial trees [ 144 ] and in relevant tree crops such as sweet orange [ 145 ] and other citrus species [ 146 ]. In apple, the GA-induced repression of flowering takes place through the regulation of TERMINAL FLOWER 1 ( TFL1 )-like genes [ 147 ]. In addition, GA repression by spermidine induces flowering in apple [ 148 ]. These contrasting effect of GA in some woody and non-woody species requires further research, but once again precludes the establishment of comprehensive patterns of GA responses.

4.2. Flower Formation and Fertilization

Several processes related to flower development are triggered by GA. In Arabidopsis, the GA-induced degradation of the DELLA proteins RGA, RGL1, and RGL2 promotes the formation of petal, stamen, and anther [ 149 ]. GAs also induce pollen formation as they allow cell wall development during meiotic cytokinesis [ 150 ]. Likewise, they stimulate filament elongation, by the activation of TCP15 , which in turn induces SMALL AUXIN UP RNA 63 ( SAUR63 ) genes [ 151 ].

Despite their usual antagonistic effects, GA and JA act synergistically in several processes of flower development. In this context, GA induces the biosynthesis of jasmonates, which enhance the expression of several MYB TFs permitting the correct formation of stamen and development of male fertility [ 152 ]. Indeed, both the jasmonates-related repressor proteins JASMONATE ZIM-DOMAIN (JAZ) and DELLA act synergistically to repress filament development [ 153 ]. The SWOLLEN ANTHER WALL 1 ( SAW1 ) zinc-finger TF enhances GA20ox3 expression in rice promoting microspore and anther development and dehiscence through GAMYB , while the same GAMYB gene is the target of miRNA159 in yellow lupin controlling pollen release [ 154 , 155 ]. In the presence of GA and jasmonates, MYC2 induces TERPENE SYNTHASE genes TPS11 and TPS21 , permitting the emission of volatile sesquiterpenes necessary for flower development [ 156 ]. Therefore, GA-related induction of flower organ formation seems to rely on cooperation with jasmonates.

The ability of GA to regulate flowering is also linked to stress responses. At low temperatures, in rice, the drop of endogenous GA content due to the repression of the GA20ox3 and GA3ox1 genes and the increase in the SLR1 DELLA protein blocks pollen production and drives infertility, but the process can be reverted by adding exogenous GA [ 157 ]. Moreover, treatments with exogenous GA 3 show that GA regulates anther and pollen development by improving cold tolerance in almond [ 158 ]. In rapeseed, male sterility is also produced after high-temperature treatments, which interferes with the GA signaling pathway [ 159 ]. Thus, the ability of GA to integrate temperature-linked information into the flowering process enables the adjustment of these responses under fluctuating conditions in the field.

Nonetheless, a negative effect of GAs in some flower formation processes has also been reported. They inhibit ovule primordia formation in both Arabidopsis and tomato, although the mechanism of this inhibition is different. In spite of acting synergistically in various developmental processes, BRs seem to downregulate GA20ox1 during ovule formation in tomato, playing a negative role in GA biosynthesis during this process. In this way, BRs stabilize DELLA proteins allowing ovule primordia formation, but both these hormones act independently in Arabidopsis [ 160 ].

5. Fruit Development

The modulation of fruit traits by the application of phytohormones and plant growth regulators has the utmost relevance in agronomy and a significant economic impact. The molecular mechanisms by which GA influences such traits along with fruit formation are beginning to be understood, showing that the cross-talk of GA with other hormones such as ABA is key in fruit development [ 161 ] and ripening in species such as strawberry [ 162 ]. GA activates ALCATRAZ ( ALC ) genes which govern the fructification process in Arabidopsis [ 163 ]. In spite of being a key hormone in fruit set [ 164 , 165 ], GA prevents fruit ripening in strawberry [ 166 ], pear [ 165 ], or tomato through the inhibition of RIPENING INHIBITOR ( RIN ), NON-RIPENING ( NOR ), and COLORLESS NON-RIPENING ( CNR ) genes [ 167 , 168 ]. Besides, GA is involved in other fruit development-related processes. It promotes the expansion of cells, increasing fruit weight without any loss of quality traits in pineapple [ 169 ] and apple [ 170 ], control chlorophyll and carotenoid metabolism to produce orange regreening [ 171 ], and modulate tomato morphology and firmness by controlling the activity of Sly-miR159 [ 172 ] and FIRM SKIN 1 ( FIS1 ) [ 173 ], respectively.

The SPATULA ( SPT ) gene, as well as the DELLA proteins, repress fruit development in Arabidopsis. This process can be reverted by the addition of exogenous GA. However, SPT does not interact with GID1 and consequently, it cannot be degraded by GA. Nevertheless, it is suggested that SPT can interact with other unidentified TF which is degraded, in an example of a DELLA-independent GA-driven process [ 174 ].

The effect of GA on parthenocarpy has also been reported. It induces this process by controlling cell division and cell expansion in atemoya, whereas fruit set and parthenocarpy are induced in 2,4-D-treated pear plants through GA biosynthesis enhancement [ 175 , 176 ]. In line with this, the overexpression of the pear gene PbGA20ox2 in tomato leads to parthenocarpic fruit formation [ 177 ].

These studies highlight the potential role of GA treatments in fruit growing since they seem to promote fructification and improvement of fruit quality in diverse species.

6. Seed Germination

Determination of seed dormancy and the optimal moment to initiate germination is critical for improving plant livelihood and avoiding potential threats in the first stages of seedling development. It is well established that GA is the main hormone involved in seed dormancy breakdown, and the ABA/GA balance is the major regulator of seed dormancy and germination in wheat [ 178 ] and rice [ 179 ], with high GA content leading to decreased dormancy. In rice, the interplay between GA and BRs through the activity of LEA genes has also been shown to influence dormancy [ 180 ]. The main GA-related signaling pathways influencing seed germination are shown in Figure 3 . GA, particularly GA 1 and GA 4 , enhances seed germination in monocots such as macawn palm [ 181 ] and dicots such as red bayberry [ 182 ], while in Arabidopsis they promote the degradation of RGL2, the main repressor of seed germination [ 183 ]. DELLA degradation by the increase in GA in embedded Arabidopsis seeds also promotes seed germination by releasing ARABIDOPSIS THALIANA MERISTEM LAYER 1 (ATML1) and PROTODERMAL FACTOR2 (PDF2) from DELLA and allowing the expression of the L1 box gene [ 184 ]. In barley and rice, the α-amylase synthesis required during seed germination is induced by GAs [ 185 , 186 , 187 ].

Schematic representation of the GA-related signaling involved in seed germination. Arrows indicate activation and blunt-end lines indicate repression or inhibition. See text for details and references. ABA1/ZEP: aba1/zeaxanthin epoxidase, ATML1: Arabidopsis thaliana meristem layer 1, CRY: cryptochrome, CWRP: cell-wall-remodeling-protein, DAG1: dof-type zinc finger DNA-binding protein, DOG1: delay of germination 1, FUS3: fusca3, GA2ox: GA2oxidase, GA3ox: GA3oxidase, HSF: heat shock factor, HSP: heat shock protein, HYH: hy5 homolog, LEA: late embryogenesis abundant, LEC1: leafy cotyledon 1, PDF2: protodermal factor 2, PHYB: phytochrome B, PIF1: phytochrome-interacting factor 4, PIL5: phytochrome-interacting factor-like 5, PWR: powerdress, RVE1: reveille 1, RGL2: rga-like protein 2, SOM: somnus, SPT: spatula, SPY: spindly, VOZ1/2: vascular plant one-zinc finger.

DELAY OF GERMINATION ( DOG1 ) gene expression and protein levels are directly correlated with seed dormancy, being a checkpoint for dormancy release in freshly harvested seeds in an ABA-independent fashion [ 188 ]. DOG1 also regulates the temperature window for seed germination in different species. It modulates GA20ox expression in a temperature-dependent way, thus attaining the required levels of GA to induce CELL-WALL-REMODELING PROTEINS ( CWRP ) genes, which alter the mechanical properties of endosperm [ 189 ] allowing the weakening of endosperm in cress [ 190 ]. In addition, GA induces the enzymatic degradation of mannans in endosperm cell walls through the activity of endo-β-mannanase [ 191 ]. ABA-INSENSITIVE4 (ABI4) promotes ABA synthesis and GA2ox7 expression, inhibiting GA biosynthesis and, therefore, maintaining seed dormancy and blocking germination [ 192 , 193 ]. In addition, ABA also represses germination through the activation of miR9678 reinforcing the importance of GA biosynthesis in the ABA/GA balance and the key role of this balance in wheat [ 194 , 195 ] or maize [ 196 ] seed germination. At low temperatures, GA deactivates SOMNUS ( SOM ) and promotes seed germination. However, at high temperatures, SOM expression is enhanced directly by DELLA proteins and ABA [ 197 ] and epigenetically by the AGAMOUS-LIKE 67-EARLY BOLTING IN SHORT DAYS (AGL67-EBS) complex [ 198 ], inhibiting GA synthesis and thus preventing seed germination. Moreover, at supra-optimal temperatures, HEAT SHOCK PROTEIN (HSP) and HEAT SHOCK FACTOR (HSF) activate FUSCA3 (FUS3) protein synthesis and accumulation. This process drives ABA synthesis and GA degradation, blocking seed germination [ 199 ]. ABI3 and SOM activity is regulated, depending on temperature, by differential histone acetylation mediated by POWERDRESS (PWR), which represses SOM under normal temperature conditions [ 200 ]. These data show again the ability of GA to integrate temperature-linked information into gene expression.

Penfield et al. (2005) [ 201 ] showed that PHYTOCHROME-INTERACTING FACTOR3-LIKE5 (PIL5) and SPT are implicated in seed germination through the repression of GA-3ox gene and thus GA synthesis. In a light-dependent way, PIL5 inhibits seed germination. PIL represses GA biosynthesis genes and promotes GA catabolism in a direct and indirect way, activating SOM [ 202 ] and DAG1 , which inhibits GA3ox1 [ 203 , 204 ]. Furthermore, light conditions and GA control seed germination. In barley, red light has no effect on germination but blue light and cryptochrome activate GA2ox and inactive GA3ox , which reduces GA levels and blocks germination [ 205 , 206 ]. Nonetheless, in Arabidopsis, degradation of PIL5 by red light allows seed germination [ 207 ]. Upon light activation, phyB interacts with FAR RED ELONGATED HYPOCOTYL 3 (FHY3) and represses REVEILLE 1 ( RVE1 ) and RVE2 , which promote seed dormancy by inhibiting GA biosynthesis and stabilizing RGL2 DELLA protein [ 208 ], and FHY3 enhances GA synthesis through SPT activation [ 209 ]. Seed germination is also repressed through the regulation of PIF target genes VASCULAR PLANT ONE-ZINC FINGER ( VOZ ) VOZ1 and VOZ2 zinc finger TFs mediated by the inhibition of GA synthesis. The active form of phyB represses PIF1 , VOZ1 , and VOZ2 and enhances seed germination [ 210 ]. In addition, blue light also alleviates seed dormancy by phyB stimulation and phyA repression, and leads to GA synthesis and signaling through HY5 HOMOLOG ( HYH ) action in Arabidopsis [ 211 ], in a new example of light-quality integration driven by GA.

Environmental differences between wet and dry seasons modulate the germination of wolf apple seeds mainly due to GA and ABA seed content modification, allowing the germination only in the most favorable conditions [ 212 ]. Other factors such as maternal plant environment affect seed germination in Arabidopsis [ 213 ]. Recently, in soybean, Chen et al. (2020) [ 214 ] found that shading in mother plants promotes seed germination through GA biosynthesis enhancement and ABA synthesis repression.

H 2 O 2 enhances seed germination in different species [ 215 ]. Reactive oxygen species (ROS), which induce ABA catabolism and GA biosynthesis genes, enhance seed germination and vice versa, ROS synthesis inhibition reduces significantly germination in wild cardoon [ 216 ]. On the other hand, 1-Cys Prx ( AtPER1 ), a seed-specific anti-oxidant peroxiredoxin, is accumulated during seed development, maintaining seed dormancy through ROS inhibition [ 217 ]. Moreover, GA promotes embryo maturation by releasing LEAFY COTYLEDON 1 (LEC1) from DELLA interaction [ 218 ].

Additionally, GA seems to participate in somatic embryogenesis in Medicago truncatula [ 219 ] and Arabidopsis. Activation of FUS3 by the somatic embryogenesis-related TF AGAMOUS-Like 15 (AGL15) reduces the expression of the biosynthetic gene GA3ox2 and induces the expression of GA-2ox6 , involved in the inactivation of active GA, thus reducing GA content. Another embryogenesis-related gene, LEC2, is induced by GA and enhances the auxin-responsive genes YUCCA ( YUC ) YUC2 , YUC4 , and INDOLE-ACETIC ACID-INDUCED PROTEIN 30 ( IAA30 ), thus promoting somatic embryogenesis. In Arabidopsis, upregulation of IAA30 expression along with low GA levels promotes somatic embryogenesis [ 220 ]. Thereby, the involvement of GA in this developmental process seems to rely on the interaction with the auxin signaling machinery.

7. Current and Potential Applications

The relevance of GA in modern agriculture cannot be underestimated. From the Green Revolution to nowadays crop production, manipulation of GA content has brought significant improvements in crop yield and quality.

Industrial production of the five classical phytohormones for agronomical or research purposes is an important business market worldwide that is led by Europe, which represents more than half of the market share, and followed by the USA (23.6%) and Asia (13.6%) [ 221 ]. In this market, the prominence of the USA stands out as the biggest supplier of these products in America and France, with the latter representing 21.9% of the European market share. However, it is expected that the countries of the Asia Pacific region, with a leading role for China, will exhibit significant growth opportunities for this market [ 222 ]. Concerning the data for each family of compounds, the market of phytohormone production was led in 2020 by cytokinins, which represent 38.1% of plant growth regulators market share, followed by auxins and GA [ 222 ]. However, this gap is expected to narrow in the coming years. The cytokinins market, mainly used for agricultural purposes, especially in cotton production, is expected to grow at a composed annual growth rate (CAGR) of 4.9% until 2027, reaching a market value of USD 2.4 billion, with the Asia Pacific region holding 41% of market share [ 223 ]. Auxins, which are the second largest plant growth regulators in terms of market share nowadays (dominated by North America with 38.7% of market share), are expected to grow at a CAGR of 4.5% until 2027 and a forecasted value of USD 1.1 billion. Auxin production growth will be driven by cotton production demanded by the textile sector and by auxin application for organic fruit and vegetable production [ 224 ]. Ethylene production is also expected to grow at a CAGR of 5.5%. Nevertheless, although it is expected that ethylene production will grow in all market segments, the main driver of this market, and its future evolution, is its use for plastic production and in the automotive industry [ 225 ]. The ABA market is projected to grow at a CAGR of 4.2% until 2028, which is expected to reach USD 0.65 billion thanks to investments in agriculture in Asia Pacific countries [ 226 ]. The global market linked to GA and related compounds was estimated at USD 500 million in 2015, although it is expected to grow up to USD 1.42 billion by 2027. A CAGR of 8.8% between 2017 and 2027 is forecasted, with a market growing at a 10% rate in the Asian Pacific zone followed by Europe, 8.6%, and North America, 8.1%, which is today the region leader in market share. The use of GA for fruit production, which represent 67.7% of its current market, is expected to grow at a rate of 8.7% in the forecasted period, followed by their use for the malting of barley, which is expected to grow at a rate of 10.7%, sugarcane yield and seed production [ 227 ]. Taken together, these reports indicate that the GA market is projected to witness the fastest growth rate among the five classical phytohormones, almost doubling the other ones. Distinct steps in the biosynthesis process of GA can be inhibited by the application of several compounds which are currently used in agriculture [ 14 ]. Greater knowledge of GA molecular activity routes and the identification of the key genes involved in GA responses could provide the tools needed for the improvement of the agronomic performance of crops, whether by means of genetic engineering or by the identification of cheaper compounds. In the present review, we have gathered the information available concerning the many aspects of plant biology in which GA plays a role, thus identifying new possible targets for crop improvement. With the world expected to attain 10 billion people by 2050, every possible advancement in agriculture is needed in order to feed the predicted population.

Among the several compounds applied in agriculture that influence GA levels, PBZ emerges as one of the more relevant as it not only reduces GA levels but also decreases ethylene production and increases cytokinin content. Although its use is under scrutiny and subject to tight regulations in some countries, and it has even been banned in other ones such as Sweden [ 228 ], PBZ is one of the most widely used GA inhibitors. It is expected that its use continues to grow in the coming years with a CAGR of 5%, reaching a global market value of USD 3.04 billion in the year 2028 from the current 2.06 [ 229 ]. Several agronomic traits are affected by PBZ treatment, including growth, water status, membrane stability, photosynthesis, etc. (reviewed in [ 230 ]). More detailed knowledge of the PBZ mode of action and the promotion of its application could provide an excellent manner to improve crop production and stress tolerance. Several other compounds have been found to inhibit GA synthesis in plants, and they are widely used in crop production [ 14 ]. However, we will focus on research that directly analyzes GA responses, and that might help in the development of novel strategies. As already mentioned, a better comprehension of GAs and their effects can lead to an increase in production or an improvement in quality traits. In forage crops such as Medicago truncatula GA is used to improve biomass production for land harnessing [ 231 ]. Shade avoidance response is a non-desirable trait in crops, but it may be modulated to increase wood production in Chinese red pine by means of specific GA treatment and light regimes [ 232 ]. Similarly, in hybrid poplar, the production of wood and biofuel can be increased by enhancing the expression of the GA biosynthesis gene GA20ox [ 233 ]. It is even possible to improve crops by ameliorating traditional practices such as grafting [ 234 ] or opening new markets by modifying the architecture and size of ornamental plants, such as orchids [ 235 ]. One of the most serious defects of cereal crops is the pre-harvest sprouting, which causes huge economic losses every year. It was found that in the mir156 rice mutant the gene IDEAL PLANT ARCHITECTURE 1 ( IPA1 ) modulates multiple steps in the GA pathway, enhancing seed dormancy, representing an effective method to suppress pre-harvest sprouting in rice [ 236 ]. In tomato, GA treatments enhance seed germination, reduce sprouting time and, moreover, accelerate plant growth, being potentially useful to increase plant production and quality [ 237 ].

Environmental damage derived from modern agriculture practices has become a great concern in our society, and the ongoing climate change scenario could even worse the effects. A deep understanding of GA and its action mechanisms might help to solve this problem. Knowledge about DELLA proteins and nitrogen interactions could enhance grain yield in rice and reduce nitrogen fertilizers dependence via chromatin modulation [ 238 ]. GA biosynthesis alteration can be a new molecular target for weed population control, for reducing herbicide usage, and therefore for reducing environmental damage, as it has been shown in wild radish [ 239 ]. GAs are, as a general rule, seed germination promoters. Glyphosate, one of the most widely used herbicides in the world seems to inhibit the P450 cytochrome enzymes, interfering in the de novo synthesis of GA [ 240 ]. However, since GA reduced germination of the invasive Heracleum sosnowskyi , GA treatment emerges as a good method to control these species populations [ 241 ]. Christiaens et al. (2012) [ 242 ] reported that in pre-cooled Helleborus niger and Helleborus x ericsmithii , GA application induces early flowering and enhances the number and size of flowers. Similarly, in blueberry, the inflorescence number and vegetative growth increased with GA 3 treatment [ 243 ]. However, in Matthiola incana , GA induced stem elongation but no effect on flowering was observed [ 244 ]. These results highlight another aspect of GA, as the species-specific responses and the variability found in some cases can discourage their application. As seen in the present review, these different responses can be significant between crop and forest species. A greater effort to unravel the reasons underlying these differences will increase confidence in GA application.

Vitis species are some of the most profitable crops worldwide, and GAs are extensively applied to improve their performance. GA addition increases grapes size [ 245 ], representing one of the first experiments carried out to use GA in agronomic production [ 246 ]. They are also used to reduce the density of bunches increasing fruit size [ 247 , 248 ] and decreasing bunch rot [ 249 , 250 , 251 ]. However, these results are not observed in all grapevine varieties [ 252 ]. Nowadays, the transcriptomics effects of GA are being studied to develop successful breeding and selection programs [ 253 ].

The positive effect on fruit yield has been reported in different species such as strawberry, pineapple, and blueberry [ 169 , 243 , 254 ]. Moreover, GA increases plant height [ 255 ] and grain yield in rice [ 256 ], maize, and soybean [ 257 , 258 , 259 ]. Based on these data, it has been suggested that the manipulation of the copy number of GA-related genes might be an interesting strategy to enhance plant yield [ 260 ]. On the other hand, early application of PBZ can increase potato yield, and its application is recommended in high-temperature zones [ 261 ].

Proper control of plant stress responses can avoid yield loss derived from adverse environmental conditions. GA has been found to modulate plant responses to stress. Usually, GA activity is repressed in the presence of different stresses to reduce growth and improve defense mechanisms [ 17 ]. Moreover, more specific research is needed to clarify the GA role in response to biotic stress. GAs can be used to fight biotic stress since they induce resistance to Spodoptera frugiperda [ 262 ] or to Candidatus Liberibacter asiaticus [ 263 ]. The role of GA on phytoremediation has also been shown, resulting in both ecological and economic benefits. When GA is combined with pressmud it allows sunflower plants to grow in chromium (Cr(VI)) contaminated soil by stabilization of Cr [ 264 ]. In addition, IAA and GA 3 application to Brassica juncea enhance phytoremediation in soils contaminated with cadmium and uranium [ 265 ]. Foliar application of GA to Corchorus capsularis allows the phytoremediation of copper-contaminated soils [ 266 ], highlighting their putative role to improve crop production in polluted soils, a problem of increasing relevance worldwide.

As already seen, GA weighs in on a plethora of plant developmental processes. This knowledge could be used to promote its action, producing enriched functional foods [ 267 ]. By contrast, the inhibition of GA could be used to avoid GA-related proteins which can cause medical conditions such as allergic diseases to pepper, cedar [ 268 ], or strawberry [ 269 ]. Thus, a deeper knowledge of GA actions could be useful not only for scientific or productive purposes but also from a food safety point of view.

The development of precise gene-editing techniques has opened a new era in plant research, allowing for the accurate modification of gene sequences that can alter plant performance in a transgene-free manner. CRISPR/Cas9, the most popular of these techniques, is beginning to be applied in relevant crops with the aim of modifying GA-related responses to improve plant performance. For instance, signaling mutants in tomato have shown improved responses to water deficit conditions without lowering harvest index [ 66 ], while GA content modification through the modulation of GA20 oxidases has been reported in rice and maize [ 270 , 271 , 272 ]. As shown in the present review, many other GA-related target genes can be modified by these same means, thus opening the possibility for accurate and beneficial editing of crops and trees.

However, despite their paramount relevance, there might be alternatives to molecular manipulation and chemical agriculture. GA research started, as already seen, due to the study of a fungus that was able to synthesize this plant growth regulator. Since then, researchers have discovered many bacteria and fungi species that are part of the soil microbiome and that are able to produce gibberellins [ 273 , 274 ]. Thus, crop production can be improved through rhizosphere modification as has already been done [ 46 , 275 ].

8. Conclusions

Although historically shadowed in research by other phytohormones, the impact of GA in agriculture has driven an increased interest in its study. Nonetheless, the understanding of the molecular mechanisms involved in the GA-related responses still lags behind that of other phytohormones.

However, research in recent years has led to the identification of key genes involved in the responses to GA, thus enabling the design of more specific research and breeding programs. As shown above, careful planning is mandatory as several traits can be affected when modifying GA content or signaling routes. Nonetheless, we have shown that for some GA-related developmental processes, such as adventitious rooting or flowering, significant differences can be found between trees and crops, raising the question about the transferability of knowledge between species. Relevantly, GA seems to integrate specific cues into their responses, such as light quality or age of the plant, which might help explain those differences. Therefore, the present review might help researchers to plan their strategies by taking these differences into account. Besides, GA cooperation with other phytohormones in specific responses such as stress and flower formation is another significant issue that deserves greater attention. Moreover, temperature and light quality information seem to be integrated, at least in part, through the modulation of GA levels, thus offering new potential targets for improved plant performance through the use of biotechnological tools. In particular, the modulation of GA levels might be a potential tool for the development of plant varieties able to stand warmer temperatures and harsh conditions, thus assuring a more resilient vegetable production under a climate change scenario.

GA is a versatile plant growth regulator involved in a barrage of developmental processes. It is worth noticing their implication in xylogenesis, shoot elongation, root development, flowering, and seed germination. However, in most cases, GA activity seems to rely on its balance with ABA. Thus, future research should be focused not only on GA modulation itself but on its relationship with ABA, since the ABA/GA balance is a major modulator of physiological responses. The present review shows that, even if no direct link exists at the molecular level between ABA and GA on many occasions, both hormones act antagonistically in virtually every major physiological process, together influencing key plant development processes. Therefore, ABA content modulation, whether increasing its content through direct application of ABA or reducing its content with the use of specific inhibitors (abamine, abscinazole-E3M), represents a potential tool for the fine-tuning of crop responses.

The examples shown on the direct implications of GA in agronomical performance highlight the importance of these compounds in modern plant production and the potential applicability to other crop species, leading to a qualitative and quantitative improvement in agricultural production. As research advances, the role of GA in the Green Revolution might just be one of the many improvements for agriculture they could provide. Despite the research knowledge gathered so far, the greater benefits might just be yet to come.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/plants11192650/s1 , Table S1. Genes up-regulated or down-regulated by GA action in each physiological process and species reported in the review; Table S2. Genes or proteins reported in the review which activate or inhibit GA signaling or synthesis pathways in each developmental process.

Funding Statement

this work was funded by Xunta de Galicia (Spain) through the projects IN607A and “Contrato Programa” 2021 (AGI/CSIC I+D+I 2021, Ref- ACAM 20210200033).

Author Contributions

Conceptualization, J.M.V.; investigation, R.C.-C.; writing—original draft preparation, R.C.-C.; visualization, R.C.-C.; visualization—editing, J.M.V.; writing—review and editing, J.M.V. and C.S.; supervision, C.S.; funding, N.V. and C.S. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Open access
• Published: 24 November 2021

Gibberellin in tomato: metabolism, signaling and role in drought responses

• Hagai Shohat 1 ,
• Natanella Illouz Eliaz 2 &
• David Weiss   ORCID: orcid.org/0000-0002-3253-8441 1  

Molecular Horticulture volume  1 , Article number:  15 ( 2021 ) Cite this article

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The growth-promoting hormone gibberellin (GA) regulates numerous developmental processes throughout the plant life cycle. It also affects plant response to biotic and abiotic stresses. GA metabolism and signaling in tomato ( Solanum lycopersicum ) have been studied in the last three decades and major components of the pathways were characterized. These include major biosynthesis and catabolism enzymes and signaling components, such as the three GA receptors GIBBERELLIN INSENSITIVE DWARF 1 (GID1) and DELLA protein PROCERA (PRO), the central response suppressor. The role of these components in tomato plant development and response to the environment have been investigated. Cultivated tomato, similar to many other crop plants, are susceptible to water deficiency. Numerous studies on tomato response to drought have been conducted, including the possible role of GA in tomato drought resistance. Most studies showed that reduced levels or activity of GA improves drought tolerance and drought avoidance. This review aims to provide an overview on GA biosynthesis and signaling in tomato, how drought affects these pathways and how changes in GA activity affect tomato plant response to water deficiency. It also presents the potential of using the GA pathway to generate drought-tolerant tomato plants with improved performance under both irrigation and water-limited conditions.

Introduction

Drought is a common and devastating abiotic stress which causes damage to crops worldwide (Dai, 2011 ; Tardieu, 2020 ). Water deficiency directly and indirectly suppresses major biochemical pathways, including photosynthesis and primary carbon metabolism, leading to inhibition of growth, flowering and fruit development (Zhu, 2016 ; Tardieu et al., 2018 ). Plants have adopted three major strategies to cope with drought: drought escape, drought tolerance and drought avoidance (Chaves et al., 2003 ). Some annual plants escape from severe drought by early flowering (Kooyers, 2015 ). Drought tolerance is acquired by osmotic adjustment (accumulation of osmolytes), accumulation of stress-protecting proteins and scavenging of reactive oxygen species (ROS) (Vinocur and Altman, 2005 ). All higher (vascular) plants exhibit ‘drought avoidance’ (drought-stress avoidance) responses during transient water-deficit episode. These include rapid stomatal closure and suppression of canopy growth to reduce transpiration (Brunner et al., 2015 ; Lind et al., 2015 ). At the same time, roots continue to grow, in search of new sources of water, a phenomenon called hydro- or xero-tropism (Feng et al., 2016 ; Dietrich, 2018 ). This leads to an increased root-to-shoot ratio and improved water balance.

Phytohormones play a central role in plant responses to drought (Verma et al., 2016 ; Gupta et al., 2020 ). During the early stages of soil dehydration, the major stress hormone abscisic acid (ABA) accumulates and induces various drought responses (Cutler et al., 2010 ), leading, in some plants, to drought tolerance, and in all higher plants to ‘drought avoidance’ (Kooyers, 2015 ). Numerous studies have shown that the growth-promoting hormones, auxin (Shani et al., 2017 ; Salehin et al., 2019 ), cytokinins (Nishiyama et al., 2011 , Nishiyama et al., 2011 ; Farber et al., 2016 ), brassinosteroids (Ye et al., 2017 ; Planas-Riverola et al., 2019 ; Xie et al., 2019 ) and gibberellins (GAs, Colebrook et al., 2014 ), reduce plant resistance to water deficiency.

The growth-promoting hormone GA regulates numerous developmental processes throughout the plant life cycle, from seed germination to fruit development (Yamaguchi, 2008 ; Daviere and Achard, 2013 ). GA also negatively affects plant response to biotic and abiotic stresses (Navarro et al., 2008 ; Colebrook et al., 2014 ). GA and inhibitors of GA biosynthesis are widely used in agriculture to control germination, stem elongation, plant architecture, flowering time and fruit development (Rademacher, 2016 ). Accumulating evidence suggest that inhibition of GA activity, either by chemical treatments or by gene-editing, can also be used to improve plant performance under stress conditions (Eshed and Lippman, 2019 ). Drought opposes GA-induced processes; it inhibits seed germination, shoot growth and fruit development (Munns and Tester, 2008 ). Several studies have shown that osmotic stress inhibits GA accumulation (Achard et al., 2006 ; Nelissen et al., 2018 ; Shohat et al., 2021 ). In turn, the reduced GA levels lead to the accumulation of DELLA, the master growth inhibitor, which promotes adaptation to abiotic stresses, including drought (Colebrook et al., 2014 ).

Tomato ( Solanum lycopersicum ), like many other crops, is susceptible to drought (Iovieno et al., 2016 ; Zhou et al., 2019 ). In the past two decades, numerous studies on tomato response to drought have been conducted (Gur and Zamir, 2004 ; Gong et al., 2010 ), including studies assessing the role of GA in such processes (Nir et al., 2014 , 2017 ; Omena-Garcia et al., 2019 ; Illouz-Eliaz et al., 2020 ; Shohat et al., 2021 ). Here, we review the current knowledge on GA biosynthesis and signaling in tomato, how drought affects these pathways and how these changes in hormone activity affect tomato plant response to water deficiency. We also present the potential in exploiting the GA pathway to generate drought-tolerant tomato plants with improved performance under irrigation and water-limited conditions.

GA metabolism and signaling

Ga metabolism.

A comprehensive and up-to-date review on GA metabolism was recently published by Hedden ( 2020 ). GAs are diterpenoids, produced from the general substrate geranylgeranyl diphosphate (GGPP), which is converted to ent- kaurene by ent- copalyl diphosphate synthase (CPS) and ent- kaurene synthase (KS) in the plastids (Fig.  1 ). ent- kaurene is then converted to the first GA precursor GA 12 , by two cytochrome P450 monooxygenases, i.e., ent- kaurene oxidase (KO) and ent- kaurenoic acid oxidase (KAO), which act on the outer membrane of the plastids and in the endoplasmic reticulum, respectively. Bioactive GAs, are synthesized in the cytosol from GA 12 and GA 53 by two 2-oxoglutarate-dependent dioxygenases (2-ODDs) families, GA 20-oxidases (GA20ox) and GA 3-oxidases (GA3ox). GA 12 is converted to GA 9, and GA 53 to GA 20, by GA20oxs. Then, GA3oxs, convert GA 20 and GA 9 by 3β-hydroxylation to GA 1 and to GA 4 , respectively.

GA metabolic and signaling pathways in tomato. The scheme shows GA biosynthesis enzymes (green), GA deactivation enzymes (red) and bioactive GAs (black squares)

GA deactivation plays a central role in the regulation of bioactive GA accumulation in response to both environmental and developmental cues (Yamaguchi et al., 2008 ). GA inactivation is primarily catalyzed by another family of 2-ODD enzymes, known as GA 2-oxidases (GA2ox), which reduce the levels of bioactive GAs. GA2ox genes are classified as either class I, which catalyze the conversion of bioactive GAs (GA 1 and GA 4 ) or their direct precursors (GA 20 and GA 9 ) to biologically inactive GA derivatives , or class III, which use the early GA precursors GA 12 and GA 53 as substrates. Other GA deactivation mechanisms are driven by cytochrome P450s, which acts on non-13-hydroxylated GAs (GA 12 , GA 9 and GA 4 ) to produce epoxidized GAs that lack biological activity (Zhu et al., 2006 ), and GA METHYL TRANSFERASE1 (GAMT1) enzymes, which methylate bioactive GAs to form inactive GA methyl esters (Varbanova et al., 2007 ).

GA sensing and signaling

GA acts by triggering the destruction of DELLA (Locascio et al., 2013 ). While DELLAs lack a DNA-binding domain, they interact with transcription factors to activate and repress transcription (Zentella et al., 2007 ; Yoshida et al., 2014 ). GA binding to the GIBBERELLIN-INSENSITIVE DWARF1 (GID1) receptor increases receptor affinity to DELLA, leading to the formation of the GA-GID1-DELLA complex (Fig. 1 ). This facilitates the interaction of DELLA with an SCF E3 ubiquitin ligase complex via the GID2/SLEEPY1 (SLY1) F-box protein. The SCF SLY1 complex polyubiquitinates DELLA, targeting it for degradation by the 26S proteasome (Sasaki et al., 2003 ; Dill et al., 2004 ; Griffiths et al., 2006 ; Harberd et al., 2009 ; Hauvermale et al., 2012 ), which subsequently leads to transcriptional reprogramming and activation of GA-dependent responses.

GID1 interacts with DELLA’s N-terminal region which harbors the conserved DELLA and VHYNP motifs. The C-terminal region of DELLA interacts with various transcription factors to repress GA responses, rendering it the element responsible for DELLA activity (Sun et al., 2012 ; Locascio et al., 2013 ). Mutations in the N-terminal region of DELLA block its interaction with the GID1 receptor, thereby preventing DELLA degradation (Fig.  2 ). Such gain-of-function dominant mutations constitutively inhibit GA responses, including growth. Several studies have shown that these mutants are tolerant to various biotic and abiotic stresses, including drought (Magome et al., 2008 ; Bari et al., Bari and Jones, 2009 ; Nir et al., 2017 ). By contrast, loss-of-function, recessive mutations in the C-terminal region of DELLA are associated with constitutive GA responses (Fig. 2 ), resulting in excess elongation and stress-susceptible plants (Achard et al., 2006 , 2008 ; Nir et al., 2017 ).

Schematic presentation of the two types of DELLA mutants and their effect on GA signaling. Wild-type (left), DELLA loss-of-function (center) and gain-of-function (right) mutations. Red X represents the mutation site in DELLA

GA metabolism, sensing and signaling in tomato

Tomato is widely used as a model system for crop research; it is diploid, self-compatible, simple to cross, easy to grow and has an efficient transformation protocol. As a result, well characterized genetic materials and tools, sequenced genome and extensive gene expression profiles are available (The Tomato Genome Consortium, 2012 ). Studies in tomato cover many topics, including flowering, fruit development and maturation, secondary metabolism, interaction with the environment and hormone activity, in general, and GA metabolism and signaling, in particular (Serrani et al., 2007 ; Livne et al., 2015 ; Illouz-Eliaz et al., 2019 ; Israeli et al., 2019 ; Shinozaki et al., 2020 ).

The GA metabolism and signaling pathways in tomato are summarized in Fig. 1 . gib-1 , gib-2 , and gib-3 , three GA-deficient mutants identified and characterized in tomato (Koornneef et al., 1990 ; Bensen and Zeevaart, 1990 ) exhibit typical GA-deficiency phenotypes, including dwarfism, small and dark green leaves and delayed seed germination, all of which are corrected by application of exogenous GA (Butcher et al., 1990 ). GIB-1 encodes CPS , GIB-3 encodes KS and GIB-2 encodes KAO (Bensen and Zeevaart, 1990 ; Koornneef et al., 1990 ). The tomato CPS, KS and KO are encoded by a single gene, and KAO, which forms GA 12 , has four paralogs (Pattison et al., 2015 ).

The later steps in the pathway are catalyzed by rather large families of 2-ODDs; 8 putative GA20ox, 6 putative GA3ox and 11 putative GA2ox (Pattison et al., 2015 ; Chen et al., 2016 ; Shohat et al., 2021 ). CRISPR-derived ga20ox1 and ga20ox2 mutants, recently characterized in tomato (Shohat et al., 2021 ), exhibit mild GA-deficiency phenotypes, including shorter stems and smaller leaves. The ga20ox1/ga20ox2 double mutant exhibited an additive effect, including severe dwarfism, dark-green, small leaves and delayed germination, suggesting that GA20ox1 and GA20ox2 play a key role in GA biosynthesis in tomato. A mutation in the tomato class III GA-deactivating gene GA2ox7 increases the levels of bioactive GA 1 and GA 4 , and is associated with a unique phenotype, i.e., elongated internodes but normal leaves, suggesting limited stem-to-leaf transport of bioactive GAs (Schrager-Lavelle et al., 2019 ).

The canonical GA signal transduction pathway in tomato includes three GID1 receptors ( GID1a, GID1b1 and GID1b2 (Illouz-Eliaz et al., 2019 )), a single DELLA protein named PROCERA (PRO) and a single F-box protein, SLY1 (Jasinski et al., 2008 ; Illouz-Eliaz et al., 2019 , 2020 ). GID1a is the dominant GA receptor with the strongest effect on stem elongation and leaf growth. In contrast, flower growth is only affected in plants bearing type B GID1 receptor mutants. The gid1 single and double mutants exhibit almost normal growth, suggesting overlapping activities and high redundancy. Seeds of the triple gid1 mutant ( gid1 TRI ) only germinate upon embryo rescue and the plants exhibit extreme dwarfism and complete insensitivity to GA.

Three pro (DELLA) loss-of-function alleles were characterized in tomato (Jasinski et al., 2008 ; Lor et al., 2014 ; Livne et al., 2015 ). The conserved VHVID domain in the C-terminal region of PRO is required to repress GA responses (Bassel et al., 2008 ). A point mutation (T905 to A) in this domain, in pro , resulted in constitutive GA responses, leading to early germination, elongated stems and facultative parthenocarpy (Van Tuinen et al., 1999 ; Bassel et al., 2008 ). pro ΔGRAS , a null mutant of PRO (Livne et al., 2015 ) lacks the entire C′-terminal part of the protein, exhibits enhanced GA responses compared to pro, including an extremely elongated stem and obligatory parthenocarpy. Moreover, in contrast to the weak pro allele, pro ΔGRAS is fully insensitive to paclobutrazol and GA treatments. The third DELLA loss-of-function allele was generated using Transcription Activator-Like Effector Nucleases (TALENs, Lor et al., 2014 ). This mutant is null and phenocopies pro ΔGRAS . Transgenic tomato plants overexpressing the gain-of-function stable DELLA mutant protein proΔ17 which lacks the DELLA domain, exhibit a severe GA-deficient phenotype and GA insensitivity (Nir et al., 2017 ). Another gain-of-function allele was generated using CRISPR-Cas9 technology to target the DELLA domain in pro TALEN , turning its loss-of-function nature to gain-of-function (Zhu et al., 2019 ).

A CRISPR-derived tomato sly1 mutant exhibits severe dwarfism (Illouz-Eliaz et al., 2020 ). sly1 is insensitive to GA, suggesting a strong inhibition of GA signaling, confirming the importance of DELLA degradation via the proteasome pathway to relieve GA responses in tomato.

The role of GA and DELLA in tomato plant response to water deficiency and adaptation to drought

The role of DELLA in plant responses to abiotic stresses originated independently of GA; the liverwort Marchantia polymorpha DELLA ancestor regulates responses to stress despite the lack of GA and the canonical GA signaling pathway (Hernandez-Garcia et al., 2021 ). In higher plants, DELLA accumulation depends on GA and both, antagonistically, affect plant response to stress. Several studies in tomato have shown that inhibition of GA activity and accumulation of DELLA promote drought resistance by affecting several different metabolic and developmental processes throughout the plant life cycle, from seeds to mature plants (Fig.  3 , Nir et al., 2014 , 2017 ; Omena-Garcia et al., 2019 ; Illouz-Eliaz et al., 2019 , 2020 ; Shohat et al., 2021 ).

Low GA activity promotes drought resistance in tomato via several mechanisms. Low GA levels or activity promote ‘drought tolerance’ by osmoregulation (Omena Garcia et al., 2019 ). It also promotes ‘drought avoidance’ by inhibiting canopy growth, accelerating stomatal closure, reducing xylem expansion and proliferation and increasing root to shoot ratio (Nir et al., 2014 , 2017 ; Illouz Eliaz et al., 2020 ; Ramon et al., 2020 ; Shohat et al., 2020 , 2021 )

GA and drought tolerance in tomato

Tomato seeds are tolerant to desiccation and can germinate after years of dry storage (Priestley et al., 1985 ). ABA has a central role in the acquisition of desiccation tolerance (Ooms et al., 1993 ; Finkelstein et al., 2008 ) through its promotion of the activity of various major regulators of seed desiccation tolerance during seed maturation, including ABA INSENSITIVE3 (ABI3) , FUSCA3 ( FUS3 ) and LEAFY COTYLEDON1 ( LEC1 ) and LEC2 (To et al., To A et al., 2006 ). GA opposes ABA activity in seeds (Groot et al., 1987 ; Tyler et al., 2004 ; Steinbrecher and Leubner-Metzger, 2017 ), and also affects desiccation tolerance; tomato DELLA null mutant pro ∆GRAS seeds are susceptible to desiccation and fail to germinate even after short periods (days) of storage (Livne et al., 2015 ). This was attributed to the low expression of the ABA-regulated, drought tolerance-related genes ABI3 , FUS3 and LE25 in pro ∆GRAS seeds. It was therefore suggested that the accumulation of DELLA during seed maturation is important for the acquisition of ABA-induced long-term drought tolerance in tomato seeds.

Tolerance to drought can be acquired by osmotic adjustment, i.e., the accumulation of ions and organic solutes in the cells (Shabala and Shabala, 2011 ). Under water-deficit conditions, some plants accumulate high levels of solutes in their roots and leaves to reduce the cellular osmotic potential and maintain high turgor pressure (Turner, 2018 ). Omena-Garcia et al. ( 2019 ) reported that the GA-deficient gib-1, gib-2 and gib-3 tomato mutants accumulate higher levels of osmolytes, and were able to maintain higher leaf water content and leaf turgor under water-deficit conditions.

GA and ‘drought avoidance’ in tomato

All higher plants respond to water limitation by rapid stomatal closure and inhibition of shoot growth (Brunner et al., 2015 ). These responses reduce transpiration and water loss (Skirycz and Inzé, 2010 ). Nir et al. ( 2014 ) showed that inhibition of bioactive GA accumulation in tomato by overexpressing the Arabidopsis GAMT1 gene, reduces water loss under drought conditions. The reduced transpiration in the transgenic plants was ascribed to the smaller leaves and to reduced stomatal aperture. Later, Nir et al. ( 2017 ) showed that overexpression of the stable DELLA protein pro∆17 in tomato plants reduced stomatal aperture and transpiration, independently of leaf growth. Moreover, targeted overexpression of pro∆17 in guard cells was sufficient to reduce stomatal aperture, suggesting that PRO acts in guard cells in a cell-autonomous manner. In line with this, the DELLA loss-of-function pro mutant exhibits increased stomatal conductance and water loss under water-deficit conditions. This effect of GA/DELLA is likely part of the natural ‘drought avoidance’ response in tomato; under water-deficit conditions the expression of the GA deactivation gene GA2ox7 is strongly upregulated in guard cells, leading to reduced levels of bioactive stomatal GAs (Shohat et al., 2021 ). This upregulation of GA2ox7 is required for the rapid stomatal response to drought, as the loss of GA2ox7 activity inhibited stomatal closure in the early stages of soil dehydration (Shohat et al., 2021 ). A role for GA in stomatal movement was also described in Commelina benghalensis, Vicia faba and Fritillaria imperialis , where GA application increased stomatal aperture (Santakumari and Fletcher, 1987 ; Goring et al., 1990 ).

The effects of pro∆17 on stomatal closure and water loss were suppressed in the ABA-deficient sitiens ( sit ) tomato mutant, indicating that the effect of DELLA is ABA-dependent. While DELLA did not affect ABA levels, increased DELLA activity promoted ABA responses in guard cells (Nir et al., 2017 ; Shohat et al., 2020 ). RNAseq analysis of isolated guard cells derived from tomato plants with high versus low DELLA (PRO) activity, identified the ABA transporter ABA-IMPORTING TRANSPORTER 1.1 ( AIT1.1 ) as upregulated by PRO (Shohat et al., 2020 ). The CRISPR-derived ait1.1 mutant exhibits increased transpiration and reduced ABA-induced stomatal closure. ait1.1 also suppresses the promoting effect of DELLA on stomatal closure, suggesting that most, if not all, of the effects of GA/DELLA on stomatal response to water deficiency are related to the negative cross-talk between GA and ABA.

GA and DELLA also impact ‘drought avoidance’ through developmental responses. Reduced transpiration throughout prolonged periods of water deficiency is also achieved by growth suppression and the reduction of transpiration area (Salah and Tardieu, 1997 ). Several studies suggest that inhibition of GA accumulation under water-deficit conditions plays a role in drought-induced growth suppression (Skirycz and Inzé, 2010 ; Litvin et al., 2016 ). For example, low levels of GA in Populus inhibit growth and promote resistance to water-deficit conditions (Zawaski and Busov, 2014 ). Drought conditions inhibit GA accumulation in maize leaf elongation-zones and suppress their growth (Nelissen et al., 2018 ). The reduced GA levels in tomato under water-deficit conditions is a results of both, inhibition of GA biosynthesis and activation of GA catabolism (Litvin et al., 2016 ; Shohat et al., 2021 ). Water-deficit conditions inhibit the expression of the GA biosynthesis genes GA20ox1 and GA20ox2 , promote the expression of GA2ox7 , reduce the levels of bioactive GAs and suppress leaf expansion (Shohat et al., 2021 ). ga20ox1 and ga20ox2 mutants exhibit reduced whole-plant transpiration under water-deficit conditions due to their smaller canopy area.

While shoot growth is inhibited under water-deficit conditions, root growth is maintained, and even promoted, leading to increased root-to-shoot ratio (Sharp et al., 2004 ). These developmental changes improve water balance under water-limited conditions. Some evidence implies that GA has a role in altering root-to-shoot ratio under water-deficit conditions. Although GA promotes root elongation in Arabidopsis (Yaxley et al., 2001 ; Fu and Harberd, 2003 ), in some other species, GA has no effect or even suppresses root growth (Berova and Zlatev, 2000 ; Gou et al., 2010 ; Fonouni-Farde et al., 2019 ; Moriconi et al., 2019 ). Reduced GA levels or signaling promote lateral root density and growth in Populus (Gou et al., 2010 ). In Medicago , GA inhibits and the GA biosynthesis inhibitor paclobutrazol, promotes primary root elongation and lateral root counts (Fonouni-Farde et al., 2019 ). The DELLA loss-of-function sln1 barley mutant exhibits reduced root growth (Moriconi et al., 2019 ). In tomato, GA has a strong effect on shoot growth, but only a minor effect on primary root elongation (Ramon et al., 2020 ). In line with this, gid TRI exhibits a dramatically increased root-to-shoot ratio due to the strong inhibition of shoot growth, but only a mild effect on root elongation. Thus, inhibition of GA accumulation upon water deficiency is expected to restrict shoot growth without conferring an effect on root elongation and therefore, may contribute to the increased root-to-shoot ratio.

Low GA activity also reduces water loss in tomato through changes in the hydraulic conductivity; low GA activity in gid1a or sly1 mutants inhibits xylem-vessel expansion and proliferation and reduces hydraulic conductivity (Illouz-Eliaz et al., 2020 ). Under severe drought conditions, the effect of low GA activity on xylem expansion can also protect plants from cavitation and embolism (Ishihara and Hirasawa, 1978 ; Baum et al., 1999 ; Brodribb and Hill, 2000 ). Thus, inhibition of xylem expansion and proliferation by low GA activity may be another mechanism through which reduced GA promotes adaptation to prolonged periods of limited water.

Harnessing the GA pathway to improve tomato performance under water-limited conditions

Manipulation of the GA pathway has enormous potential in crop improvement (Eshed and Lippman, 2019 ). Mutations in the GA biosynthesis or signaling pathways have been used to improve crops. The best example is the introduction of semi-dwarf cereal crops in the 1960s, which led to a significant increase in yield. The semi-dwarf varieties are resistant to lodging even when excessively fertilized (Wu et al., 2020 ). Two major types of mutations are responsible for what has come to be known as the ‘Green Revolution’ (Hedden, 2003 ); a loss-of-function mutation in the SD1 gene encoding the GA biosynthesis enzyme GA20ox2 in rice (Monna et al., 2002 ; Sasaki et al., 2002 ; Spielmeyer et al., 2002 ), and a gain-of-function mutation in Rht1 , a gene encoding DELLA in wheat (Peng et al., 1999 ).

As described above, the GA pathway can also be harnessed in tomato to enhance resistance to abiotic stresses, including drought. Since GA and DELLA have a pleotropic effect on growth, a trade-off between yield and drought resistance is expected. However, this might only be true for strong inhibition of GA activity. Illouz-Eliaz et al. ( 2020 ) showed that while mutation in a single GA receptor (GID1a) suppressed growth in the field, it had no effect on yield, giving rise to a tomato line with a higher harvest index (fruit weight/plant fresh weight). This is a desired side-effect of GA inhibition, in that it allows higher planting density to obtain higher yield per unit area (Gifford and Evans, 1981 ). Thus, the ultimate goal is to generate mutants with mild dwarfism, normal yield under well-watered conditions and significantly improved drought resistance. Introduction of the CRISPR technology has made this more feasible to achieve within a relatively short time (Jinek et al., 2012 ; Brooks et al., 2014 ), in contrast to the decades required when using classical breeding (Bai and Lindhout, 2007 ). CRISPR-based technologies provide a variety of genome-editing tools, including targeted mutation knockouts (KOs), tissue-specific KOs, multiplex gene editing, targeted insertion, gene activation and precise genome editing (Brooks et al., 2014 ; Rodríguez-Leal et al., 2017 ; Zhu et al., 2020 ; Dong and Ronald, 2021 ; Pan et al., 2021 ). CRISPR has already been applied to improve the agronomical traits of an orphan Solanaceae crop ( Physalis pruinosa ) and a wild tomato species ( Solanum pimpinellifolium ), by simultaneously editing four genes involved in plant architecture (SP), flowering time (SP5G) and fruit size (SlCLV1/3 and SlWUS) (Lemmon et al., 2018 ; Li et al., 2018 ).

Possible GA pathway targets for CRISPR-based mutagenesis to increase drought resistance in tomato

Transduction of the GA signal is based on a cascade of interactions, i.e., GA with GID1, GID1 with DELLA and DELLA with SLY1. The possible interaction sites between these three signaling components are presented in Fig.  4 , and described elaborately by McGinnis et al. ( 2003 ), Murase et al. ( 2008 ) Hirano et al., ( 2010 ). Attenuating without eliminating the affinity between these interacting components, may lead to mild growth suppression without affecting yield, but with increased drought resistance. A rapid and efficient way to do so is by applying precise CRISPR-based genome-editing tools such as base editing (single base-pair substitution/deletion, Zhu et al., 2020 ).

Possible target sites in the major tomato signaling components to attenuate without eliminate GA responses. GA-GID1 interaction sites are indicated by green arrows, GID1-PRO interaction by blue arrows and PRO-SLY1 interaction by red arrows. The specific sites in homologous GID1, DELLA and SLY1 are elaborated in McGinnis et al., ( 2003 ), Murase et al., ( 2008 ) and Hirano et al., ( 2010 )

Perturbations of GA binding to GID1 can be obtained by site-specific mutations in the GA binding “pocket” of GID1 (Murase et al., 2008 ). Attenuating the affinity of GID1 to DELLA (PRO) can be achieved by mutations in the GID1 N-terminal extension (N-Ex) domain (Murase et al., 2008 ) or by mutations in the N-terminal region of PRO (GID1 binding site). However, deletion of PRO’s N-terminal causes severe dwarfism (Zhu et al., 2019 ). Thus, mutations in other sites, outside the N-terminal region, that affect GID1 binding, may generate weak gain-of-function alleles, as shown before in rice (Hirano et al., 2010 ). A mild reduction in GA signaling can also be obtained by interfering with the DELLA-SLY1 interaction. SLY1 has two conserved domains required for its interaction with DELLA, i.e., the GGF domain and the LSL domain (McGinnis et al., 2003 ). A CRISPR-derived tomato sly1 mutant, which carries a single nucleotide insertion, causing a frame shift and premature stop codon before the LSL domain, was already generated, but has a severe dwarf phenotype (Illouz-Eliaz et al., 2020 ). Using the same precise editing techniques to generate weak sly1 alleles which only reduces the affinity to DELLA, may provide fine-tuning of GA responses only.

Attenuation of GA signaling can also be achieved using multiple guide constructs to target various cis-regulatory elements in the promoters of GID1s, PRO or SLY1 . This is expected to generate a collection of alleles exhibiting changes in the expression levels and patterns and their subsequent activity, and to enable selection of drought-tolerant lines. It should be noted, however, that DELLAs are primarily regulated at the post-translational level (Blanco-Tourinan et al., 2020 ). Thus, this approach seems to be more relevant to GID1s and SLY1.

The GA signaling components in tomato are encoded by a small number of genes (single PRO and SLY1 and three GID1 s). Thus, mutation in a single gene might lead to undesired phenotypic changes and yield loss. Illouz-Eliaz et al. ( 2019 , 2020 ) show that although the gid1a mutant grows well under stable conditions, it exhibits phenotypic instability when grown under extreme, unstable environmental conditions in the field, leading, in some plants, to strong growth suppression and yield loss. Growth and yield instability might be prevented if the target gene belongs to a large family. For example, the enzymes in the later stages of the GA biosynthetic pathway are encoded by rather large gene families in all plant species. The tomato genome encodes 8 GA20ox s and 6 GA3ox s (Pattison et al., 2015 ). Several studies show that enzymes from these groups exhibit tissue-specific expression (Serrani et al., 2007 ; Chen et al., 2016 ). According to their spatial expression pattern ( http://bar.utoronto.ca/efp_tomato/cgi-bin/efpWeb.cgi ), GA20ox1 and GA20ox2 seems to be the best candidates for the generation of drought-resistant plants with no, or a weak effect on yield. Indeed, ga20ox1 and ga20ox2 mutants exhibit a mild growth phenotype and reduced water loss under drought conditions (Shohat et al., 2021 ).

In conclusion, manipulations of the GA pathway in tomato can be exploited to improve drought resistance, as well as resistance to other abiotic and biotic stresses. Alongside resistance, these modifications may improve yield through their effect on plant architecture and harvest index. Further research will still be necessary to develop high-yield tomato plants with improved stress resistance using the GA pathway, and will be made possible using the recent advances in gene-editing technologies.

Availability of data and materials

All data presented in this review is included in this published manuscript.

Abbreviations

2-oxoglutarate-dependent dioxygenases

• Abscisic acid

ABA INSENSITIVE3

ABA-IMPORTING TRANSPORTER 1.1

Copalyl diphosphate synthase

Clustered regularly interspaced short palindromic repeats

• Gibberellin

GA 13-oxidase

GA 2-oxidase

GA 20-oxidase

GA 3-oxidase

GA METHYL TRANSFERASE1

Geranylgeranyl diphosphate

GIBBERELLIN INSENSITIVE DWARF 1

Kaurenoic acid oxidase

Kaurene oxidase

Kaurene synthase

LEAFY COTYLEDON

N-terminal extension

Reactive oxygen species

SEMIDWARF 1

SELF-PRUNING

SELF-PRUNING 5G

Transcription activator-like effector nucleases

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Shohat, H., Eliaz, N.I. & Weiss, D. Gibberellin in tomato: metabolism, signaling and role in drought responses. Mol Horticulture 1 , 15 (2021). https://doi.org/10.1186/s43897-021-00019-4

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Gibberellin 2-oxidase 1(CsGA2ox1) involved gibberellin biosynthesis regulates sprouting time in camellia sinensis

• Ziyuan Qiu 1 ,
• Wenhui Guo 1 ,
• Qian Yu 1 ,
• Dongxue Li 1 ,
• Mengjie Zhao 1 ,
• Xuewen Hua 1 ,
• Yu Wang 2 ,
• Qingping Ma 1 &
• Zhaotang Ding 3  

BMC Plant Biology volume  24 , Article number:  869 ( 2024 ) Cite this article

Metrics details

Tea is an important cash crop and buds are its main product. To elucidate the molecular mechanism of the sprouting time of tea plants, ‘Yuchunzao’, which was an early sprouting tea cultivar, was studied. ‘Echa 1’, sprout one week later than ‘Yuchunzao’ in spring, was used as the control.

A total of 26 hormonal compounds and its derivatives in tea plants were qualified by using Ultra Performance Liquid Chromatography-Tandem mass spectrometry (UPLC-MS/MS). The result showed that GA 20 , GA 3 and ICA were significantly different in ‘Yuchunzao’ than in ‘Echa 1’, with GA 20 and GA 3 up-regulated and ICA down-regulated. Based on the Illumina platform, transcriptome analysis revealed a total of 5,395 differentially expressed genes (DEGs). A diterpenoid biosynthesis related gene, gibberellin 2-oxidase 1 ( CsGA2ox1 ), was downregulated in ‘Yuchunzao’ compared to ‘Echa 1’. CsGA2ox1 regulate the transformation of GA different forms in plants. The relative expression of CsGA2ox1 showed an adverse trend with the content of GA 20 and GA 3 . Our results suggest that down regulation of CsGA2ox1 resulted in the accumulation of GA 3 and GA 20 , and then promoted sprout of ‘Yuchunzao’.

This study provides theoretical basis of tea plants sprout and guides the tea breeding in practice.

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Introduction

Tea plant [ Camellia sinensis (L.) O. Kuntze] is an important economic crop in China. New shoots of tea plants are the source of tea, which is one of the most popular drinks. The sprouting time of tea plants in spring determined the harvest season. However, even under the same cultivation conditions, tea varieties that germinate early show significant difference in sprouting time from those that germinate late [ 1 ]. Tea varieties that germinate early represent a long harvest period and high economic value [ 2 , 3 , 4 ]. Tea buds harvested in early spring have a better flavor and thus a high price [ 5 ]. In addition, because of the low temperatures in early spring, tea harvested at this time is less threatened by pests and diseases and is of better quality [ 6 ]. The price of tea produced in spring is usually higher than that in summer and autumn [ 3 , 6 ]. Thus, the sprouting time of tea plants affected the economic income largely, so tea cultivars with early sprouting time in spring were desired.

Under prolonged cold stress in winter, tea buds are in dormancy [ 7 ]. Sprouting time is related to the time when the tea plant ends its dormancy. The sprout process is complex and influenced by many factors, photoperiod and temperature are environmental factors affecting winter dormancy in tea plants [ 8 ]. While, hormone levels, enzyme activity and carbohydrate levels are internal factors affecting the release of dormancy of tea buds [ 9 ], hormone levels are the key signaling regulators [ 1 ]. However, the regulation of plant growth and development by hormones is extremely complex, with multiple hormones interacting with each other. Previous studies have reported that some phytohormones could affect the sprouting of tea plants in spring, such as gibberellin (GA), cytokinin (CK), abscisic acid (ABA) and auxin [ 10 , 11 ]. Of these, ABA could induce shoot dormancy, but GA, CK and auxin could break shoot dormancy of tea plants [ 11 ]. In a previous study, the expressions of several auxin transport related genes were consistent with the indole acetic acid (IAA) content changes and the active-dormant status transition in tea buds [ 8 ]. ABA levels and ABA/IAA ratio decreased while IAA levels increased in tea buds from dormancy to sprout stage [ 12 ], suggesting that the catabolic release of ABA as well as the accumulation of IAA promotes bud dormancy release. Tea bud sprouting was related to the ratio of hormones such as zeatin/ABA rather than the absolute amount of a particular hormone [ 13 ], and zeatin is one type of CK. In a previous study, zeatin, GA and IAA levels were significantly higher in the tea tree sprouting stage than in the dormant stage [ 1 ], indicating that these hormones have a positive effect on bud sprouting. In addition, exogenous application with the combination of GA and CK could also break dormancy early in tea shoots [ 14 ]. In plants, there are many GA types, and they have different activities and functions [ 15 , 16 , 17 ]. It is still unclear that which GA type contributes to the sprouting of tea plants. Although many studies have been conducted on dormancy and release of tea buds, the mechanism of bud sprouting is not yet known in tea plants.

In this study, an early sprouting tea cultivar ‘Yuchunzao’ and the control tea cultivar ‘Echa 1’ were used to interpret the sprouting mechanism of tea plants. Under the same conditions, ‘Yuchunzao’ sprouted approximately one week earlier than ‘Echa 1’. The content of endogenous hormonal compounds in the shoots of both varieties was examined by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis. Meanwhile, the transcriptome sequencing analysis was carried out to find the differentially expressed genes related to sprouting of tea plants. The contents of endogenous hormonal compounds and the gene expressions of differentially expressed genes was compared to reveal the molecular mechanism of the early sprout of ‘Yuchunzao’. This study will provide a theoretical basis for regulating the sprouting time of tea plants.

Materials and methods

Plant materials.

Two tea cultivars ‘Echa 1’ and ‘Yuchunzao’ were used as materials, and ‘Echa 1’ was used as the control. One year old plants of both tea cultivars were cultivated in the greenhouse (16 h light) with 25 ± 5 ℃ and 70% humidity. The apical shoots with one bud and two leaves for ‘Yuchunzao’ and the bud of ‘Echa 1’ at the same time on April 8, 2021 were picked and frozen in liquid nitrogen. These samples were stored at -80 ℃ for further transcriptome analysis and hormone detection. Three biological replicates of each cultivar were conducted. A total of ten buds were harvested for each biological replicate.

Extraction and detection of hormonal compounds

The samples were grind to powder with 30 Hz for 1 min. A total of 50 mg powder was extracted with methanol: water: formic acid (15:4:1 v/v). The concentrated extracts were re-dissolved in 100 µL of 80% methanol solution, and then filtered through a 0.22 μm PTFE membrane. Two microliter liquid was injected in an LC-ESI-MS/MS system (HPLC, Shim-pack UFLC SHIMADZU CBM30A system; MS, Applied Biosystems 6500 Triple Quadrupole). Waters ACQUITY UPLC HSS T3 C18 column (1.8 μm, 2.1 mm ×100 mm) was used for isolation of hormones. Mobile phase A was pure water and mobile phase B was acetonitrile with 0.05% formic acid. The gradients of the mobile phase were as follows: 95% A in 0 min and maintained for 1 min, down to 5% A in 8 min and maintained for 1 min, increased to 95% A immediately and maintained for 3 min. The temperature was performed at 40 o C and the flow rate was set at 0.35 mL/min. The effluent was alternately connected to the ESI-triple quadrupole-linear ion trap (QTRAP)-MS. The AB 6500 QTRAP LC/MS/MS system is equipped with an electrospray ionization (ESI) Turbo Ion Spray interface controlled by Analyst 1.6 software (AB Sciex). The ESI was used with gas temperature of 500 °C, the mass spectrometry voltage of 4500 V, and curtain gas flow rate of 35 psi. The collision-activated dissociation parameter is set to medium. Peak area was recorded for quantitative analysis.

Qualitative and quantitative analysis of hormonal compounds

A total of 26 hormonal compounds were detected in tea buds. All of the standards were purchased from Olchemim Ltd. (Olomouc, Czech Republic) and Sigma (St. Louis, MO, USA). Standards diluted at 0.01 ng/ml, 0.05 ng/ml, 0.1 ng/ml, 0.5 ng/ml, 1 ng/ml, 5 ng/ml, 10 ng/ml, 50 ng/ml, 100 ng/ml, 200 ng/ml, and 500 ng/ml were analyzed. Standards were dissolved and diluted using acetonitrile. The standard curve and regression equation were established with the concentration of the standards as the horizontal coordinate and the peak area as the vertical coordinate (Supplementary Table 1 ). The content of hormonal compounds in tea shoots was calculated according to the regression equation.

RNA extraction, complementary DNA (cDNA) library construction and high-throughput sequencing

Total RNA was extracted from tea leaves according to the instructions of Plant Quick RNA Isolation Kit (Huayueyang Biotech, Beijing, China). The concentration and purity of RNA was determined using a NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE). The integrity of RNA was evaluated using an Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). The cDNA library was constructed according to the spcification of the NEBNext Ultra™ RNA Library Preparation Kit for Illumina (NEB, USA). An amount of 1 µg RNA was used to construct the cDNA library. The processes were as follows: the mRNA was purified in magnetic beads with Oligo (dT) and then randomly interrupted with fragmentation buffer. The first strand cDNA was synthesized using random hexamer primer, and then RNase H and DNA polymerase I were added. End-repaired, A-tailed and sequencing ligated were performed after cDNA purification using AMPure XP beads. AMPure XP system (Beckman Coulter, Beverly, United States) was used to purify library fragments for preferential selection of cDNA fragments with a length of 240 bp. The PCR products were amplified and purified, and the quality of the libraries was assessed using an Agilent Bioanalyzer 2,100. Clusters were generated using the TruSeq PE Cluster Kit version 4-cBot-HS (Illumina, USA). The library was paired-end sequenced on an Illumina 2,500 sequencer to obtain raw reads.

Sequence quality assessment and identification of differentially expressed genes

Adapter-containing readings, ploy-N-containing readings, and low-quality readings were removed from the raw data to obtain clean reads. Q30 was used to measure the clean reads quality. The clean reads were mapped to the tea reference genome ( http://tpia.teaplant.org/ ) via the HISAT2 ( http://ccb.jhu.edu/software/hisat2/index.shtml ) software [ 18 ]. The gene expression levels were assessed using fragments per kilobase of transcript per million fragments mapped (FPKM). Genes with fold change ≥ 2 and false discovery rate (FDR) < 0.01 were categorised as differentially expressed genes by DESeq2 software [ 19 ]. Genes were functionally annotated based on the following databases: NCBI non-redundant protein sequences (Nr; ftp://ncbi.nih.gov/blast/db/ ), Swiss-Prot ( http://www.uniprot.org/ ), Gene ontology (GO; http://www.geneontology.org/ ), Clusters of Orthologous Groups of proteins (COG; http://www.ncbi.nlm.nih.gov/COG/ ), protein family (Pfam; http://pfam.xfam.org/ ), and Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/ ).

Sequence alignment and phylogenetic Tree Construction

To understand the structure of gibberellin 2-oxidase ( GA2ox ), the protein sequences of GA2ox from tea plant and 10 other different plants were compared to each other using BLAST ( http://www.ncbi.nlm.nih.gov/BLAST ) with default parameters. GA2ox putative proteins from tea plant and 29 other species were used to construct a phylogenetic tree using the neighbour-joining method via Mega X with 500 bootstrap replications [ 20 ]. The motifs were identified using the MEME ( http://meme-suite.org/tools/meme ) website.

Quantitative real-time PCR analysis

Quantitative real-time PCR (qRT-PCR) was performed on the Bio-Rad CFX96 system to verify the accuracy of the transcriptomic data. And 8 different genes were selected randomly to validate the expression levels. Primers were designed by AlleleID 6.0 software (Supplementary Table 2 ). The CsGAPDH was used as a reference gene. The procedure was as follows: 95 °C for 30 s; 95 °C for 5 s; 60 °C for 30 s for a total of 40 cycles. 0.8 µL primer (10 µM), 50 ng cDNA and 12.5 µL 2X SYBR Green Fast qPCR Mix (Biomarkers, China) were included in the total volume of the 25 µL reaction volume. The 2 −ΔΔCt method was used for the relative expression of genes [ 21 ].

Statistical analysis

The SPSS 23.0 ( https://www.ibm.com/support/pages/spss-statistics-230-fix-pack-3 ) and Microsoft Excel 2016 were used for statistical analysis. Differences between groups were evaluated using t test and P  < 0.05 was considered to be significantly different.

Quantitative analysis of hormonal compounds

In tea plants, ABA accounted for 1.03–1.57 µg/g, followed by 1-Aminocyclopropanecarboxylic acid (ACC) of 159–210 ng/g and salicylic acid (SA) of 108–166 ng/g. Among the GAs, GA 20 was present at the highest level of 8–21 ng/g; GA 1 , GA 4 , GA 7 , GA 9 , GA 19 , GA 24 , GA 15 and GA 53 were not detected in tea plants. For auxins, IAA showed the highest level of 28–43 ng/g, but 3-Indolebutyric acid (IBA) was not detected. For CK, trans-Zeatin (tZ) showed the highest content of 0.35–0.64 ng/g, but cis-Zeatin (cZ) and Dihydrozeatin (DZ) were not detected. In addition, jasmonic acid (JA) accounted for 20–106 ng/g in tea plants (Fig.  1 ).

In comparison, only the hormonal compounds ACC, SA, GA 3 and GA 20 were higher in ‘Yuchunzao’ compared to ‘Echa 1’. All other hormonal compounds were lower in ‘Yuchunzao’ compared to ‘Echa 1’. Among them, GA 3 , GA 20 and Indole-3-carboxylic acid (ICA) levels were significantly different between two tea varieties. Moreover, the ratio of GA/ABA was higher in ‘Yuchunzao’.

Phenotypes of ‘Yuchunzao’ (left) and ‘Echa 1’ (right) and the content of selected endogenous hormone compounds in ‘Yuchunzao’ and ‘Echa 1’. IAA: Indole-3-acetic acid, ME_IAA: Methyl indole-3-acetate, ICAld: Indole-3-carboxaldehyde, ICA: Indole-3-carboxylic acid, ACC: 1-Aminocyclopropanecarboxylic acid, IP: N6-Isopentenyladenine, tZ: trans-Zeatin, MEJA: Methyl jasmonate, JA: Jasmonic acid, JA_ILE: Jasmonoyl-L-Isoleucine, SA: Salicylic acid, ABA: Abscisic acid, GA 3 : Gibberellin A 3 , GA 20 : Gibberellin A 20 . The * indicates significant difference, ns indicates non-significant difference

Quality assessment of transcriptomic raw data

A total of 42.94 Gb of clean data was obtained after removing the reads containing adaptors and low-quality sequences (NCBI SRA accession: PRJNA1005819). Clean data reached 6.42Gb for each sample. The GC percentage was over 45.03% for all samples in clean data. The Q30 for all samples was more than 94.15%, which represents high quality. Over 87.10% the clean reads were mapped to the tea genome, with 74.73–75.15% unique mapped readings (Table  1 ). In conclusion, these data indicate that the quality of sequences is reliable and can be used for further analysis.

Identification and functional annotation of differential expressed genes

A total of 5,395 DEGs were identified between the buds of ‘Yuchunzao’ and ‘Echa 1’, including 2,950 down-regulated genes and 2,445 up-regulated genes. Functional annotation analysis revealed 1,815, 3,227, 1,972, 3,762 and 4,828 DEGs in the COG, GO, KEGG, Swiss-Prot and NR databases, respectively. A total of 8 DEGs (CSS0017652, CSS0050504, CSS0039293, CSS0011049, CSS0030210, CSS0017383, CSS0023205 and CSS0037997) were randomly selected for qRT-PCR analysis in order to verify the reliability of DEGs RNA-seq data. The results showed that expression of most of DEGs showed consistency between RNA-seq analysis and qRT-PCR verification. RNA-seq analysis was proved to be reliable (Fig.  2 ).

Quantitative real-time (qRT-PCR) verification for randomly selected differentially expressed genes (DEGs). Fold change of FPKM represents RNA-seq data. 2 –ΔΔCt represents qRT-PCR data. The * indicates significant difference, ns indicates non-significant difference

Based on KEGG analysis, Metabolism related DEGs were mostly enriched, especially for amino acid biosynthesis, carbon metabolism, starch and sucrose metabolism associated DEGs. For Plant hormone signal transduction, a total of 40 DEGs were identified (Fig.  3 ). Of them, only one GA synthesis related gene was identified, which was gibberellin 2-oxidase 1 ( CsGA2ox1 , CSS0002801). It showed lower expression in ‘Yuchunzao’ than in ‘Echa 1’ (Log2FC -3.42).

Enrichment of DEGs in different KEGG pathways

In the COG functional classification, DEGs were divided into 26 clusters, and CsGA2ox1 was annotated in “Secondary metabolites biosynthesis, transport and catabolism” class (Supplementary Fig.  1 A). In GO classification analysis, CsGA2ox1 was simultaneously annotated in iron ion binding, GA catabolic process and oxidation-reduction process (Supplementary Fig.  1 B).

Participation of the CsGA2ox1 gene as a component of the GA synthesis in the diterpenoid biosynthesis pathway

In the present study, the CsGA2ox1 was found to be down-regulated in buds of ‘Yuchunzao’, compared to ‘Echa 1’. The predicted CsGA2ox1 protein contained the specific structural domain 2OG-FeII_Oxy which was conserved in the 2OG-FeII_Oxy superfamily (Fig.  4 A). CsGA2ox1 was found to be have three conserved motifs, and location of these motifs were consist with 2OG-FeII_Oxy domain (Fig.  4 B). GA2ox catalyzes bioactive GA and direct precursors of GA to be inactive GA [ 22 ]. CsGA2ox1 enzymes catalyze the formation of GA 8 , GA 34 , GA 51 and GA 29 from GA 1 , GA 4 , GA 9 and GA 20 , respectively. In the present study, GA 3 and GA 20 were accumulated but the expression of CsGA2ox1 was down regulated in ‘Yuchunzao’ (Fig.  4 C). In addition, phylogenetic tree showed that CsGA2ox1 was more closely related to the orthologs from Coffea arabica , Datura stramonium , Quercus suber , Quercus robur and Actinidia chinensis var. chinensis (Supplementary Fig.  2 ).

Protein structure analysis of GA2ox. ( A ) Conserved structure of CsGA2ox1. ( B ) Modal analysis of GA2ox. Camellia sinensis (CsGA2ox1), Actinidia chinensis var. chinensis (AcGA2ox), Diospyros kaki (DkGA2ox2), Nerium oleander (NoGA2ox2), Coffea arabica (CaGA2ox), Olea europaea subsp. Europaea (OeGA2ox), Salix suchowensis (SsGAox), Populus alba (PaGA2ox), Paeonia suffruticosa (PsGA2ox), Jasminum sambac (JsGA2ox), Sesamum indicum (SiGA2ox). ( C ) Involvement of CsGA2ox1 in GA synthesis in the diterpenoid synthesis pathway. Green indicates down-regulated genes. Red indicates up-regulated metabolites

In this study, transcriptome analysis and hormonal compounds levels of the early sprouting tea cultivar ‘Yuchunzao’ and the control cultivar ‘Echa 1’ were performed to identify the key factor regulating sprouting time of tea plants in spring. Quantitative analysis of hormonal compounds showed that ICA was significantly lower in ‘Yuchunzao’, and GA 3 and GA 20 were significantly higher in ‘Yuchunzao’. Transcriptome analysis indicated a diterpenoid biosynthesis related gene CsGA2ox1 , which was involved in GA metabolism. It was downregulated in ‘Yuchunzao’ and showed reverse trend with the content of GA 20 and GA 3 .

The content of major hormonal compounds in the new shoots varies in plants. In Castanea mollisima , the dominant hormonal compounds were JA-ILE, SA and JA [ 23 ]. In blueberry flower buds, the major hormonal compounds were JA, ABA and ACC [ 24 ]. In Phalaenopsis , ABA, IAA and SA accounted for the highest levels [ 25 ]. In tea buds, the major endogenous hormonal compounds were SA, JA, ACC and ABA. This result was similar to the previous studies [ 26 , 27 ]. However, the most significant hormonal compounds such as ABA, ACC and SA were not significantly different between ‘Yuchunzao’ and ‘Echa 1’. Notably, ABA levels were usually considered to be negatively correlated with bud sprouting, and ABA level of ‘Yuchunzao’ was lower than that in ‘Echa 1’ in this study, which may be interpret the reason of early sprouting of ‘Yuchunzao’ to some extent. The mechanism of ABA regulating sprouting needs to be further determined. It is certain that the increase in the ratio of GA/ABA could promote the germination of cucumber and soybean seeds, and vice versa [ 28 , 29 ]. In this study, the ratio of GA/ABA was higher during the tea buds of ‘Yuchunzao’ (Fig.  1 ), while ABA levels did not differ significantly between the two varieties, so the increase of the GA/ABA ratio was mainly attributed to the rise in GA rather than the fall in ABA. We hypothesised that GA is more closely involved in regulating sprouting than ABA. In addition, although the content of GA 20 and GA 3 was significantly lower than the major hormonal compounds in tea shoots, they were different significantly between two cultivars. Thus, we suggested that GA 20 and GA 3 might be the major hormonal compounds contributing to the sprouting of tea plants.

GA is a class of diterpenoid phytohormones that are associated with plant growth and development [ 22 ]. Furthermore, GA has been pointed out as an important factor in the release of dormancy of plant and promoting growth of shoots after the release of dormancy [ 30 ]. The low temperature was required for dormant release, and the GA partially replaced the need for low temperature resulting in the promotion of sprouting [ 31 ]. GA has more than 100 types, only GA 1 , GA 3 , GA 4 , and GA 7 were biologically active [ 30 ]. GA 3 is the most active component of the sprout-promoting GAs [ 32 , 33 ]. In addition, exogenous GA 3 could accelerate tea bud sprout and the growth of tea plant [ 34 , 35 ]. Bioactive GA 3 is synthesized from GA 20 , and GA 3 level may increase by elevated GA 20 (Fig.  4 C). GA 20 content showed significant positive correlation with plant height, petiole length, and leaf development indicators such as leaf length width and area [ 36 ]. The level of GA 20 in tea buds was about four times higher after dormant release than at mid-dormancy [ 37 ], suggesting that GA 20 is highly correlated with tea bud release. In this study, the content of both GA 20 and GA 3 were higher in ‘Yuchunzao’ than in ‘Echa 1’, which indicating that GA 20 and GA 3 play important roles in promoting geminating of tea shoots.

CsGA2ox1 is an enzyme involved in GA metabolism, it can catalyze GA 1,4,9,20 to GA 8,34,51,29 , respectively [ 38 ]. GA 20 is also the precursor of bioactive GA 3 . Therefore, there is a substrate competition between GA 3 and GA 8,34,51,29 (Fig.  4 C). In this study, CsGA2ox1 showed lower expression in ‘Yuchunzao’ than in ‘Echa 1’, the GA 20 and GA 3 were accumulated in ‘Yuchunzao’, which indicating that the down regulation of CsGA2ox1 induced the accumulation of GA 20 and GA 3 . GA2ox catabolism of GA is a key mechanism for maintaining bud dormancy [ 39 , 40 ]. Low expression of GA2ox could increase rice and pear seed germination, and vice versa [ 41 , 42 ]. In addition, expression of GA2ox inhibits the early bud break phenotype in SVLRNAi transgenic hybrid aspen plants [ 43 ]. In the present study, the CsGA2ox1 gene was found to be down-regulated in ‘Yuchunzao’. We could suggest that low expression of CsGA2ox1 resulted in high levels of GA 20 , which led to early sprout phenotypes in ‘Yuchunzao’. Except for GA, one of auxin ICA was significantly lower in ‘Yuchunzao’. ICA has been proved to promote plant growth [ 44 , 45 ]. However, auxin is not the direct trigger for bud release, it may induce GA synthesis to promote sprouting and sustained bud growth [ 46 ]. And in this study, ICA levels were significantly different between two varieties, but their absolute contents were too low to be detected. Thus, the relationship between ICA level and sprouting of tea plants need further verification.

In addition, in KEGG metabolism-related pathways, DEGs are enriched for amino acid biosynthesis, carbon metabolism, and starch and sucrose metabolism. Since ‘Yuchunzao’ germinated earlier than ‘Echa 1’, the tenderness of the buds sampled at the same time was different, leading to differences in the intrinsic quality components of the two varieties. Sugars were stored in the buds to replenish energy during bud growth and development, and the pathways of sugar metabolism in the buds were constantly changing to meet the different energy requirements of the buds at various stages of growth [ 1 ]. Furthermore, plant hormones may also cause metabolite differences. Phytohormones and sugar crosstalk affect bud sprout and growth [ 1 , 31 ]. Therefore, further research is needed to verify their relationship with sprouting.

In conclusion, GA 20 and GA 3 were accumulated in ‘Yuchunzao’, which showed reverse trend with the expression of GA metabolism related gene CsGA2ox1 . It suggested that low expression of CsGA2ox1 led to the accumulation of its substrate GA 20 and GA 3 , which causes early tea bud sprouting. However, the direct relationship between CsGA2ox1 and GA in tea remains to be investigated. This study provides theoretical basis of tea plants sprout and guides the tea breeding in practice.

Data availability

All transcriptomic original sequencing data associated with this study have been submitted to the NCBI SRA under the accession number PRJNA1005819.

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This work was supported by Natural Science Fund of Shandong Province (ZR2021QC159), National Natural Science Foundation of China (32302607), Youth innovation team project of Shandong Province (2023KJ208), the Open Project of Liaocheng University Landscape Architecture Discipline (319462212) and Innovation Training Program for College Students (CXCY2023253).

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Ziyuan Qiu, Wenhui Guo, Qian Yu, Dongxue Li, Mengjie Zhao, Han Lv, Xuewen Hua & Qingping Ma

College of Horticulture, Qingdao Agricultural University, Qingdao, 266109, China

Tea Research Institute, Shandong Academy of Agricultural Sciences, Jinan, 250100, China

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Ziyuan Qiu prepared samples for analysis, determined and analyzed the data, interpreted the results, and wrote the original draft paper. Wenhui Guo and Qian Yu determined and analyzed the data and interpreted the results. Mengjie Zhao, Han Lv, and Xuewen Hua measured supplementary experimental data. Yu Wang collected samples and assisted. Qingping Ma and Zhaotang Ding designed the study, analyzed the data, interpreted the results, and revised the manuscript. Dongxue Li made revisions to the first draft of the article. All authors reviewed the manuscript.

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Qiu, Z., Guo, W., Yu, Q. et al. Gibberellin 2-oxidase 1(CsGA2ox1) involved gibberellin biosynthesis regulates sprouting time in camellia sinensis . BMC Plant Biol 24 , 869 (2024). https://doi.org/10.1186/s12870-024-05589-1

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Osmbf1a facilitates seed germination by regulating biosynthesis of gibberellic acid and abscisic acid in rice.

1. Introduction

2.1. osmbf1a is ubiquitously expressed in rice and is induced during seed germination, 2.2. osmbf1a positively regulates seed germination in rice, 2.3. osmbf1a modulates terpenoid-related metabolic pathways, 2.4. osmbf1a regulated endogenous aba and ga levels in rice seed, 2.5. overexpressing zmmbf1a and zmmbf1b in rice enhances seed germination, 2.6. zmmbf1a and zmmbf1b overexpression modulates ga and aba in rice, 3. discussion, 4. materials and methods, 4.1. construction and planting materials, 4.2. phenotypic analysis of seed germination, 4.3. rna extraction and rt-qpcr, 4.4. rna-seq analyses, 4.5. dap-qpcr analyses, 4.6. detection of ga3 and aba content, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Wang, X.; Chen, Z.; Guo, J.; Han, X.; Ji, X.; Ke, M.; Yu, F.; Yang, P. OsMBF1a Facilitates Seed Germination by Regulating Biosynthesis of Gibberellic Acid and Abscisic Acid in Rice. Int. J. Mol. Sci. 2024 , 25 , 9762. https://doi.org/10.3390/ijms25189762

Wang X, Chen Z, Guo J, Han X, Ji X, Ke M, Yu F, Yang P. OsMBF1a Facilitates Seed Germination by Regulating Biosynthesis of Gibberellic Acid and Abscisic Acid in Rice. International Journal of Molecular Sciences . 2024; 25(18):9762. https://doi.org/10.3390/ijms25189762

Wang, Xin, Ziyun Chen, Jinghua Guo, Xiao Han, Xujian Ji, Meicheng Ke, Feng Yu, and Pingfang Yang. 2024. " OsMBF1a Facilitates Seed Germination by Regulating Biosynthesis of Gibberellic Acid and Abscisic Acid in Rice" International Journal of Molecular Sciences 25, no. 18: 9762. https://doi.org/10.3390/ijms25189762

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Article Contents

Introduction, materials and methods, supplementary data, acknowledgements, author contributions, conflict of interest, data availability.

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A transcriptional hub integrating gibberellin–brassinosteroid signals to promote seed germination in Arabidopsis

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Chunmei Zhong, Barunava Patra, Yi Tang, Xukun Li, Ling Yuan, Xiaojing Wang, A transcriptional hub integrating gibberellin–brassinosteroid signals to promote seed germination in Arabidopsis, Journal of Experimental Botany , Volume 72, Issue 13, 22 June 2021, Pages 4708–4720, https://doi.org/10.1093/jxb/erab192

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Seed germination is regulated by multiple phytohormones, including gibberellins (GAs) and brassinosteroids (BRs); however, the molecular mechanism underlying GA and BR co-induced seed germination is not well elucidated. We demonstrated that BRs induce seed germination through promoting testa and endosperm rupture in Arabidopsis. BRs promote cell elongation, rather than cell division, at the hypocotyl–radicle transition region of the embryonic axis during endosperm rupture. Two key basic helix–loop–helix transcription factors in the BR signaling pathway, HBI1 and BEE2, are involved in the regulation of endosperm rupture. Expression of HBI1 and BEE2 was induced in response to BR and GA treatment. In addition, HBI1 - or BEE2 -overexpressing Arabidopsis plants are less sensitive to the BR biosynthesis inhibitor, brassinazole, and the GA biosynthesis inhibitor, paclobutrazol. HBI1 and BEE2 promote endosperm rupture and seed germination by directly regulating the GA-Stimulated Arabidopsis 6 ( GASA6 ) gene. Expression of GASA6 was altered in Arabidopsis overexpressing HBI1 , BEE2 , or SRDX-repressor forms of the two transcription factors. In addition, HBI1 interacts with BEE2 to synergistically activate GASA6 expression. Our findings define a new role for GASA6 in GA and BR signaling and reveal a regulatory module that controls GA and BR co-induced seed germination in Arabidopsis.

In plants, the freshly formed seeds maintain dormancy until the proper time of germination. Seed germination is a critical process in the plant life cycle and relies on networks of interconnected signal transduction pathways that integrate multiple hormonal and environmental signals ( Bewley, 1997 ; Koornneef et al. , 2002 ; Bentsink and Koornneef, 2008 ; Seo et al. , 2009 ; Shu et al. , 2016 ; Topham et al. , 2017 ). Gibberellins (GAs) and brassinosteroids (BRs) promote seed germination, while abscisic acid (ABA) represses it ( Finch-Savage and Leubner-Metzger, 2006 ; Bentsink and Koornneef, 2008 ; Weitbrecht et al. , 2011 ; Gallego-Bartolome et al ., 2012 ; Tuan et al. , 2018 ; Kim et al. , 2019 ). A high GA/BR and low ABA level is a favorable condition for seed germination.

Multiple ABA-responsive transcription factors (TFs), including ABSCISIC ACID INSENSITIVE5 (ABI5), play key roles in inhibition of seed germination ( Finkelstein and Lynch, 2000 ; Carles et al. , 2002 ; Lopez-Molina et al. , 2002 ; Skubacz et al. , 2016 ). ABI5 binds to the ABA-responsive element (ABRE) in the promoters of the genes encoding late embryogenesis abundant (LEA) proteins, such as EARLY METHIONINE-LABELED 1 ( EM1 ) and EM6 , to repress their expression ( Carles et al. , 2002 ). ABI5 also plays roles in integrating external signals and the crosstalk between several growth hormones, including GA and BR ( Skubacz et al. , 2016 ).

GA promotes seed germination by directly inducing the expression of the genes involved in cell division and elongation or derepression of gene expression by degrading DELLA proteins, negative regulators of GA signaling. Degradation of DELLA proteins, particularly RGL2, also reduces ABA biosynthesis and promotes seed germination ( Piskurewicz et al. , 2008 ). The antagonistic interaction between GA and ABA in controlling seed germination has been extensively studied ( Bewley, 1997 ; Olszewski et al. , 2002 ; Finch-Savage and Leubner-Metzger, 2006 ; Piskurewicz et al. , 2008 ; Weitbrecht et al. , 2011 ; Liu et al. , 2016 ; Liu and Hou, 2018 ).

BR promotes seed germination by controlling the inhibitory effect of ABA on seed germination ( Hu and Yu, 2014 ; Zhao et al. , 2019 ). Extensive physiological, biochemical, and genetic studies, mainly using Arabidopsis, have led to the identification and functional characterization of the components of BR signal transduction ( Li et al. , 2001 , 2002 ; Nam and Li, 2002 ; Tang et al. , 2011 ). BR signaling begins with the perception of the hormone ligand by the plasma membrane-associated receptor complex consisting of BRASSINOSTEROID-INSENSITIVE1 (BRI1) and BRI-ASSOCIATED KINASE1 (BAK1). The activated BRI1–BAK1 receptor complex phosphorylates BR-SIGNALING KINASE 1 (BSK1) and CONSTITUTIVE DIFFERENTIAL GROWTH 1 (CDG1), which further phosphorylates the PP1 type phosphatase BRI1 SUPPRESSOR 1 (BSU1). BSU1, along with PROTEIN PHOSPHATSE 2A (PP2A), dephosphorylates and inactivates the glycogen synthase kinase3-like kinase BRASSINOSTEROID INSENSITIVE2 (BIN2). Inactivation of BIN2 promotes the accumulation of positive regulators of BR signaling, BRASINAZONE-RESISTANT 1 (BZR1) and BRI1-EMS-SUPPRESSOR 1 (BES1), which directly control the transcription of BR-responsive genes to regulate plant developmental events ( Li et al. , 2001 ; Kim et al. , 2011 ; Planas-Riverola et al. , 2019 ). Overexpression of BZR1 diminishes the inhibitory effect of ABA in transgenic Arabidopsis plants ( Tsugama et al. , 2013 ). In the absence of BR, BIN2 phosphorylates BZR1 and BES1 to repress their DNA binding capacity ( He et al. , 2002 ; Wang et al. , 2002 ; Yin et al. , 2002 ; Ryu et al. , 2007 ). BES1 physically interacts with ABI5 to hinder its DNA binding capacity, attenuating the ABA-mediated suppression of seed germination by lowering the expression of ABI5 targets ( Zhao et al. , 2019 ). BIN2 is a repressor of BR signal, but it promotes the ABA responses. During seed germination, BIN2 physically interacts with ABI5 to phosphorylate and stabilize AB15 in the presence of ABA. BIN2 and ABI5 mutually modulate the ABA-induced inhibition of seed germination. However, BRs antagonize the BIN2–ABI5 cascade and promote seed germination ( Hu and Yu, 2014 ), indicating a complex hormonal crosstalk during seed germination.

Both BR and GA promote cell expansion and seed germination. The physical interaction of DELLA and BZR1 seems to be the molecular basis for the BR–GA crosstalk (Gallego-Bartolome et al ., 2012; Ross and Quittenden, 2016 ; Ross et al. , 2016 ). BR can rescue the germination phenotypes of the GA biosynthetic mutant, ga1-3, and the GA-insensitive mutant, sleepy1 ( Steber and McCourt, 2001 ), suggesting that BR-induced seed germination does not totally depend on GA response, but rather the hormones working in parallel. Seeds of both the BR biosynthetic mutant det2-1 and the BR-insensitive mutant bril1-1 are able to germinate without BR and are hypersensitive to ABA. In rice, seed germination and seedling growth are significantly affected by the BR biosynthetic inhibitor brassinazole (BRZ) which is completely recovered by treatment with GA ( Li et al. , 2020 ). These observations indicate that BRs play an auxiliary role in the GA-promoted regulation of seed germination and can reverse the inhibitory effect of ABA ( Steber and McCourt, 2001 ). A recent study using iTRAQ (isobaric tag for relative and absolute quantification) proteomic analysis has revealed that GAs and BRs coordinately regulate rice seed germination and embryo development by modulating the expression of several common targets ( Li et al. , 2018 ). However, the molecular mechanisms underlying GA- and BR-induced seed germination have not been thoroughly investigated.

The interacting transcriptional module, DELLA/BZR1/PHYTOCHROME INTERACTING FACTOR4 (PIF4), integrates GA, BR, and light signals to mediate cell elongation ( Bai et al. , 2012b ; Li et al. , 2012 ; Oh et al. , 2012 ). Under low GA conditions, DELLA interacts with BZR1 and PIF4 to inhibit their DNA binding activity, thus inhibiting cell growth and elongation. The promotion of cell elongation by BZR1–PIF4 requires a tripartite helix–loop–helix/basic helix–loop–helix (HLH/bHLH) module that consists of PACLOBUTRAZOL-RESISTANT (PRE), ILI1 BINDING bHLH PROTEIN1 (IBH1), and HOMOLOG OF BEE2 INTERACTING WITH IBH1 (HBI1) ( Bai et al. , 2012a ; Fan et al. , 2014 ; Zheng et al. , 2019 ). HBI1 is also a positive regulator of BR signaling and functionally redundant with another bHLH TF, BEE2 (BRASSINOSTEROID ENHANCED EXPRESSION2) ( Malinovsky et al. , 2014 ). Genetic evidence suggests that HBI1 plays a pivotal role in GA-induced cell elongation. A total of 177 direct targets of HBI1 have been identified by chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA sequencing (RNA-Seq), several of which encode cell wall-related proteins, such as expansins ( EXP2 ) and GA-stimulated Arabidopsis (GASA) family proteins ( GASA4 and GASA6 ) ( Rubinovich and Weiss, 2010 ; Bai et al. , 2012a ; Fan et al. , 2014 ; Yan et al. , 2014 ; Zhong et al. , 2015 ). In Arabidopsis, the GASA family is represented by 14 members, of which GASA4 and GASA6 are positive regulators of GA response ( Zhang and Wang, 2008 ; Rubinovich and Weiss, 2010 ; Zhong et al. , 2015 ). Our previous study suggests that GASA6 regulates seed germination by serving as an integrator for the GA, ABA, and glucose (Glc) signaling cascades ( Zhong et al. , 2015 ).

In this study, we demonstrate that, similarly to GA, BRs also promote seed germination by accelerating endosperm rupture through promoting cell elongation at the hypocotyl–radicle transition region. In addition, we provide genetic and molecular evidence that two GA- and BR-responsive bHLH TFs, HBI1 and BEE2, directly bind to E box elements in the GASA6 promoter to regulate its expression. We illustrate a mechanism in which a bHLH TF complex mediates GA/BR-induced seed germination through activation of GASA6.

Plant material and growth conditions

All mutant and transgenic lines were in the Arabidopsis thaliana accession Col-0. Seeds were surface-sterilized and sown on plates with half-strength basal Murashige and Skoog (MS) medium (Sigma-Aldrich, USA) containing 0.8% (w/v) agar (MBCHEM, China). Plants were grown in a climate-controlled room (22 °C, photoperiod of 16 h light/8 h dark, light intensity of ~100 µmol m −2 s −1 , and relative humidity of 70%). HBI1-OE (overexpressing) and BEE2-OE lines were kindly provided by Dr Cyril Zipfel (Sainsbury laboratory, Norwich, UK), and HBI1-SRDX and BEE2-SRDX lines were kindly provided by Dr Masaru Ohme-Takagi (Bioproduction research institute, Tsukuba, Japan). HBI1-OE/gasa6 and BEE2-OE/gasa6 were generated by a genetic cross between gasa6 (SALK_072904) and HBI1-OE or BEE2-OE , and homozygous lines were verified by PCR using the primers listed in Supplementary Table S1 .

Germination assay and hypocotyl length assay

For each germination assay, three independently grown seed batches of the wild type (WT), HBI1-OE , or BEE2-OE were compared. To ensure synchronous germination, seeds were imbibed at 4 °C for 3 d, then moved to a growth chamber with a 16 h/8 h light/dark cycle at 22 °C. The experiments were performed on half-strength MS medium supplemented with 1 µM 2,4-epibrassinolide (BR), 1 µM BRZ (Sigma-Aldrich, USA), 100 µM gibberellin (GA 3 ), 1 µM paclobutrazol (PAC) (Sigma-Aldrich, USA), or 100 µM ABA (Sigma-Aldrich, USA). At least 80 seeds were imbibed for each treatment and examined for testa and endosperm rupture under a SMZ1500 stereomicroscope (Nikon, Japan), and photographed with a high-resolution digital camera (COOLPIX4500, Nikon, Japan). Germination rate was determined by calculating the percentage of testa and endosperm rupture in the control and different treatments. In the hypocotyl length assay, seeds were incubated for 36 h to attain 100% germination because BR-treated seeds germinate faster than those of the WT. After germination, testas were stripped and 50–70 embryos were photographed with a BX51 camera (Olympus, Japan). Hypocotyl length was measured using the Image J software ( https://imagej.nih.gov/ij/index.html ). The SPSS software ( http://www.spss.com/ ) was used for statistical analysis throughout this study.

Measurement of embryonic axis epidermal cells

To ensure the synchronous and full germination of both untreated and treated seeds, we incubated the seeds for 36 h at room temperature before taking the measurements. Seeds were collected at 36 h and fixed in 50% (v/v) methanol and 10% (v/v) acetic acid overnight at 4 °C. Embryos were dissected from testas and stained as described previously ( Sliwinska et al. , 2009 ), and subsequently photographed with an LSM510 Meta confocal laser-scanning microscope (Zeiss, Germany). Photographs were enlarged electronically for measurement of cell length and width with Image J software.

Gene expression analysis

Quantitative real-time PCR (qRT-PCR) was performed as previously described ( Zhong et al. 2015 ). Briefly, total RNA was extracted from 2-week-old seedlings or seeds using the total RNA isolation Kit (Promega, USA) according to the manufacturer’s instruction. About 800 ng of total RNA for each sample was reverse transcribed using the PrimeScript RT Reagent Kit with gDNA Eraser (TAKARA, Japan). All PCRs were performed using SYBR Premix Ex Taq Mix (TAKARA, Japan) in triplicate and repeated at least three times. The transcript levels were measured by the comparative cycle threshold (Ct) method (bulletin no. 2; Applied Biosystems, http://www.appliedbiosystems.com ). Ubiquitin1 ( UBQ1 ) ( Jiang et al. , 2012 ) and Tubulin 3 ( TUB3 ) ( Patra et al. , 2013 ) were used as internal controls. Primers used for qRT-PCR are listed in Supplementary Table S1 . β-Glucuronidase (GUS) assay was performed as previously described ( Zhong et al. , 2015 ). Briefly, T 3 transgenic lines carrying different truncated GASA6 promoters fused with the GUS reporter gene were analyzed for GUS histochemical staining. Samples were incubated in the GUS staining solution [1 mg ml –1 5-bromo-4-chloro-3-indolyl glucuronide (X-Gluc) dissolved in 50 mM Na-phosphate buffer] at 37 °C overnight, then bleached using 70% (v/v) ethanol. All the samples were photographed under an Olympus BX Microscope (Olympus, Japan).

Yeast two-hybrid assay

The cDNA encoding either the full length or fragments of the desired proteins were fused to pGADT7 [activation domain (AD)] or pGBKT7 [DNA-binding domain (BD)]. The AD and BD fusion plasmids were paired in different combinations and co-transformed into Saccharomyces cerevisiae strain AH109 (Clontech, USA). Transformed colonies were then selected on synthetic dropout (SD) medium lacking leucine and tryptophan (–Leu –Trp). Interactions were determined by growth of the colonies on SD medium lacking histidine, leucine, and tryptophan (–His –Leu –Trp), and containing 5 mM (for HBI1) 3-amino-1,2,4-triazole (3-AT). Primers used for plasmid construction for yeast two-hybrid assay are listed in Supplementary Table S1 .

Bimolecular fluorescence complementation (BiFC) assay

Full-length HBI1 , BEE2 , or IBH1 cDNAs were cloned into the pSAT6-nYFPC1 or pSAT6-cYFPC1 vectors, which contained either the N- or the C-terminal half of yellow fluorescent protein (YFP). The resulting constructs were paired in different combinations and co-transformed into the A. thaliana mesophyll protoplasts as described previously ( Yoo et al. , 2007 ). The YFP signals were observed with an LSM510 Meta confocal laser-scanning microscope (Zeiss, Germany). Primers used for plasmid construction for the BiFC assay are listed in Supplementary Table S1 .

Protoplast transient assay

Different fragments of the GASA6 (1.4, 1.2, 1.1, or 0.9 kb) promoter were each cloned into the pGreen II 0800-LUC vector ( Hellens et al. , 2005 ) to generate reporter constructs. Full-length HBI1 , BEE2 , or IBH1 cDNAs were cloned into the pBlueScript vector with the Cauliflower mosaic virus ( CaMV ) 35S promoter and rbcS terminator to generate effector constructs. Each reporter construct, together with either 35S::HBI1 , 35S::BEE2 , or 35S::IBH1 , was co-transformed into the mesophyll protoplasts of A. thaliana for transcriptional activity assay.

Single or double mutants of the GASA6 (1.4 kb) promoter were generated with the MutanBEST Kit (TAKARA, Japan) and subsequently cloned into the pGreen II 0800- LUC vector. Firefly and Renilla luciferase activities were assayed with the microplate luminometer (Turner Biosystems, USA) and the Dual-Luciferase Reporter Assay reagents (Promega, USA). Primers used for plasmid construction for protoplast assay are listed in Supplementary Table S1 .

ChIP-PCR assay

ChIP assays were performed as previously described ( Hou et al. , 2014 ). Briefly, 5-day-old seedlings of 35S::HBI1-YFP-HA or 35S::BEE2-YFP-HA were fixed on ice for 45 min in 1% formaldehyde under vacuum. Fixed tissues were homogenized, and chromatin was isolated and sonicated to generate DNA fragments with an average size of 500 bp. The solubilized chromatins were immunoprecipitated by Protein A+G magnetic beads (Magna, USA) with anti-HA (Sigma-Aldrich, USA), and the co-immunoprecipitated DNAs were subsequently recovered and analyzed by qPCR with the SYBR Premix Ex Taq Mix (TAKARA, Japan). The relative fold enrichment was calculated by normalizing the amount of target DNA fragments against the respective input DNA samples and then against the amount of PP2A genomic fragments. Primers used for ChIP-PCR are listed in Supplementary Table S1 .

Recombinant protein production in bacteria, and EMSA

To produce recombinant HBI1 and BEE2 proteins in bacteria, the corresponding ORFs were cloned into the pGEX4T1 vector (GE Healthcare Biosciences, USA). The resulting plasmids were transformed into BL21 cells containing pRIL (Agilent, USA). Protein expression was induced by adding 0.2 mM isopropyl-β- d -thiogalactopyranoside (IPTG) to the cell cultures at A 600 ~1.0 and incubated for 3 h at 37 °C. The cells were harvested and lysed using CelLytic B (Sigma-Aldrich, USA). The glutathione S -transferase (GST) fusion proteins were bound to glutathione–Sepharose 4B columns (Amersham, USA) and then eluted by 10 mM reduced glutathione in 50 mM Tris–HCl buffer (pH 8.0) ( Patra et al. , 2018 ).

For EMSA, two (GASA1 37 bp and GASA2 30 bp) probes were synthesized, with or without 5′ biotin labeling (Integrated DNA Technology, USA). The probes were designed to include the potential binding sites, as indicated by the ChIP experiment and protoplast transient assay. Oligos were annealed to produce double-stranded probes for EMSA using nuclease-free duplex buffer (Integrated DNA Technology, USA). The DNA-binding reactions were carried out in 10 mM Tris, pH 7.5, 50 mM KCl, 5 mM MgCl 2 , 1 mM DTT, 2.5% glycerol, 0.5% NP-40, and 50 ng of poly(dI–dC) in a final volume of 20 µl. Purified proteins were incubated with 25 fmol DNA probe at room temperature for 45 min. For the competition experiment, cold probes were added in an excess molar ratio (1000 times). The DNA–protein complexes were resolved by electrophoresis on 6% non-denaturing polyacrylamide gels and then transferred to BiodyneB modified membrane (0.45 mm; Pierce, USA). The band shifts were detected by a chemiluminescent nucleic acid detection module (Pierce, USA) and exposed to X-ray films.

BRs promote seed germination by accelerating cell expansion

The completion of seed germination requires two sequential steps: shortly after imbibition, the testa and endosperm rupture consecutively, followed by radicle emergence ( Bentsink and Koornneef, 2008 ; Weitbrecht et al. , 2011 ). We analyzed the Arabidopsis seed germination in the presence of 2,4-epibrassinolide (one of the biologically active brassinosteroids, hereafter referred to as BR). Seeds were germinated on half-strength MS medium alone or supplemented with 1 µM BR. At 12 h, ~40% of testa rupture was observed in control seeds, compared with 86% in BR-treated seeds. Endosperm rupture was significantly higher (55%) in BR-treated seeds compared with the control (undetectable). Similar patterns of endosperm rupture were also observed at 24 h ( Fig. 1A , B ), suggesting that BR promotes seed germination by accelerating testa and endosperm rupture.

BR accelerates seed germination by promoting cell expansion. (A) Germination phenotypes of wild-type (WT) Arabidopsis (Col) seeds treated with 1 µM BR for 12 h and 24 h. (B) Percentages of testa and endosperm rupture in (A). (C) Hypocotyl length of WT seeds treated with 1 µM BR at 36 h. (D) Images of embryonic axis cells of WT seeds treated with 1 µM BR at 36 h; the yellow asterisk indicates the first cell. (E and F) Cell length and width, respectively, of the embryonic axis of WT seeds in (D). Seeds germinated on half-strength basal MS were used as control. ND, no detection. The black asterisks indicate significant differences compared with control (one-way ANOVA was used to analyze the significant differences). Three biological replicates were used for analysis. * P <0.05; ** P <0.01.

Hypocotyl elongation assays were conducted under similar conditions to those of germination assays. BR significantly promoted the hypocotyl length by ~30% compared with the control ( Fig. 1C ). The sizes of the four cells in the hypocotyl–radicle transition region were measured to determine whether the effects of BR on embryo axis growth were caused by cell division or cell elongation. The cell lengths were greater in the presence of BR compared with the control ( Fig. 1D , E ). The effects of BR on the four cells in the transition region seem to be gradual, as in the presence of BR the lengths of the cell closest to the radicle (the first cells) increased 86 µm in contrast to the fourth cells which increased 40 µm ( Fig. 1D , E ). A similar effect of BR was observed on cell width ( Fig. 1D , F ). These observations imply that BR accelerates endosperm rupture by promoting cell elongation in the hypocotyl–radicle transition region of the embryo.

HBI1 and BEE2 mediate endosperm rupture mainly via enhancing BR and GA responses

HBI1 and its closest homolog BEE2 are known to act downstream of BR and GA signaling pathways to promote cell elongation ( Bai et al. , 2012a ). However, their roles in seed germination have not been investigated. We performed qRT-PCR to examine the expression of HBI1 and BEE2 during Arabidopsis seed germination as well as their response to BR and GA treatments. The seeds were stratified for 3 d, and expression of HBI1 and BEE2 was measured at 0, 16, and 24 h of light exposure. The expression of both HBI1 and BEE2 increased gradually during seed germination. Transcript abundance of BEE2 was higher than that of HBI1 in germinating seeds ( Fig. 2A , B ; Supplementary Fig. S1 ). Consistent with previous observations, the expression of both regulators was significantly induced following BR or GA treatment ( Fig. 2C , D ; Supplementary Fig. S2A, B ). Next, we determined whether ABA regulates expression of HBI1 and BEE2 to influence endosperm rupture. We found that the expression of HBI1 and BEE2 was significantly increased in the abi5 mutant compared with that in the WT ( Supplementary Fig. S3 ). Additionally, ABA repressed the expression of HBI1 in WT seeds while BEE2 expression did not change significantly ( Supplementary Fig. S4 ). Next, we compared endosperm rupture in seeds of HBI1 and BEE2 overexpression lines ( HBI1-OE and BEE2-OE ) with that of the control (WT) in the presence of the BR biosynthesis inhibitor, BRZ. Compared with the WT, the HBI1-OE and BEE2-OE seeds were less sensitive to BRZ, as evidenced by significantly higher percentages of endosperm rupture in the BRZ-supplemented medium ( Fig. 2E , F ). In addition, we compared the percentage of edosperm rupture of HBI1-OE and BEE2-OE with that of the WT in the presence of the GA biosynthesis inhibitor, PAC. Under the control condition, HBI1-OE showed no difference in seed germination compared with the WT, but in the presence of PAC, HBI1-OE showed an ~65% increase of seed germination ( Fig. 2G ). Similarly, the percentage of endosperm rupture of BEE2-OE was significantly higher than that of the WT in the presence of PAC ( Fig. 2G ). In addition, overexpression of HBI1 ( HBI1-OE ) diminished the negative effect of ABA on seed germination, as evident by the higher percentage of endosperm rupture compared with that of WT and BEE2-OE seeds when treated with ABA ( Supplementary Fig. S5A ). These findings suggest that overexpression of HBI1 enhances the BR and GA responses in regulating endosperm rupture, and HBI1 is capable of counteracting the inhibitory effect of ABA during seed germination.

HBI1 and BEE2 are involved in BR-mediated endosperm rupture. Relative transcript levels of GASA6 , HBI1 , and BEE2 in response to BR and GA 3 as measured using quantitative RT-PCR (qRT-PCR). The expression of HBI1 (A) and BEE2 (B) during the course of seed germination; 0 h was marked as the time point when seeds were exposed to light after 3 d of stratification. Two-week-old seedlings were treated with 1 µM BR (C) or 100 µM GA 3 (D) for 2 h. The transcript levels were normalized to UBQ1 . Data represent the mean ±SE ( n =3). One-way ANOVA was used to analyze any significant difference. All experiments were repeated at least twice with similar results. (E) Images of germination phenotypes of WT (Col), HBI1 -OE , or BEE2 -OE seeds treated with 1 µM BRZ for 36 h; scale bar=0.1 cm. (F) Percentages of endosperm rupture (ER) in WT, HBI1-OE , or BEE2 -OE seeds in (E). (G) Percentages of ER of WT, HBI1 -OE , or BEE2 -OE seeds treated with 1 µM PAC for 54 h. (H) Percentage of ER in WT, GASA6-OE and GASA6-RNAi seeds treated with 1 µM BRZ at 48 h. Seeds germinated on half-strength basal MS was used as the control. The asterisks indicate significant differences compared with control or the WT (one-way ANOVA was used to analyze significant differences). Three biological replicates were used for analysis. * P <0.05; ** P <0.01.

HBI1 and BEE2 promote seed germination, probably via GASA6

HBI1 is a potential regulator of genes encoding many cell wall-related proteins, such as expansins and GASAs ( Fan et al. , 2014 ). A previous study has shown that GASA6 acts as a positive regulator in GA-, ABA-, and Glc-mediated seed germination ( Zhong et al. , 2015 ). However, the involvement of GASA6 in BR signaling is not well studied. We performed qRT-PCR to determine the effect of BR on GASA6 expression. Similar to HBI1 and BEE2 , GASA6 expression was significantly activated by BR and GA ( Fig. 2C , D ; Supplementary Fig. S2A, B ). Also similar to HBI1 , expression of GASA6 was induced in abi5 seeds and reduced in WT seeds in the presence of ABA ( Supplementary Figs S3A, B, S4A, B ). In addition, the seed germination efficiencies of GASA6 -overexpressing lines ( GASA6-OE ) and RNAi lines ( GASA6-RNAi ) were evaluated in the presence of BRZ. In the control conditions, no significant change in seed germination was observed for either GASA6-OE or RNAi lines ( Fig. 2H ). However, in the presence of 1 µM BRZ, seeds of GASA6-OE showed increased germination compared with the WT, whereas seeds of GASA6-RNAi displayed decreased germination ( Fig. 2H ). Similarly, in the presence of ABA, GASA6-OE seeds showed a significantly improved germination rate compared with the WT and GASA6-RNAi ( Supplementary Fig. S5B ). These results suggest that HBI1 and GASA6 act coordinately to promote BR- and GA-mediated seed germination and attenuate the negative effect of ABA during seed germination.

HBI1 and BEE2 directly regulate GASA6 expression in Arabidopsis

In silico analysis identified a total of 12 bHLH TF-binding motifs (E-box elements) in the GASA6 promoter ( Supplementary Fig. S6 ). In addition, the co-expression analysis using the ATTED-II network drawer revealed that both HBI1 and BEE2 are co-expressed with GASA6 ( Supplementary Figs S7–S9 ). To test whether HBI1 and BEE2 regulate GASA6 expression through binding to the E-box elements, we first determined GASA6 expression in the HBI1-OE and BEE2-OE lines, as well as in the HBI1-SRDX and BEE2-SRDX lines. As HBI1 and BEE2 are functionally redundant, it is assumed that the single knockout mutants will not show an obvious phenotype ( Malinovsky et al. , 2014 ). Therefore, we used the HBI1-SRDX and BEE2-SRDX lines, in which the dominant repressor form of HBI1 or BEE2 specifically suppresses the target genes, thus preventing the possible interference of functional redundancy ( Hiratsu et al. , 2003 ; Ikeda et al. , 2012 ). The results showed that GASA6 expression was significantly higher in HBI1-OE or BEE2-OE lines than that in the WT but was repressed markedly in the HBI1-SRDX or BEE2-SRDX lines ( Fig. 3A ; Supplementary Fig. S10 ), indicating that HBI1 and BEE2 regulate the expression of GASA6 in Arabidopsis.

To identify the binding sites of HBI1 and BEE2 in the GASA6 promoter, we performed transient expression assays using Arabidopsis protoplasts. Truncated fragments of the GASA6 promoter, cloned into the pGreenII 0800-LUC vector ( Hellens et al. , 2005 ), served as reporters. HBI1 or BEE2 , expressed under the control of the CaMV 35S promoter, were used as effectors. The reporters and effectors were co-transformed into Arabidopsis mesophyll protoplasts in different combinations. HBI1 or BEE2 significantly induced the activities of the 1.4 kb and 1.2 kb GASA6 promoters (upstream of the ATG start codon). However, their effects were dramatically reduced on the 1.1 kb and 0.9 kb promoter ( Fig. 3B ). These observations indicate that the 100 bp region between 1.2 kb and 1.1 kb of the GASA6 promoter is likely to be critical for the HBI1- and BEE2-induced expression. We identified three E-box elements (CAAATG, CATGTG, and CACATG) between 1.4 kb and 1.1 kb. To clarify the importance of these three E-box elements in HBI1/BEE2-controlled expression, point mutants were generated individually in the three E-boxes and used in the Arabidopsis transient expression assays. As shown in Fig. 3C , the last two nucleotides (TG) in all three E-box elements were replaced with AA to generate mutant promoters, mut 1, 2, 3, and their combination, mut 1 + 2 and mut 1 + 3 ( Fig. 3C ). The transient expression assays showed that, compared with the activation of the WT promoter, the activation of the three single mutant promoters by HBI1 was significantly reduced, whereas only mut 3 affected the activation by BEE2. However, the double mutation, mut1 + 3, significantly reduced the activation by either HBI1 or BEE2 ( P <0.001) ( Fig. 3D , E ), indicating that two or more distantly located E-boxes are required for the regulation of GASA6 by the two factors.

HBI1 and BEE2 regulate GASA6 expression by binding to the E-box-like elements in vivo and in vitro. (A) Transcript levels of GASA6 in HBI1- or BEE2-OE and SRDX lines measured using quantitative RT-PCR (qRT-PCR). Data were normalized to UBQ1 . (B) Transactivation of the full - length and truncated GASA6 promoter–reporters by HBI1 or BEE2 in Arabidopsis protoplasts. Various constructs used in transient expression assays are shown in the upper panel. (C) Schematic diagram of the 1.4 kb GASA6 promoter with all E-boxes (black) and mutated E-boxes (red) used in (D) and (E). Transactivation of the GASA6 promoter and its mutants by HBI1 (D) or BEE2 (E) in Arabidopsis protoplasts. (F) Schematic diagram of different fragments of the GASA6 promoter (left); the numbers indicate the promoter length. Analysis of GUS activities in different pGASA6::GUS lines (right). Scale bar=0.5 mm. (G) Schematic diagram of the GASA6 promoter. P1 to P6 indicate fragments used for chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) amplification. ChIP-qPCR analysis of HBI1-HA or BEE2-HA binding to the GASA6 promoter upon precipitation with anti-HA antibody. Five-day-old 35S::HBI1-YFP-HA , 35S::BEE2-YFP-HA , or WT seedlings were used in ChIP-qPCR. Fold enrichments indicate the enrichment of HBI1-HA or BEE2-HA binding to the GASA6 promoter compared with that of the WT. Data represent the mean ±SE of three replicates. (H) EMSA of HBI1 or BEE2 after incubation with biotin-labeled DNA probes containing the E-box sequences of the GASA6 promoter (Probe1 and Probe2). In competition experiments to demonstrate the specific binding of proteins to the probes, non-labeled probes (cold probes) were added in 1000-fold excess of the labeled probes. Values represent the mean ±SE of at least four biological replicates. Except when specifically indicated, asterisks indicate significant differences compared with control (one-way ANOVA was used to analyze the significant differences). * P <0.05; ** P <0.01.

To further validate this, we performed 5′ end deletion analysis of the GASA6 promoter using transgenic plants expressing various truncated promoter fragments fused to the GUS reporter gene. Analysis of the transgenic plants revealed that the region between –2100 bp and –1100 bp, where multiple E-boxes reside, is potentially important for GASA6 expression during seed germination and seedling growth ( Fig. 3F ).

Next, we performed ChIP-PCR assay using transgenic plants expressing HBI1-YFP-HA or BEE2-YFP-HA to measure enrichment of the E-boxes in the GASA6 promoter. The WT plants served as control. HBI1 strongly bound to the E-box-containing regions of P5 (–1367 bp upstream of ATG) in the GASA6 promoter ( Fig. 3G ). A similar DNA enrichment pattern by the BEE2-YFP-HA protein was also detected in the GASA6 promoter ( Fig. 3G ), suggesting that HBI1 and BEE2 co-target the GASA6 promoter, probably via direct binding to the E-box elements. However, the E-box elements (CACATG and CATGTG) in the 100 bp region are different from the one (CAAATG) in the P5 fragment, suggesting that the mechanisms of HBI1 or BEE2 regulating GASA6 expression are somewhat intricate. Direct binding of HBI1 or BEE2 to the E-box elements in the GASA6 promoter was further verified by EMSA, where two DNA probes, with or without 5′ biotin labeling, were synthesized based on the E-box elements of the GASA6 promoter (Probe 1, caatttttaatca caaatg ctattttattggacgacc; Probe 2, GTCTCC CATGTG AGTG CACATG GAGTTATG). The results showed that both HBI1 and BEE2 individually bind to the E-box elements, resulting in a mobility shift. The specificity of the DNA–protein interaction was confirmed by the competition experiment, in which the addition of excess (1000×) non-labeled probe eliminated the interaction between labeled probe and HBI1 or BEE2 ( Fig. 3H ).

BEE2 and HBI1 form a heterodimer and synergistically regulate expression of GASA6

It has been well demonstrated that bHLH factors homo- or heterodimerize through the bHLH domain ( Heim et al. , 2003 ; Toledo-Ortiz et al. , 2003 ). To determine whether HBI1 and BEE2 form a homo- or heterodimer, we first performed BiFC in Arabidopsis mesophyll protoplasts. Reciprocal fusions of BEE2, IBH1, and HBI1 with the N- or C-terminal half of YFP (nYFP and cYFP, respectively) were generated and co-transformed into the protoplasts in combinations. IBH1, a known interactor of BEE2 and HBI1, served as a positive control. Strong YFP fluorescence signals were observed in the nucleus when HBI1–nYFP or BEE2–nYFP was co-transformed with IBH1–cYFP and BEE2–nYFP was co-transformed with HBI1–cYFP, indicating specific interactions of HBI1–IBH1, BEE2–IBH1, and BEE2–HBI1 ( Fig. 4A ). Next, we performed yeast two-hybrid assays to confirm that the HBI1–BEE2 interaction is mediated by the bHLH domains. BEE2 was truncated into four fragments, with or without the bHLH domain, fused with the GAL4 AD, and co-expressed with HBI1 fused with the GAL4 BD ( Fig. 4B . Only the bHLH domain-containing BEE2 fragments interacted with HBI1, confirming the requirement of the bHLH domain in dimerization.

HBI1 and BEE2 modulate the expression of GASA6 by forming a homodimer or heterodimer in vivo . (A) Bimolecular fluorescent complementation (BiFC) assay shows that HBI1 and BEE2 interact with each other and IBH1 to form heterodimers in Arabidopsis mesophyll protoplasts. YFP, signal of yellow fluorescence protein; Chlorophyll, autofluorescence of chloroplasts; Bright, protoplasts in light view; Merge, merge of YFP, chlorophyll, and light view. (B) Diagram of the BEE2 domain structures and various deletions (left); yeast two-hybrid assays show the heterodimer of HBI1, and the interaction domain. Protein–protein interactions were detected by yeast growth on triple (–His–Leu–Trp) dropout selection medium, with 5 mM 3-amino-1,2,4-triazole (3-AT) (right). (C) Schematic diagram of various constructs used in transient expression assays (D). (D) Transactivation of the GASA6 promoter (1.4 kb) by HBI1, BEE2, and IBH1 in Arabidopsis mesophyll protoplasts. The GASA6 promoter fused to the LUC reporter was co-transformed with effectors or empty vector (control) into mesophyll protoplasts. Fold of LUC/REN indicates the expression level of GASA6 activation by various effectors. Values represent the mean ±SE of four biological replicates. Except when specifically indicated, asterisks indicate significant differences compared with control (one-way ANOVA was used to analyze the significant differences). ** P <0.01.

To determine the biological significance of the dimerization among HBI1, BEE2, and IBH1, we performed transient expression assays in the protoplasts with different combinations of these effector proteins ( Fig. 4C ) on the GASA6 promoter (p GASA6-luc ). As shown in Fig. 4D , activation of the GASA6 promoter was significantly higher when HBI1 and BEE2 were co-expressed (HBI1+BEE2) compared with HBI1 or BEE2 expressed alone ( Fig. 4D ). On the other hand, the addition of IBH1 significantly attenuated the activity of HBI1 or BEE2 ( Fig. 4D ), possibly by forming a non-DNA-binding complex with HBI1 or BEE2 as described previously ( Ikeda et al. , 2012 ; Zhiponova et al. , 2014 )

GASA6 acts downstream of HBI1 and BEE2 to promote cell elongation

To investigate the relationship between HBI1 or BEE2 and GASA6 at the genetic level, HBI1- OE /gasa6 and BEE2/gasa6 plants were generated by making a genetic cross between HBI1-OE or BEE2-OE transgenic plants and the homozygous GASA6 T-DNA insertion mutant ( gasa6 ) . HBI1-OE or BEE2-OE lines exhibited a BRZ-resistant phenotype. Although no significant difference was observed between the WT and gasa6 under the control condition ( Fig. 5A ), the endosperm rupture percentage of gasa6 was markedly reduced compared with the WT under 1 µM BRZ treatment ( Fig. 5B ). Furthermore, HBI1-OE or BEE2-OE in the gasa6 background showed increased sensitivity to BRZ (~60%; Fig. 5B ), compared with that without BRZ treatment (~90%; Fig. 5A ), suggesting that, in the BR signaling cascade, GASA6 acts downstream of HBI1 and BEE2 to promote cell elongation.

GASA6 acts downstream of HBI1 and BEE2 to promote seed germination. Endosperm rupture (ER) percentage of WT, HBI1-OE , BEE2-OE , gasa6 , HBI1-OE/gasa6 and BEE2-OE/gasa6 seeds after 18, 24, and 36 h of germination (A) control (half-strength basal MS medium) and (B) half-strength basal MS medium with 1 mM BRZ. The black asterisks indicate significant differences compared with the WT (one-way ANOVA was used to analyze the significant differences). * P <0.05; ** P <0.01.

BR and GA are principal plant growth regulators that function redundantly to control many important physiological functions, including seed germinations and cell elongation ( Steber and McCourt, 2001 ; Hu and Yu, 2014 ; Li et al. , 2018 ; Zhao et al. , 2019 ). Physical interactions between BZR1/BES1 and DELLAs mediate the crosstalk between BRs and GAs during cell elongation in Arabidopsis ( Bai et al. , 2012b ; Gallego-Bartolome et al ., 2012; Li et al. , 2012 ); however, the molecular mechanism underlying GA–BR crosstalk during seed germination is not well studied. In this study, we demonstrated that BR accelerates endosperm rupture by enhancing the growth of the hypocotyl–radicle transition region of the embryo ( Fig. 1 ), similar to what has been observed previously in GASA6 overexpression ( Zhong et al. , 2015 ). The elongation of the embryonic axis in a completely germinated Arabidopsis seed is a result of cell elongation rather than cell division ( Sliwinska et al. , 2009 ). As expected, the length and width of the cells in the hypocotyl–radicle transition region are significantly increased in the presence of BR ( Fig. 1D–F ), suggesting that BR affects cell elongation and width during embryonic axis elongation before endosperm rupture in Arabidopsis. Although the underlying mechanism requires further investigation, our findings provide a new insight into the coherent events at BR-promoted cell elongation during seed germination.

BZR1 and BES1 contribute to regulation of seed germination ( Ryu et al. , 2014 ; Zhao et al. , 2019 ). The gain-of-function mutant bes1-D exhibits reduced sensitivity to ABA during seed germination, a phenotype not observed in the bzr1-D mutant, suggesting that BES1, but not BZR1, is the major contributor to BR-mediated suppression of ABA signaling during seed germination ( Ryu et al. , 2014 ). In addition, BES1 physically interacts with ABI5 to attenuate the ABA-mediated suppression of seed germination by lowering the expression of ABI5 targets ( Zhao et al. , 2019 ). Similar to that of GASA6 ( Zhong et al. , 2015 ), we found that HBI1 and BEE2 expression increased gradually during seed germination ( Fig. 2A , B ; Supplementary Fig. S1 ) and increased significantly in abi5 mutant seeds ( Supplementary Fig. S3 ). ABA repressed the expression of HBI1 in WT seeds, while BEE2 expression remained unchanged ( Supplementary Fig. S4 ). We thus hypothesized that HBI1 and BEE2 are involved in regulation of seed germination. Supporting this notion is that the endosperm rupture of the HBI1-OE or BEE2-OE lines showed decreased sensitivity to the BR biosynthesis inhibitor BRZ ( Fig. 2 E, 2F ). Seeds of HBI1-OE did not show the negative effect of ABA on germination ( Supplementary Fig. S5 ), suggesting that, similar to BZR1 and BES1, HBI1, and possibly BEE2, breaks ABA-induced dormancy and promotes GA–BR-indued seed germination. Our results indicate that HBI1 and BEE2 are involved in BR-mediated seed germination by promoting endosperm rupture through controlling cell elongation.

It has been demonstrated that the tripartite HLH/bHLH module, PRE–IBH1–HBI1, regulates cell elongation in response to GA and BRs ( Bai et al. , 2012a ; Fan et al. , 2014 ). Consistent with the role of HBI1 in promoting cell elongation ( Bai et al. , 2012a ), BEE2, the closest homolog of HBI1, plays redundant roles in cell elongation ( Carretero-Paulet et al. , 2010 ). The germination phenotypes of the BEE2-OE and HBI1 -OE lines ( Fig. 2F , G ) support the individual role of HBI1 and BEE2. To identify downstream targets of HBI1 and BEE2, we performed co-expression network analysis and found that GASA6 , known to integrate GA, ABA, and Glc signaling to regulate seed germination ( Zhong et al. , 2015 ), is co-expressed with HBI1 ( Supplementary Fig. S8 ) and BEE2 ( Supplementary Fig. S9 ). In addition, similar to HBI1 and BEE2 , GASA6 expression is also activated by BR and GA ( Fig. 2C , D ; Supplementary Fig. S2 ). Both HBI1 and BEE2 function in the GA- and BR-mediated seed germination processes ( Fig. 2E–G ). Our findings suggest that the inhibitory effect on seed germination by BRZ is overcome by GASA6 overexpression but enhanced by GASA6 -RNAi ( Fig. 2H ). We showed that HBI1 and BEE2 promote seed germination by directly regulating the expression of GASA6 . The transcript levels of GASA6 were significantly altered in the overexpression and repression lines of HBI1 and BEE2 ( Fig. 3A ; Supplementary Fig. S10 ). In addition, the region between 2.1 kb and 0.9 kb of the GASA6 promoter is important for GASA6 expression during seed germination and seedling growth ( Fig. 3F ). ChIP-qPCR, EMSA, and protoplast transactivation assays suggested that HBI1 and BEE2 activate the GASA6 promoter mainly through binding the region between 1.4 kb and 1.1 kb ( Fig. 3 ). Furthermore, mutations in the potential bHLH-binding motifs in the GASA6 promoter significantly affected the promoter activity in Arabidopsis protoplasts ( Fig. 3D , E ), indicating that the two E-box motifs (CACATG and CATGTG) in the GASA6 promoter are crucial for the activation by HBI1 and BEE2. HBI1 and BEE2 overexpression in the gasa6 mutant increased the sensitivity to BRZ ( Fig. 5 ). Collectively, these results indicated that GASA6 is one of the downstream targets of HBI1 and BEE2 in the regulation of BR–GA-regulated seed germination.

Combinatorial transcriptional regulation is a hallmark of eukaryotic gene expression. Tight regulatory control is achieved by the highly dynamic nature of transcriptional activators and repressors. Heterodimeric TFs increase options of gene expression control. bHLH TFs are known to form homo- and heterodimers to regulate the expression of target genes ( Toledo-Ortiz et al. , 2003 ). Here, we demonstrated the interaction between HBI1, BEE2, and IBH1 in both yeast cells and Arabidopsis mesophyll protoplasts ( Fig. 4A , B ). In addition, BEE2 is found to interact with HBI1 to synergistically activate GASA6 ( Fig. 4D ). On the other hand, IBH1 antagonizes the function of HBI1 and BEE2 in activating GASA6 expression, possibly by forming non-DNA-binding complexes, HBI1–IBH1 or BEE2–IBH1 ( Fig. 4D ). Accumulating evidence suggests that interactions between activators and repressors fine-tune plant growth, development, and metabolic outcomes. In barley, the GA pathway is controlled by the interaction of two transcriptional activators and two repressors ( Zou et al. , 2008 ). In Catharanthus roseus , GBF1 and GBF2 interact with and antagonize transcriptional activities of MYC2 on the pathway gene promoters ( Sui et al. , 2018 ). Similarly, the subgroup IIId bHLH TF RMT1 competes with MYC2 and antagonizes its activity ( Patra et al. , 2018 ). In Arabidopsis, TCP4 interacts with AP2/ERF WRINKLED1 to attenuate its transcriptional activity to fine-tune seed oil accumulation ( Kong et al. , 2020 ). We showed that the HBI1–BEE2–IBH1 module is critical in regulation of BR–GA-induced seed germination.

BR and GA pathways are well characterized for triggering expression of downstream genes, such as GASA6 . Less known is how the combined effects of BRs and GA regulate the gene expression. Prior to this study, the transcriptional hub that amplifies the BR–GA signal to GASA6 was elusive. Our findings reveal a new role for GASA6 in BR signaling and uncover an additional molecular mechanism of GA–BR-induced seed germination in Arabidopsis. HBI1 and BEE2 promote endosperm rupture and seed germination by directly activating the expression of GASA6 . Moreover, further dissections of the protein–protein and protein–DNA interactions associated with the regulatory network advance our understanding of GA–BR-induced cell elongation during endosperm rupture.

The following supplementary data are available at JXB online .

Fig. S1. Relative gene expression of HBI1 and BEE2 during seed germination.

Fig. S2. Relative gene expression of HBI1 , BEE2 , and GASA6 in response to BR and GA.

Fig. S3. Relative expression of GASA6 , HBI1 , and BEE2 in abi5 mutant seeds.

Fig. S4. Relative gene expression of HBI1 , BEE2 , and GASA6 in response to ABA.

Fig. S5. Effect of ABA on endosperm rupture of WT, HBI1-OE , or BEE2-OE seeds.

Fig. S6. Cis -motif analysis of the AtGASA6 promoter.

Fig. S7. The co-expression network of GASA6 in Arabidopsis as analyzed by the ATTED-II network drawer.

Fig. S8. The co-expression network of HBI1 in Arabidopsis as analyzed by the ATTED-II network drawer.

Fig. S9. The co-expression network of BEE2 in Arabidopsis as analyzed by the ATTED-II network drawer.

Fig. S10. Relative gene expression of GASA6 in HBI1- or BEE2-OE and SRDX lines.

Table S1. List of gene-specific primer sequences.

Our sincere thanks go to Dr Sitakanta Pattanaik (University of Kentucky) for his thoughtful suggestions and critical review of this manuscript. We thank Dr Cyril Zipfel (Sainsbury Laboratory, UK) for kindly providing the overexpression lines of HBI1 and BEE2 , and Dr Masaru Ohme-Takagi (Institute for Environmental Science and Technology of Saitama University, Japan) for kindly providing the SRDX lines of HBI1 and BEE2 . This work was funded by the National Natural Science Foundation of China (grant no. 31700282 to CZ, and 90917011 and 31372099 to XW). This work is also supported partially by the Harold R. Burton Endowed Professorship to LY and by the National Science Foundation under Cooperative Agreement no. 1355438 to LY.

CZ, BP, LY, and XWL: study design; CZ, BP, YT, and XL: performing the experiments; CZ, B.P, LY, and XW: data analysis; CZ, BP, XW, and LY: writing.

The authors declare no conflicts of interest.

Sequence data from this study can be found in the Arabidopsis Genome Initiative or GenBank/EMBL databases under the following accession numbers: HBI1 ( At2g18300 ), BEE2 ( At4g36540 ), IBH1 ( At2g43060 ), GASA6 ( At1g74670 ), UBQ1 ( At3g52590 ), PP2A ( At1g69960 ), and TUB3 (At5g 62700). All data supporting the findings of this study are available within the paper and within its supplementary data published online.

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Journal of Nanobiotechnology volume  22 , Article number:  565 ( 2024 ) Cite this article

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Graphene oxide (GO), beyond its specialized industrial applications, is rapidly gaining prominence as a nanomaterial for modern agriculture. However, its specific effects on seed priming for salinity tolerance and yield formation in crops remain elusive. Under both pot-grown and field-grown conditions, this study combined physiological indices with transcriptomics and metabolomics to investigate how GO affects seed germination, seedling salinity tolerance, and peanut pod yield. Peanut seeds were firstly treated with 400 mg L⁻¹ GO (termed GO priming ). At seed germination stage, GO-primed seeds exhibited higher germination rate and percentage of seeds with radicals breaking through the testa. Meanwhile, omics analyses revealed significant enrichment in pathways associated with carbon and nitrogen metabolisms in GO-primed seeds. At seedling stage, GO priming contributed to strengthening plant growth, enhancing photosynthesis, maintaining the integrity of plasma membrane, and promoting the nutrient accumulation in peanut seedlings under 200 mM NaCl stress. Moreover, GO priming increased the activities of antioxidant enzymes, along with reduced the accumulation of reactive oxygen species (ROS) in response to salinity stress. Furthermore, the differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) of peanut seedlings under GO priming were mainly related to photosynthesis, phytohormones, antioxidant system, and carbon and nitrogen metabolisms in response to soil salinity. At maturity, GO priming showed an average increase in peanut pod yield by 12.91% compared with non-primed control. Collectively, our findings demonstrated that GO plays distinguish roles in enhancing seed germination, mitigating salinity stress, and boosting pod yield in peanut plants via modulating multiple physiological processes.

Introduction

High salt concentration is a significant constraint to crop growth, severely reducing productivity, especially under the ongoing global climate change scenario [ 1 , 2 ]. To survive under salinity conditions, plants have evolved intricate regulatory mechanisms to minimize salt toxicity [ 3 , 4 ]. From the perspective of plant growth and development, some plant species enhance their growth by promoting the assimilation, transportation, and distribution of nutrients like nitrogen (N), phosphorus (P), and potassium (K) to counteract high soil salinity [ 5 , 6 ]. In some cases; however, the plant growth is inhibited under high soil salinity conditions for the purpose of stimulating plant salinity responses like activating cell signaling pathways, enhancing photosynthesis, and modulating antioxidant systems [ 4 , 7 ]. The contradictions among the above results have attracted considerable attention, thus prompted us to further elucidate the coordination in the trade-off between plant growth and crop salinity resistance.

Legumes have long been recognized as important sources of proteins for human beings and livestock [ 8 – 10 ]. Legumes contribute significantly to sustainable agriculture and global food security by uniquely fixing atmospheric nitrogen through rhizobia symbiosis in their root nodules [ 11 , 13 ]. As a typical representative of legumes, peanut is originated from South America, and is cultivated in arid and semi-arid areas worldwide [ 14 , 15 ]. Compared with other oilseed crops, peanut seeds rich in unsaturated fatty acids (e.g. oleic acid, linoleic acid, and linolenic acid), which are beneficial to the cardiovascular protection of humans [ 16 , 17 ]. In the past decade; however, soil salinity imposes severe limitations to peanut root growth, nodule development, N fixation capacity, and finally productivity [ 18 – 20 ]. Therefore, more eco-friendly and economical management practices are warranted to restrict the adverse impact of soil salinity on peanut production.

Graphene oxide (GO) is classified as a member of nanomaterials (NMs) family with multiple functions like adsorption, oxidation, and catalytic activity [ 21 , 22 ]. In the practice of environmental science, GO has been prominently utilized for removal of heavy metals or organic pollutants in both contaminated soil and wastewater due to the properties of large pore volume and rich surface chemistry [ 86 , 24 ]. In the past decade, the extensively utilization of GO in agricultural production has broaden our horizon in dissecting the prominent roles of NMs on crop science. To date, literatures have uncovered the profound role of GO application on plant abiotic stress responses which could be mainly ascribed to the following reasons: enhancement of plant growth via regulating nutrient assimilation [ 25 , 26 ], protection of photosynthetic apparatus by facilitating electron transfer process [ 27 , 28 ], and reduction of membrane lipid peroxidation through scavenging reactive oxygen species (ROS) [ 29 , 30 ]. Nonetheless, obstacles still exist to utilize GO in crop production due to its versatility. It should be noted that the over-accumulation of GO in the soil could aggravate the toxicity of toxicants and pollutants, and finally interference with plant growth [ 31 – 33 ]. Seed priming is an eco-friendly and remarkable management strategy widely adopted by agronomists and farmers to confer soil salinity [ 34 , 35 ]. Priming substances could stimulate the physiological and signalling processes of the sprouting seeds and invoke the plant salt tolerance in late growth stages without contaminating soil [ 36 – 38 ]; however, the mechanisms of NMs in seed priming are rarely known. Therefore, a research gap whether NMs like GO could be taken as a potential seed priming candidate in response to crop salinity stress should be properly addressed.

To favor our understanding of GO in peanut seed germination, salinity responses and pod productivity, the current study was carried out to test the hypothesis that seed priming with GO induced salinity tolerance in peanut seedlings is associated with the enhancement of plant growth, with a particular focus on the modulation of photosystem, antioxidant system, phytohormones, and carbon and nitrogen metabolisms. To this end, our study explored significant evidence from physiological, transcriptional, and metabonomic investigations using both pod-grown and field-grown experiments. The outcome of this study could provide a general guidance for the utilization of NMs to strengthen salinity resistance and increase productivity of legumes in the context of sustainable agriculture.

Materials and methods

Plant materials and treatments, experiment i.

To test the priming effects of graphene oxide (GO) on peanut ( Arachis hypogaea L.) seed germination, seeds of the peanut cv. Huayu 25, a prominent cultivated variety of Shandong Province, were germinated in petri dishes. The investigation was performed at Qingdao Agricultural University, Qingdao, Shandong Province, China from January to May, 2023. Prior to germination, visually similar seeds underwent surface disinfection using a 1% sodium hypochlorite solution for 15 min, followed by thorough rinsing in sterile distilled water. Subsequently, half of the seeds were immersed in distilled water (termed CK ), while the remaining seeds were exposed to 400 mg L − 1 graphene oxide (termed GO priming ) in a dark environment at 28 °C. The GO was purchased from Daojin Technology Co. Ltd. (Beijing, China). In our preliminary experiment, 400 mg L − 1 has been proven to be the best concentration of graphene solution in stimulating peanut seed germination (unpublished data). After 24 h, the seeds were transferred to petri dishes with filter paper underneath (40 to 50 seeds in one dish). For “ CK ”, the seeds were applied with 50 mL of distilled water daily for 5 consecutive days. For “ GO priming ”, the seeds were treated with 50 mL of distilled water/400 mg L − 1 graphene solution daily at 2, 4, 6/3, 5 days after germination, respectively (Fig.  1 A & H). The germination rate (GR) and percentage of seeds with radicals breaking through testa (PSWRB) were monitored for a period of 1 to 6 days. At 4 days after germination, seeds from both treatments were snap-frozen in liquid nitrogen and delivered to BioTree Biotechnology Co., Ltd. (Shanghai, China) for transcriptomic and metabolomics analysis.

Schematic diagram ( H ) illustrating the experimental design and effects of seed priming with GO on promoting seed germination ( A ), alleviating seedling salinity stress ( D ), and enhancing productivity ( I & J ) of peanut. Characterization of GO in peanut seeds using SEM image ( C ). Characterization of GO in peanut seeds ( B ), leaves ( E ), stems ( F ), and roots ( G ) using Raman spectrum

Experiment II

To investigate the effects of GO priming on salinity tolerance of peanut seedlings, a pot-grown assay was conducted in Qingdao Agricultural University, Shandong Province, China from May to October, 2023. Seeds from Experiment I , namely “CK” and “GO” were sown in polystyrene pots (inner diameter of 9 cm and depth of 8 cm) separately. The seeds were sown 2 cm below the soil surface, with one seed per pot. Each pot contained 200 g of soil that had been heat-sterilized twice. The soil’s key properties included a pH of 6.83, bulk density of 1.19 g cm − ³, organic matter content of 23.5 g kg − 1 , total nitrogen at 90.2 mg kg − 1 , available phosphorus at 28.3 mg kg − 1 , and available potassium at 67.9 mg kg − 1 . The pots were then moved to a greenhouse with the following conditions: a 16/8-hour photoperiod (light/dark), photosynthetic photon flux density (PPFD) of 1,000 µmol m⁻² s⁻¹, daytime air temperature of 25 °C, nighttime air temperature of 18 °C, and relative humidity of 75%. Each pot received 100 mL of distilled water every 2 days. 21 days after sowing, half of the “CK” and “GO” seedlings were subjected to salinity treatment by replacing distilled water with 200 mM NaCl solution in each pot at 22 and 29 days after sowing (Fig.  1 D and H). Notably, the concentration of NaCl solution utilized in the current experiment was based on our preliminary experiments and previous reports [ 39 – 41 ]. In total, four treatments were composed: “CK”, “GO”, “NaCl”, and “GO + NaCl”. At 35 days after sowing, the seedlings were collected for the determination of agronomic characters and physiological parameters. Meanwhile, root samples from the four treatments were simultaneously snap-frozen in liquid nitrogen and delivered to BioTree Biotechnology Co., Ltd. (Shanghai, China) for transcriptomic and metabolomics analysis.

Experiment III

To investigate the effects of GO priming on peanut production, a field-grown experiment was carried out at Laixi experimental station, Shandong Province, China from May to October in 2022 and 2023. The chemical properties of the soil were determined before the initiation of the experiment (Table. S1 ). Basal synthetic fertilizer (750 kg ha −1  ; N: P 2 O 5 : K 2 O = 1: 1.5: 1.5) were applied before sowing. The field was cultivated with cereal and legume crops for 8 consecutive years. Peanut seeds treated as described in Experiment I , namely “CK” and “GO”, were sown in one seedling hole on 8 May and 9 May, in 2022 and 2023, respectively. The seeds were sown on a raised bed with two rows with bed height of 12 cm, bed width of 90 cm, row space of 30 cm, and hole space of 17 cm (Fig.  1 I & J). Other agronomic practices such as irrigation, pesticide spraying, and weed control were carried out based on local farmers’ practices. The peanut pods were manually harvested on 13 September and 11 September, in 2022 and 2023, respectively. A total of three replicates (blocks) were composed with area of 45.0 m 2 (4.5 m × 10.0 m) each. After sun-drying thoroughly, peanut pod yield as well as yield related components including plant number per hectare, pod number per plant, and 100-pod weight were measured.

Synthesis of graphene oxide, scanning electron microscopy (SEM) and Raman Spectra analysis

A modified hummer’s method was utilized for the preparation of GO [ 42 , 43 ]. In brief, 1 g of graphite power was added into a solution (130 mL concentrated sulfuric acid, 30 mL phosphoric acid, containing 6 g of KMnO 4 ) and mixed at 0 °C. Then, the mixture was incubated in an oil bath at 50ºC for 12 h with continually stirring. After cooling, the solution was poured into a beaker containing 15 mL H 2 O 2 and 100 mL distilled water under mechanical stirring until the solution turned into light yellow. Then, the solution was further stirred for 2 h to ensure the complete oxidation of graphite. Afterwards, the obtained turbid was centrifuged at 2000 rpm for 5 min until the black particles were separated. The turbid in the top of tube was washed with concentrated HCl, distilled water, and ethanol for three times, respectively. Finally, the products were freeze dried overnight to obtain the GO the with purity > 99wt%; oxygen content of 30–40%; layers of 1–5, thickness of 0.55 to 1.2 nm, and diameter ranging from and 0.5 to 3 μm.

The morphology and texture of GO in primed peanut seeds was characterized with a scanning electron microscope (SEM, JSM-7500 F, JEOL, Japan) following the method outlined by Cao et al. [ 21 ]. The plant samples (root, stem, and leaf) were washed twice with distilled water, dried, and ground into powder. Then the Raman spectrum of GO and the above samples were identified using Raman spectroscopy (DXR2xi, Thermo, USA) with a 532-nm excitation laser according to the protocol of Liu et al. [ 44 ].

Plant morphology

Plant height was assessed by measuring the length of the main stem (from the cotyledonary node to the apical meristem). Subsequently, seedlings were categorized into different organs, and their fresh weight (FW) was recorded. The samples were then oven-dried at 105 °C for 30 min and stove-heated at 70 °C for 5 days to determine the dry weight (DW).

The peanut root morphology was detected based on our preliminary studies [ 41 ]. The root samples were completely dissected and thoroughly washed with distilled water. Then, the samples were scanned with a root scanning equipment (V700; SEIKO EPSON CORP.). The obtained data was further analyzed using WinRHIZO software (version 2013e; Regent Instruments Inc.).

Transmission electron microscope (TEM) observation

The subcellular structure of peanut leaves was visualized using a cytochemical staining method [ 45 , 46 ]. The freshly excised leaf tissue pieces (1–2 mm 2 ) were firstly incubated in 1.25% (v/v) glutaraldehyde buffer at 4℃ for 4 h, and then in paraformaldehyde buffer (50 mM sodium cacodylate, pH 6.9) for another 4 h. Then the tissues were polymerized at 60℃ for 48 h after dehydrating in a graded ethanol series (30–100%; v/v). A Reichert-Ultracut E ultramicrotome was utilized to cut the leaf sections to 70–90 nm. Ultimately, the leaf sections were visualized at an accelerating voltage of 75 kV with a transmission electron microscope (HT7700; Hitachi, Tokyo, Japan).

Gas exchange parameters

Gas exchange parameters were assessed on the third fully developed leaf of the main stem (termed functional leaf) in each seedling using established methods [ 39 , 47 ] with a portable photosynthesis gas analyzer-coupled portable photosynthesis system (LI-6800, LI-COR, Lincoln, NE, USA) between 9:00 and 11:00 a.m. Measurements included net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), and intercellular CO 2 concentration (Ci). The conditions in the leaf chamber (2 cm × 3 cm) were set to an ambient CO 2 concentration of 400 µmol mol − 1 , a PPFD of 1,000 µmol m − 2 s − l , an air temperature of 25 ± 1℃, and a relative air humidity of 80%.

Chlorophyll fluorescence and chlorophyll content

The chlorophyll fluorescence parameters of the functional leaf were determined using a chlorophyll fluorescence imaging system (Imag-Maxi, Heinz Walz, Effeltrich, Germany) based on our preliminary experiments [ 40 , 48 ]. After the treated seedlings were dark adapted for 30 min, the third fully developed leaf of the main stem was cut down to analysis the chlorophyll fluorescence parameters such as the maximal photochemical efficiency of Photosystem II (PSII) (Fv/Fm), quantum yield of PSII photochemistry (ΦPSII), and photochemical quenching coefficient (qP) as area of interest. The chlorophyll fluorescence parameters were calculated by the FluorImager software (Version 2.2; Technologica Ltd., United Kingdom).

To determine the total chlorophyll content, 0.05 g leaves were accurately weighed and transferred to 25 mL glass scale tubes, and then extracted by adding 25 mL mixture of acetone and ethanol (1:1, v/v). Then, the samples were incubated for 12 h under dark at 40℃ and mixed thoroughly for several times. The absorbance values at 663 and 645 nm were measured by an UV-Vis spectrophotometer (Cary 60, Agilent, USA). The total chlorophyll content was calculated as described by Lichtenthaler and Wellburn [ 59 ] using the following formula:

Ca = 12.72×A663-2.59×A645 (1).

Cb = 22.88×A645-4.67×A663 (2).

Ct = Ca + Cb = 20.29×A645 + 8.05×A663 (3).

where Ca is chlorophyll a content (mg·L − 1 ), Cb is chlorophyll b content (mg·L − 1 ), Ct is total chlorophyll content (mg·L − 1 ), and A663 and A645 represent absorbance at 663 and 645 nm, respectively.

Relative water content and relative electrolyte conductivity

The relative water content (RWC) of the functional leaf was measured according to Jensen et al. [ 50 ]. The excised leaves were soaked in 10 mL of distilled water for 4 h under dark at 4℃ to obtain the turgid weight (TW). The fresh weight (FW) and dry weight (DW) were determined as mentioned above. RWC was calculated as the following formula: RWC (%) = [(FW − DW) / (TW − DW)] × 100.

The relative electrolyte conductivity (REC) was analyzed with a conductivity bridge (DDS-307 A, LEX Instruments Co., Ltd., China) following the protocol of Griffith and Mclntyre [ 51 ]. The functional leaves were soaked in 10 mL of distilled water for 12 h under dark at 25℃ to obtain the conductivity (C1). After which the solution was boiled for 30 min and the conductivity (C2) was measured again after cooling. REC (%) was calculated as: C1/C2 × 100%.

Histochemical staining and quantitative assay of H 2 O 2 and O 2 −

Hydrogen peroxide (H 2 O 2 ) within the functional leaf was visually detected in situ through the application of 3,3’-diaminobenzidine (DAB) staining [ 52 ]. Leaf samples were submerged in a DAB solution at a concentration of 1 mg mL − 1 (pH 3.8) and incubated for 12 h at 25℃, under a PPFD of 1000 µmol m − 2 s − 1 . Subsequently, the leaves underwent bleaching in boiling ethanol at a concentration of 95% (v/v) and were then immersed in a lactic acid/phenol/water mixture at equal parts (1:1:1, v/v/v) for imaging purposes. Similarly, the in situ visual detection of superoxide anion (O 2 − . ) was performed using nitro blue tetrazolium (NBT) staining [ 53 ]. The leaf samples were immersed in a 1 mg mL − 1 NBT solution (pH 6.1) for 8 h at 25℃ in the absence of light. The bleaching and imaging process for these samples was identical to that described above.

For the quantitative assay of hydrogen peroxide (H 2 O 2 ), 0.2 g fresh functional leaf samples were excised and homogenized immediately with pre-cooled 2 mL of 0.2 M HClO 4 . After centrifuging at 6,000 g for 5 min at 4℃, the supernatant was collected and adjusted to pH 6.5. After centrifuging at 12,000 g for 5 min at 4℃, H 2 O 2 was eluted from the supernatant and mixed with 0.4 mL reaction buffer containing 4 mM 2, 2’-azino-di-(3-ethylbenzthiazoline-6-sulfonic acid), 100 mM potassium acetate, and horseradish peroxidase (0.5 U). Then, the quantification of H 2 O 2 levels was ascertained by monitoring the absorbance shift of the titanium peroxide complex at a wavelength of 412 nm [ 55 ].

For the quantitative assay of O 2 −· production rate, 0.2 g fresh functional leaf samples were excised and homogenized immediately with 2 mL of pre-cooled phosphate buffer (50 mM, pH 7.8). After centrifuging at 12,000 g for 20 min at 4℃, the supernatant was collected for the subsequent determination. Then, 0.5 mL of the supernatant was mixed thoroughly with 0.5 mL of phosphate buffer (50 mM, pH 7.8) and 1 mL of hydroxylamine hydrochloride (10 mM). After incubating for 1 h at 25℃, 1 mL of p-aminobenzene sulfonic acid (17 mM) and 1 mL of α-naphthylamine (7 mM) were added and incubated for another 20 min at 25℃. After centrifuging at 3,000 g for 5 min, the O 2 −· production rate was quantified by monitoring the synthesis of nitrite at 530 nm [ 27 ].

Antioxidant enzyme activities and malondialdehyde content

Fresh samples weighing 0.5 g from the functional leaves were pulverized using a pre-cooled mortar and pestle, mixed with 5 mL of ice-cold phosphate buffer (50 mM, pH 7.8) that included 20% glycerol (v/v), 0.2 mM EDTA, 5 mM MgCl 2 , 1 mM AsA, 1 mM GSH, and 1 mM DTT. This mixture was then subjected to centrifugation at 12,000 g for 20 min at 4℃. The resulting supernatant was utilized to evaluate the activity of various antioxidant enzymes, namely superoxide dismutase (SOD), catalase (CAT), guaiacol peroxidase (G-POD), ascorbate peroxidase (APX), and to measure the levels of malondialdehyde (MDA) equivalents. The activity of SOD was measured at 560 nm, reflecting its capacity to inhibit the photochemical reduction of nitro blue tetrazolium (NBT), according to the method of Stewart and Bewley [ 56 ]. CAT activity was gauged by the rate of H 2 O 2 degradation, observed at 240 nm, adapting the method by Patra et al. [ 57 ]. G-POD activity was assessed with a guaiacol substrate at 470 nm based on the procedure of Cakmak and Marschner [ 58 ]. APX activity was determined through the rate of ascorbate oxidation at 290 nm based on the protocol of Nakano and Asada [ 59 ]. The content of MDA was ascertained using the thiobarbituric acid (TBA) reaction method, with absorbance readings of the red adduct taken at 450, 532, and 600 nm to compute the MDA equivalents [ 60 ].

Accumulations of total soluble sugar, sucrose, and free amino acids

The dry samples of peanut roots were firstly powdered by a high-speed ball mill (MM400; Retsch GmbH, Haan, Germany). Then, 0.1 g of the samples was extracted with 8 mL of 80% (v/v) ethanol at 80℃. After centrifugation at 3000 g for 30 min, the supernatant was collected for the subsequent determination. The total soluble sugar content was analyzed at 620 nm based on the anthrone method [ 61 ]. The sucrose content was determined at 480 nm following the resorcinol method as described by Buysse and Merckx [ 61 ]. The free amino acids (FAA) content was evaluated at 570 nm following the ninhydrin reaction as modified by Moore and Stein [ 62 ].

Contents of nitrogen, phosphorus, and potassium

The dry samples of peanut roots were powered as mentioned above and digested with H 2 SO 4 -H 2 O 2 . The total nitrogen (N) content was determined using the micro Kjeldahl method [ 63 ]. The total phosphorus (P) content was measured by a continuous flow analyzer based on the procedure of Khashi u Rahman et al. [ 64 ] with minor modifications. The total potassium (K) content was determined by using a flame photometer following the method of Chakraborty et al. [ 65 ].

Total RNA extraction and RNA-seq analysis

Freshly excised peanut root samples were used for total RNA extraction using the Cetyltrimethylammonium bromide (CTAB) method [ 66 ]. The RNA’s purity, concentration, and integrity were assessed with a NanoPhotometer ® spectrophotometer (IMPLEN, CA, USA), a Qubit ® RNA Assay Kit in a Qubit ® 2.0 Fluorometer (Life Technologies, CA, USA), and an RNA Nano 6000 Assay Kit on the Bioanalyzer 2100 system (Agilent Technologies, CA, USA), respectively [ 67 ]. Subsequently, 1 µg of high-quality RNA per sample was used to construct the cDNA library, which was sequenced on an Illumina HiSeq platform by Novogene Corporation Inc. The software fastp v0.19.3 was employed to clean and trim the raw data, ensuring high-quality clean reads by filtering out reads with adapters, paired reads with over 10% N content, and reads where more than 50% of the bases had a quality score of Q ≤ 20 [ 68 ]. The clean data were then mapped to the peanut reference genome ( https://peanutbase.org/ ) using HISAT v2.1.0 software. The expression abundance of reads was quantified using the fragments per kilobase of transcript per million base pairs (FPKM) value. Differentially expressed genes (DEGs) between the groups were identified using DESeq2 v1.22.1 (Ross Ihaka, University of Auckland, New Zealand) with a threshold of |log 2 Fold Change| ≥ 1 and a False Discovery Rate (FDR) < 0.05 [ 69 ]. Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation ( http://www.genome.jp/kegg/ ) of DEGs were performed as reported [ 70 ].

Quantitative real-time PCR

The identical total RNA specimens from the aforementioned RNA-seq study were employed in the subsequent quantitative real-time PCR (qRT-PCR) evaluation [ 71 ]. Details regarding the specific primers are presented in Table S2 . For the synthesis of cDNA, 1 µg of total RNA was utilized, employing the TransScript ® II First-Strand cDNA Synthesis SuperMix (AH301-03, TransGen Biotech Co., Ltd, Beijing, China) [ 72 ]. The products, once diluted to a tenfold degree, were then applied to the quantitative real-time PCR (qRT-PCR) process [ 73 ], which was conducted using SYBR ® Green Pro Taq HS (AG11701, Accurate Biotechnology (Hunan) Co., Ltd, Changsha, China) on the ECO real-time PCR system by Illumina [ 74 ].

Non-targeted metabolites extraction and determination

To identify the root-specific metabolites, non-targeted metabolite profiling was conducted. Briefly, root samples were meticulously cleansed with distilled water, then snap-frozen in liquid nitrogen, and dispatched to Gene Denovo Biotechnology Co., Ltd. for metabonomic evaluation [ 75 , 76 ]. The specimens underwent LC-MS/MS analysis using a Vanquish UHPLC system (Thermo Fisher Scientific). Subsequently, the raw data were transformed into mzXML format. High-resolution mass spectrometry data were then processed using MAPS and matched against an MS2 database for identification. Hierarchical clustering analysis followed, generating a dendrogram via the average linkage method, as detailed by Yuan et al. [ 77 ]. Principal component analysis (PCA) was also executed to delineate group distinctions. The (O)PLS model’s variable importance in projection (VIP) scores were employed to prioritize the differentially accumulated metabolites (DAMs) that most effectively differentiated the groups. Metabolites exhibiting a T-test P - value  < 0.05 and a VIP score ≥ 1 were deemed significantly different between the groups. Conclusively, KEGG pathway enrichment analysis was performed for metabolite annotation [ 78 , 79 ]. Both positive and negative ion modes were integrated for the entire analysis. Experiment I comprised three replicates while Experiment II included four.

Statistical analysis

The experimental design for the measurements employed a fully randomized model, incorporating three biological duplicates: each consisting of three petri dishes in Experiment I and ten seedlings in Experiment II , excluding metabonomic assessments. Results were presented as mean values ± standard deviation (SD) and subjected to one-way and multi-factor ANOVA using SPSS 22.0 (SPSS Inc.). The disparities between treatments were assessed for significance using Tukey’s test.

Characteristics of graphene oxide in peanut seeds and seedlings

The GO used in the current study was firstly detected with a SEM. In Experiment I , the GO in the primed seeds exhibited a stacked and folded form with layered structure (Fig.  1 C). Raman spectroscopy further showed the representative D and G peaks of GO in primed seeds (Fig.  1 B). In Experiment II , the representative D and G peaks of GO were only observed in peanut stems and roots (Fig.  1 F and G), other than leaves (Fig.  1 E) in GO-primed seedlings. These observations indicate that seed priming is an effective way to accumulate GO during the peanut seedling stage.

Graphene oxide promoted the germination of peanut seeds

To examine the effect of GO priming on seed germination of peanut, we conducted Experiment I . Seed priming with GO significantly increased the PSWRB by 25.51% compared with CK at 1 day after germination whereas no significant difference was observed along the rest time course of germination process. By contrast, GO-primed seeds exhibited a significant increase in germination rate by 7.95% and 7% at 5 and 6 days after germination, respectively, compared with the non-primed seeds (Fig.  2 A & B). RNA-seq analysis was conducted to further elucidate the expression levels of the genes associated with GO. A total of 1703 DEGs (935 up-regulated and 768 down-regulated) were detected in GO treated peanut seeds compared with CK (Fig.  2 C). qRT-PCR analysis indicated that the selected genes exhibited similar expression patterns with the RNA-seq data Fig. S5 ).

Effects of seed priming with GO on phenotypes of peanut seeds ( A ), percentage of seeds with radicals breaking through testa (PSWRB) and germination rate ( B ) during germination. ( C ) Volcano plot of the DEGs in GO-treated peanut seeds. ( D ) KEGG pathway analyses of the enriched DEGs in GO-treated peanut seeds. The enrichment circle diagram is from outside to inside, and the first circle is the KEGG pathway ID label. The strip length of the second circle corresponds to the enriched DEGs of the pathway, which represents the number of total DEGs, up-regulated DEGs and down-regulated DEGs, respectively. The third circle (polar histogram) is Rich factor

Based on the KEGG pathway enrichment analysis (Fig.  2 D), the majority of the top 19 enriched pathways were related to metabolic processes. These include pathways such as “Starch and sucrose metabolism”, the “TCA (tricarboxylic acid) cycle” involved in sugar metabolism, and “Glycine, serine, and threonine metabolism” associated with protein metabolism. Additionally, secondary metabolic processes like “Flavonoid biosynthesis” and “Phenylpropanoid biosynthesis” were also enriched (Table. S3 ). Furthermore, according to KEGG and Gene Ontology enrichment analyses, intracellular information exchange and protein processing were also enriched (Figs.  2 C and S1 ). Specifically, pathways related to protein processing in the “Endoplasmic Reticulum” and “Golgi-associated vesicles” showed enrichment. These findings suggest that GO priming may influence the seed primary metabolism (sugar and protein) as well as secondary metabolisms, thus potentially promotes seed germination.

Graphene oxide promoted peanut seed growth by regulating amino acid and secondary metabolisms

The non‑targeted metabolites assay was further carried out to elucidate the role of GO priming on seed metabolite profiles. PCA analysis indicated that the first and second principal components were displayed on the X (PC1, 38.2%) and Y (PC2, 17.7%) axis, respectively. The replicate samples clustered together and obvious separations have been observed between GO and CK (Fig.  3 B). A total of 64 DAMs (36 up-regulated and 28 down-regulated) have been identified in GO-treated seeds compared with CK (Table. S4 ). Particularly, most of the DAMs could be mainly classified as “Alkaloids”, “Amino acids”, “Benzenoids”, and “Organic acids” (Fig.  3 A). Furthermore, the differentially abundant metabolites were conducted using KEGG database. Pathways associated with “Amino acid metabolism” and “Secondary metabolites biosynthesis” exhibited higher degree of alteration in GO-primed peanut seeds compared with non-primed control (Fig.  3 C).

Dynamical changes of DAMs in GO-treated peanut seeds compared with CK. ( A ) Identified metabolites were clustered based on their abundance relative to control samples. The red and blue colors of the boxes represent upregulated and downregulated DAMs, respectively. ( B ) Principal Component Analysis (PCA) of metabolites in different groups. ( C ) KEGG classification of DAMs in response to GO

Graphene oxide enhanced peanut seedling growth by modifying nitrogen metabolism and phytohormones biosynthesis under salinity stress

To explore the impact of GO priming on the salinity stress tolerance of peanut seedlings, we conducted Experiment II . The results revealed that, compared to the control group, GO treatment alone had few effects on peanut growth and development (Fig.  4 A, B and C). However, under salinity conditions, GO-treated peanut seedlings exhibited significant improvements in both above-ground and below-ground growth (Fig.  4 A). Consequently, we focused on the effects of salinity stress (abbreviated as “NaCl”) in conjunction with GO priming (abbreviated as “GO + NaCl”). When compared to salinity stress alone, GO priming led to a remarkable increase of 17.47% in plant height, 27.22% in root length, and 26.28% in fresh weight, while the increase in dry weight was not statistically significant under salinity stress (Fig.  4 B & C). Furthermore, we conducted transcriptome sequencing for each treatment, identifying 991 DEGs shared between “GO + NaCl vs. CK” and “NaCl vs. CK” Fig. S2 A). KEGG enrichment analysis revealed their association with nitrogen utilization, secondary metabolism, and plant hormones Fig. S2 B). Additionally, we performed metabolomic profiling, which showed similar patterns to the phenotypic results. PCA indicated that the “CK” and “GO” groups were more closely related, while “NaCl” and “GO + NaCl” exhibited distinct metabolic features at the metabolic level Fig. S3 A). Further KEGG analysis of DAMs revealed significant enrichment in pathways related to proteins, sugars, and plant hormones Fig. S3 B & C).

GO alleviates peanut salinity stress through enhancing plant growth. ( A ) Phenotype analysis of seedlings under different treatments. Statistical analysis of the aboveground and underground parts of peanut seedlings under different treatments. ( B ) Plant height and root length. ( C ) Fresh weight (FW) and dry weight (DW) of stem + leaf and root. ( D ) Total nitrogen content of roots. mean ± SD ( n  = 3), “ns” non-significant, * P <0.05, ** P <0.01, Tukey’s test. Heatmap of DEGs and DAMs in nitrogen metabolism ( E ) and plant hormone metabolism including gibberellin ( F ), cytokinin ( G ) and auxin ( H ), respectively. Grids represent the expression levels of genes, which were shown as FPKM values, Padj  < 0.05. The red and blue colors of the boxes represent up-regulated and down-regulated genes, respectively. The orange and green colors of the boxes represent up-regulated and down-regulated metabolites, respectively

GO has been reported to enhance nutrient absorption in plants [ 21 ]. To investigate whether graphene affects nutrient uptake under salt stress, we measured the carbon, phosphorus, and potassium content in the roots. The results showed that GO priming significantly increased the nitrogen, phosphorus, and potassium content in the roots compared to salinity stress alone (Figs.  4 D and S4 ). Specifically, nitrogen, phosphorus, and potassium levels increased by 44.37%, 88.62%, and 29.90%, respectively (Figs.  4 D and S4 ). Notably, the NRT2 transporter, responsible for nitrogen uptake, exhibited the highest expression under salt stress, likely due to feedback regulation caused by nutrient deficiency. Additionally, in the plastids, GLU and GLUD1_2 expression was significantly higher in “GO + NaCl”, leading to the recovery of glutamate levels (Fig.  4 E).

Regarding hormones, we analyzed gene expression and content related to growth hormones and stress-responsive hormones (Fig.  4 F, G and H). Upstream rate-limiting enzymes in the gibberellin (GA) pathway, KAO and GA20ox were significantly reduced under salinity stress whereas GO priming partially restored their expression (Fig.  4 F). GA1 and GA4, the biologically active forms of GA in plants, are catalyzed by GA3ox . While salt stress suppressed the expression of this gene, GO priming promoted the reaction by upregulating the expression of GA3ox (Fig.  4 F), aligning with the observed phenotypic changes ( Fig.  4 A ) . A similar pattern was observed for auxin: the precursor of IAA- L-tryptophan content was lowest under salinity stress whereas GO priming partially restored it. Furthermore, key enzymes involved in IAA synthesis, ALDH and YUCCA, exhibited higher expression in “GO + NaCl” compared with “NaCl” (Fig.  4 H). In terms of stress hormones, we found that the cytokinin precursor DMAPP accumulated under salt stress, while the downstream key enzyme IPT expression was weakened. Consequently, the final cytokinin content was lower in “NaCl” than in “GO + NaCl” (Fig.  4 G). Overall, although standalone GO priming had limited effects on peanut seedling growth, it enhanced salinity stress tolerance by regulating nitrogen assimilation and plant hormone metabolism.

Graphene oxide regulated osmoregulation and carbon metabolism of peanut seedlings in response to salinity stress

To further investigate the impact of GO priming on peanut salt tolerance, we conducted analyses on soluble sugars, free amino acids, and total soluble sugars in the plant roots (Fig.  5 A). The results revealed that the combination of GO and NaCl led to lower levels of soluble sugars and sucrose compared to salt treatment alone. Interestingly, the content of free amino acids in the “GO + NaCl” was approximately 10% higher than in the “NaCl” (Fig.  5 A). Given these findings, we speculate that GO priming helps to maintain the osmotic pressure of peanut roots under salt stress, thereby enhancing salt tolerance.

GO alleviates peanut salinity stress through modulating carbon metabolism. ( A ) Contents of sucrose, free amino acids, and total soluble sugar. mean ± SD ( n  = 3), “ns” non-significant, * P <0.05, ** P <0.01, Tukey’s test. ( B ) Heatmap of DEGs and DAMs in carbon metabolic pathways. Grids represent the expression levels of genes, which were shown as FPKM values, Padj  < 0.05. The red and blue colors of the boxes represent up-regulated and down-regulated genes, respectively. The orange and green colors of the boxes represent up-regulated and down-regulated metabolites, respectively

Furthermore, we observed that the expression levels of genes involved in D-fructose synthesis ( INV and malZ ) were lower in the GO + NaCl treatment compared to salt treatment alone (Fig.  5 B). Conversely, genes responsible for D-glucose synthesis exhibited the opposite expression pattern. Additionally, genes ( TPS and ostB ) related to the synthesis of trehalose, which could protect the cells in high-osmotic environments, were upregulated in the “GO + NaCl” group compared with “NaCl”. On another note, the synthesis of non-soluble starch sugars also showed some improvement under GO supplementation compared to “NaCl” (Fig.  5 B). Taken together, GO priming influences carbon metabolism and osmotic regulation in peanut under salinity stress.

Graphene oxide increased the photosynthesis and strengthened the photosystem of peanut seedlings in resistance to salinity stress

We further investigated the role of GO priming in the regulation of peanut photosystem under salinity stress (Fig.  6 A). Standalone GO priming showed little effects on Fv/Fm and Pn while significantly increased the total chlorophyll content by 50.14% under stress-free conditions. Soil salinity significantly reduced the Fv/Fm, Pn, and total chlorophyll content whereas GO priming significantly increased the Fv/Fm, Pn, and total chlorophyll content by 17.62, 74.15, and 158.23%, respectively, under salinity stress (Fig.  6 C, D and E). Apart from Fv/Fm, some major chlorophyll fluorescence parameters including ΦPSII, Fv’/Fm’, and ETR were dramatically increased whereas NPQ was reduced by GO priming (Fig.  6 F). RNA-seq analysis further revealed that GO priming significantly elevated the expression of some crucial genes regarding the components of photosynthetic chain (LHCII, Photosystem II, Cytochrome b 6 /f complex, Photosystem I, LHCI, and F-type ATPase) under both stress-free and salinity conditions (Fig.  6 B). These results provide evidence that GO priming -induced alleviation effects of peanut salinity stress is associated with the strengthened photosystem.

GO alleviates peanut salinity stress via regulating photosystem. ( A ) Schematic diagram of the photosynthetic system in plant photosynthesis. ( B ) The expression profile of transcripts involved in photosynthesis. Grids represent the expression levels of genes, which are shown as FPKM values, Padj  < 0.05. The red and blue colors of the boxes represent up-regulated and down-regulated genes, respectively. ( C ) Maximal photochemical efficiency of photosystem II (PSII) (Fv/Fm). The false-color code, depicted at the bottom of the image, ranges from 0 (black) to 1 (purple). Different lowercase letters on imagines indicate significant differences among treatments. mean ± SD ( n  = 3), P <0.05, Tukey’s test. ( D ) Net photosynthetic rate (Pn). ( E ) Leaf total chlorophyll content. mean ± SD ( n  = 3), “ns” non-significant, * P <0.05, ** P <0.01, Tukey’s test. ( F ) Radar maps of some crucial chlorophyll fluorescence parameters

Graphene oxide enhanced the antioxidant system and maintained the plasma membrane integrity of peanut seedlings under soil salinity conditions

To investigate the role of GO priming in the modulation of peanut antioxidant system under salinity stress, we firstly assessed the activities of crucial antioxidant enzymes. Standalone GO treatment significantly increased the activities of SOD (100.59%) and G-POD (69.61%) compared with CK. Strikingly, the activities of SOD, APX, and CAT were dramatically increased by 94.88, 289.19, and 139.89%, respectively, under salinity conditions in peanut leaves of GO priming (Fig.  7 A). In accordance with the antioxidant enzyme data, the histochemical staining and quantity assay of ROS further indicated that GO priming significantly reduced the accumulation of H 2 O 2 and O 2 − . in peanut leaves under salinity stress (Fig.  7 A). We further detected the cell membrane peroxidation through evaluating the synthesis of MDA where seedlings of GO priming exhibited lower concentration of MDA under soil salinity conditions (Fig.  7 B). Under stress-free conditions, no significant difference was detected between GO priming and CK plants in RWC and REC. Under salinity growth conditions, GO priming significantly increased the leaf RWC by 134.08% while significantly reduced the leaf REC by 53.35%, compared with control (Fig.  7 B). Moreover, no significant difference was observed between “GO” and “CK” in the subcellular structure of peanut leaves; however, exposure to salinity stress led to severe damages in cytoplasmic membrane, mitochondria, and chloroplast. Notably, GO priming alleviated salt-induced plasmolysis and maintained the integrity of thylakoid and plasma membrane (Fig.  7 C).

GO alleviates peanut salinity stress through maintaining antioxidant system and plasma membrane integrity. ( A ) Concentrations of O 2 − . and H 2 O 2 , histochemical analysis of O 2 − . and H 2 O 2 by NBT and DAB staining, and activities of antioxidant enzymes (SOD, APX, G-POD, and CAT). ( B ) Concentrations of MDA, RWC, and REC. mean ± SD ( n  = 3), “ns” non-significant, * P <0.05, ** P <0.01, Tukey’s test. ( C ) Observation of the subcellular structure of peanut leaves by TEM. Scale bar = 1 μm

Graphene oxide increased the peanut productivity

We further investigated the potential role of GO priming in peanut productivity under field-grown conditions. GO priming significantly increased the peanut pod yield by 12.25% and 13.56% in 2022 and 2023, respectively, compared with non-primed control. For yield related components, no significant difference was observed in plant number per ha; however, GO priming significantly increased the 100-pod weight/pod number plant − 1 by 5.17/8.16% and 6.38/8.86% in 2022 and 2023, respectively, compared with CK (Table  1 ).

In recent years, the profound roles of NMs in plant growth and abiotic stress responses have received a broad spectrum of attention. The utilization of NMs also provides a fruitful avenue for agronomists and farmers to strengthen seedling growth and mitigate crop environmental stress in a more precise and economical way [ 80 – 82 ]. Here we investigate, for the first time, the dominant roles of GO priming in promoting seed germination, alleviating seedling salinity stress, and enhancing productivity in peanut plant. The results of the present work may help farmers develop profitable strategies by using NMs like GO in resisting soil salinization.

Literatures advocated that NMs could promote plant growth under both favorable and harsh conditions due to their unique property of high surface-to-volume ratio [ 83 , 84 ]. In the present work, we were able to visualize the phenotype of GO on the surface of GO-inoculated peanut seeds (Fig.  1 C). In conformity with earlier reports, we deduce that the increased surface-to-volume ratio could contribute to the acceleration of nutrient and water assimilation, and consequently increased GR and PSWRB (Fig.  2 B). Sugar and protein have been proposed as key components during seed germination [ 85 , 86 ]. From a metabolomic point of view, GO-primed peanut seeds exhibited increased accumulation of metabolites regarding sugar and protein pathways (Fig.  3 ). It is, therefore, quite plausible that GO priming plays a relevant role in promoting the biosynthesis of seed constituent substances. It is worth mentioning that GO priming also induced the secondary metabolomic processes including “Flavonoid biosynthesis” and “Phenylpropanoid biosynthesis” (Figs.  2 and 3 ). Accumulating evidence validated that flavonoids are a class of natural compounds with nutraceutical and pharmaceutical functions [ 87 , 88 ], which are also essential for crop abiotic stress responses [ 89 , 90 ]. In this regard, it appears likely that GO priming contributes to establishing a firm defence mechanism via modulating secondary metabolisms in peanut seeds, by which peanut plants could combat the upcoming environmental stress at seedling stage. The above observations prompted us to further elucidate the effects of GO priming on peanut salinity resistance at seedling stage.

The Raman spectrum of GO were detected in both stems and roots of peanut seedlings (Fig.  1 F and G). Strikingly, dramatic increases in volume, length, and nutrition contents of roots were observed in seedlings of GO priming under salinity stress (Figs.  4 A, B and D and S4 ), suggesting that GO priming might promote root growth via strengthening the absorption and/or biosynthesis of soil nutrients. From the physiological point of view, GO priming -enhanced photosynthesis (Fig.  6 D) could contribute to the accumulation of photosynthetic products like FAA under salinity stress (Figs.  5 A and  S3 ). On the one hand, the over-accumulation of FAA might participate in the biosynthesis of root structural proteins [ 91 , 92 ], thus boosting root growth to confer salinity stress (Fig.  4 A, B and C). On the other hand, FAA have been long recognized as major components of the osmoregulation system [ 93 , 94 ], which is responsible for maintaining the cell membrane integrity in root salinity resistance. Combined with transcriptome and metabolomics analysis, more attention have been paid to some enriched pathways associated with phytohormone, carbon, and nitrogen metabolisms in seedlings of GO priming under salinity stress. GO priming significantly increased the expression of genes like GLU and GLUD1_2 regarding L-Glutamate (L-Glu) biosynthesis, hence promoting the accumulation of L-Glu in peanut roots (Fig.  4 E). L-Glu acts as a precursor of environmental stress-related FAA and a long-distance signalling molecule, which is reportedly involved in plant abiotic stress responses [ 95 – 97 ]. Consequently, we deduce that GO priming mediated induction of FAA buildup justifies their beneficial roles in promoting root growth, maintaining osmotic pressure and mitigating peanut salinity stress.

Salinity stress impairs the activity of PSII, resulting in loss in the photochemical efficiency [ 98 , 99 ]. Combined with physiological and transcriptome data, we noticed that GO priming dramatically induced some crucial chlorophyll fluorescence parameters such as Fv/Fm, ΦPSII, and ETR (Fig.  6 ). The induction of ETR can be attributed to the fact that GO priming accelerates the electron transport system which was blocked by salinity stress. Meanwhile, GO priming protects PSII against over-excitation when the seedlings were suffering from soil salinity, as indicated by the induction of Fv/Fm and ΦPSII [ 100 , 101 ]. These results were consistent with the TEM observation data, suggesting that salinity-induced loss of integrity of thylakoid membranes has been effectively mitigated by GO priming (Fig.  7 C). As a result, GO priming -enhanced the integrity of thylakoid membranes contributes to the stability of chlorophyll molecules (Fig.  6 E), which in turn increases the photosynthetic rate (Fig.  6 D).

The multiple functions of phytohormones such as GA and CTK in plant salinity response are becoming increasingly evident. In some cases, the breakdown of GA and CTK resulted in vegetative growth restriction for a better adaptation of the soil salinity [ 102 – 104 , 99 ]. Conversely, the excessive accumulation of GA and CTK modulated the chloride exclusion from shoots in response to the harsh environment [ 105 , 106 ]. Here, data from RNA-seq indicate that the expression of genes involved in the metabolism of growth and stress-related hormones was significantly upregulated under both stress-free and saline conditions after GO priming . Specifically, the rate-limiting enzyme KAO and the final step enzyme GA3ox in the GA synthesis pathway were markedly increased under GO priming   ( Fig.  4 F ) . Similarly, the key gene IPT in the CTK metabolic pathway showed elevated expression levels following GO priming when exposed to salinity, which corroborated by our metabolomic results (Fig.  4 G). The well-known growth-promoting hormone IAA also exhibited increased expression of the critical YUCCA genes under GO priming , as shown by RNA-seq data ( Fig.  4 H ) . These results align with the observed growth and physiological data under various treatments ( Figs.  4 and 5 ) . Collectively, these observations suggest that GO priming enhances plant growth by regulating phytohormones to combat soil salinity. It is worth noting that GO failed to accumulate in peanut leaves (Fig.  1 E). Strikingly, outstanding contributions of GO priming in protecting the photosystem and enhancing the antioxidant system of peanut leaves have been detected under soil salinity conditions (Figs.  6 and 7 ). Herein, an interdependently association between the belowground and the aboveground parts of the seedling has been established whereby GO priming -induced phytohormones and osmotic regulatory substances might act as signals in maintaining this delicate balance. In summary, the above findings of the current work signified the essentiality of this sophisticated signal transduction mechanisms concerning GO priming -induced peanut salinity tolerance, which warrant further experimental evidence.

NMs emerge as promising new materials with immense potential for crop cultivation and breeding. Cost-benefit determinations have revealed that nanofertilizers and nanopesticides contribute significantly to increasing crop revenue while minimizing environmental risks [ 107 , 108 ]. However, as we integrate these NMs into agricultural practices, it may also address potential environmental health and safety concerns. During the seedling stage ( Experiment II ), although GO was detectable in both roots and stems, it was nearly absent in peanut leaves (Fig.  1 E, F and G). This suggests that residual GO enhances peanut salt tolerance, at least partially, through hormonal pathways (Fig.  4 ). Considering the peanut’s lengthy lifecycle; however, GO accumulation in leaves or pods remains minimal. Further evidence supporting the safety of graphene utilization comes from a study involving 14 C-labeled graphene in rice, in which 14 C-labeled graphene reacts with hydroxyl radicals in leaves, leading to its degradation into 14 CO 2 . Over a 15-day period, graphene accumulation in stems and leaves diminished, with no detectable graphene remaining in rice seeds [ 109 ]. Additionally, the polycyclic structure of graphene, akin to lignin and polycyclic aromatic hydrocarbons, renders it susceptible to degradation by lignin peroxidase enzymes secreted by soil microorganisms [ 110 ]. Thus, our investigation into the effects of GO priming provides a safe strategy for peanut cultivation under both stress-free and salinity conditions.

Integrated physiological parameters with transcriptomics and non-target metabolomics, we document that seed priming with 400 mg L − 1 GO could increase the seed germination rate and PSWRB of peanut seeds via simulating the biosynthesis of amino acids and secondary metabolites. Furthermore, when the seedlings were exposed to 200 mM NaCl stress, peanut seedlings of GO priming exhibited the promotion of plant growth including higher plant height, root length, and plant biomass. In addition, GO priming mediated photoprotection of photosynthetic machinery as indicated by the higher Pn, Fv/Fm, ΦPSII, and total chlorophyll content in response to soil salinity. Meanwhile, the activities of antioxidant enzymes including SOD, APX, and CAT were dramatically increased in peanut leaves of GO priming , hence reducing salt-induced higher MDA content and REC to maintain plasma membrane integrity. Moreover, GO priming also simulated the biosynthesis of some crucial phytohormones (GA, CTK, and IAA) and modulated the metabolisms of carbon and nitrogen in peanut roots, leading to the excessive accumulation of FAA and nutrients in response to salinity stress. Under field-grown conditions, GO priming also exhibited higher peanut pod yield with the increased 100-pod weight and pod number per plant (Fig.  8 ). Nonetheless, the mechanisms concerning GO priming -promoted yield formation of peanut pods, especially in late growth stages, should be further elucidated. Moreover, future studies pertaining to the genetic evidence of GO priming could provide a more comprehensive understanding of GO-legume interactions.

Working model illustrating the mechanisms of seed priming with GO in promoting seed germination and strengthening seedling salinity tolerance of peanut. Red and blue arrows represent up-regulation and down-regulation, respectively

Data availability

The RNA-seq data were deposited to the Sequence Read Archive (SRA) database of the National Center for Biotechnology Information (NCBI, accession number: PRJNA1105759 and PRJNA1105760).

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Acknowledgements

We are grateful to BioTree Biotechnology Co., Ltd. (Shanghai, China) for the assistance of metabolomics analysis. We thank X.-Y. Gao, J.-Q. Li, and Z.-P. Zhang from CAS Center for Excellence in Molecular Plant Sciences for the assistance of TEM.

This study was financially supported by the earmarked fund for China Agriculture Research System (CARS-13), Hong Kong Scholars Program (XJ2023012) and the Postgraduate Innovation Program of Qingdao Agricultural University (QNYCX23021).

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Ning Yan and Junfeng Cao contributed equally to this work.

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Shandong Provincial Key Laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, P.R. China

Ning Yan, Jie Wang, Xiaoxia Zou, Xiaona Yu, Xiaojun Zhang & Tong Si

School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, 999077, P.R. China

Junfeng Cao

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Junfeng Cao & Tong Si conceived the research. Ning Yan, Jie Wang, Xiaoxia Zou, Xiaona Yu and Xiaojun Zhang performed the experiments. Junfeng Cao & Tong Si analyzed data and wrote the article.

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Yan, N., Cao, J., Wang, J. et al. Seed priming with graphene oxide improves salinity tolerance and increases productivity of peanut through modulating multiple physiological processes. J Nanobiotechnol 22 , 565 (2024). https://doi.org/10.1186/s12951-024-02832-7

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Received : 19 July 2024

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DOI : https://doi.org/10.1186/s12951-024-02832-7

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