Abstract
Drought stress, which is increasing with climate change, is a serious threat to agricultural sustainability worldwide. Seed germination is an essential growth phase that ensures the successful establishment and productivity of soybean, which can lose substantial productivity in soils with water deficits. However, only limited genetic information is available about how germinating soybean seeds may exert drought tolerance. In this study, we examined the germinating seed drought-tolerance phenotypes and genotypes of a panel of 259 released Chinese soybean cultivars panel. Based on 4616 Single-Nucleotide Polymorphisms (SNPs), we conducted a mixed-linear model GWAS that identified a total of 15 SNPs associated with at least one drought-tolerance index. Notably, three of these SNPs were commonly associated with two drought-tolerance indices. Two of these SNPs are positioned upstream of genes, and 11 of them are located in or near regions where QTLs have been previously mapped by linkage analysis, five of which are drought-related. The SNPs detected in this study can both drive hypothesis-driven research to deepen our understanding of genetic basis of soybean drought tolerance at the germination stage and provide useful genetic resources that can facilitate the selection of drought stress traits via genomic-assisted selection.
Similar content being viewed by others
References
Abdel-Haleem H, Lee GJ, Boerma RH (2011) Identification of QTL for increased fibrous roots in soybean. Theor Appl Genet 122:935–946
Abdel-Haleem H, Carter TE, Purcell LC, King CA, Ries LL, Chen P, Schapaugh W, Sinclair TR, Boerma HR (2012) Mapping of quantitative trait loci for canopy-wilting trait in soybean (Glycine max L. Merr). Theor Appl Genet 125:837–846
Akond M, Liu S, Schoener L, Anderson JA, Kantartzi SK, Meksem K, Song Q, Wang D, Wen Z, Lightfoot DA, Kassem MA (2013) SNP-based genetic linkage map of soybean using the SoySNP6K Illumina Infinium BeadChip genotyping array. J Plant Genome Sci 1:80–89
Bai J, Mao J, Yang H, Khan A, Fan A, Liu S, Zhang J, Wang D, Gao H, Zhang J (2017) Sucrose non-ferment 1 related protein kinase 2 (SnRK 2) genes could mediate the stress responses in potato (Solanum tuberosum L.). BMC Genet 18:41
Boyer JS (1982) Plant productivity and environment. Science 218:443–448
Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: Software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635
Cattivelli L, Rizza F, Badeck FW, Mazzucotelli E, Mastrangelo AM, Francia E, Mare C, Tondelli A, Stanca AM (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. Field Crop Res 115:1–14
Chander S, Almeida DM, Serra TS, Jardim-Messeder D, Barros PM, Lourenço TF, Figueiredo DD, Margis-Pinheiro M, Costa JM, Oliveira MM, Saibo NJ (2018) OsICE1 transcription factor improves photosynthetic performance and reduces grain losses in rice plants subjected to drought. Environ Exp Bot 150:88–98
Charlson D, Bhatnagar S, King C, Ray J, Sneller C, Carter T, Purcell L (2009) Polygenic inheritance of canopy wilting in soybean [Glycine max (L.) Merr.]. Theor Appl Genet 119:587–594
Chen H, Shan Z, Sha A, Wu B, Yang Z, Chen S, Zhou R, Zhou X (2011) Quantitative trait loci analysis of stem strength and related traits in soybean. Euphytica 179:485–497
Chen T, Li W, Hu X, Guo J, Liu A, Zhang B (2015) A cotton MYB transcription factor, GbMYB5, is positively involved in plant adaptive response to drought stress. Plant Cell Physiol 56:917–929
Condon AG, Richards RA, Rebetzke GJ, Farquhar GD (2004) Breeding for high water-use efficiency. J Exp Bot 55:2447–2460
Csanadi G, Vollmann J, Stift G, Lelley T (2001) Seed quality QTLs identified in a molecular map of early maturing soybean. Theor Appl Genet 103:912–919
Dias FG, Borges ACN, Viana AAB, Mesquita RO, Romano E, Grossi de Sa MF, Nepomuceno AL, Loureiro ME, Ferreira MA (2012) Expression analysis in response to drought stress in soybean: shedding light on the regulation of metabolic pathway genes. Genet Mol Biol 35:222–232
Ding S, Zhang B, Qin F (2015) Arabidopsis RZFP34/CHYR1, a ubiquitin E3 ligase, regulates stomatal movement and drought tolerance via SnRK2. 6-mediated phosphorylation. Plant Cell 27:3228–3244
Dogan E, Kirnak H, Copur O (2007) Deficit irrigations during soybean reproductive stages and CROPGRO-soybean simulations under semi-arid climatic conditions. Field Crops Res 103:154–159
Dornbos DL, Mullen RE (1992) Soybean seed protein and oil contents and fatty acid composition adjustments by drought and temperature. J Am Oil Chem Soc 69:228–231
Du W, Fu S, Yu D (2009a) Genetic analysis for the leaf pubescence density and water status traits in soybean [Glycine max (L.) Merr.]. Plant Breed 128:259–265
Du W, Wang M, Fu S, Yu D (2009b) Mapping QTL for seed yield and drought susceptibility index in soybean (Glycine max L.) across different environments. J Genet Genomics 36:721–731
Du W, Yu D, Fu S (2009c) Detection of quantitative trait loci for yield and drought tolerance traits in soybean using a recombinant inbred line population. J Integr Plant Biol 51:868–878
Eskandari M, Cober E, Rajcan I (2013a) Genetic control of soybean seed oil: II. QTL and genes that increase oil concentration without decreasing protein or with increased seed yield. Theor Appl Genet 126:1677–1687
Eskandari M, Cober E, Rajcan I (2013b) Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents. Theor Appl Genet 126:403–495
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620
Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491
Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform 1:47–50
Frederick JR, Camp CR, Bauer PJ (2001) Drought-stress effects on branch and mainstem seed yield and yield components of determinate soybean. Crop Sci 41:759–763
Funatsuki H, Kawaguchi K, Matsuba S, Sato Y, Ishimoto M (2005) Mapping of QTL associated with chilling tolerance during reproductive growth in soybean. Theor Appl Genet 111:851–861
Gao F, Yao H, Zhao H, Zhou J, Luo X, Huang Y, Li C, Chen H, Wu Q (2016) Tartary buckwheat FtMYB10 encodes an R2R3-MYB transcription factor that acts as a novel negative regulator of salt and drought response in transgenic Arabidopsis. Plant Physiol Bioch 109:387–396
Ghorbel M, Cotelle V, Ebel C, Zaidi I, Ormancey M, Galaud JP, Hanin M (2017) Regulation of the wheat MAP kinase phosphatase 1 by 14-3-3 proteins. Plant Sci 257:37–47
Guo B, Sleper DA, Arelli PR, Shannon JG, Nguyen HT (2005) Identification of QTLs associated with resistance to soybean cyst nematode races 2, 3 and 5 in soybean PI 90763. Theor Appl Genet 103:1167–1173
Han Y, Li D, Zhu D, Li H, Li X, Teng W, Li W (2012) QTL analysis of soybean seed weight across multi-genetic backgrounds and environments. Theor Appl Genet 125:671–683
Han Y, Teng W, Wang Y, Zhao X, Wu L, Li D, Li W (2015) Unconditional and conditional QTL underlying the genetic interrelationships between soybean seed isoflavone, and protein or oil contents. Plant Breed 134:300–309
Hou YJ, Zhu Y, Wang P, Zhao Y, Xie S, Batelli G, Wang B, Duan CG, Wang X, Xing L, Lei M, Yan J, Zhu X, Zhu JK (2016) Type one protein phosphatase 1 and its regulatory protein inhibitor 2 negatively regulate ABA signaling. PLoS Genet 12:e1005835
Huang X, Hou L, Meng J, You H, Li Z, Gong Z, Yang S, Shi Y (2018) The antagonistic action of abscisic acid and cytokinin signaling mediates drought stress response in Arabidopsis. Mol Plant 11:970–982
Hufstetler EV, Boerma HR, Carter TE, Earl HJ (2007) Genotypic variation for three physiological traits affecting drought tolerance in soybean. Crop Sci 47:25–35
Hwang S, King CA, Ray JD, Cregan PB, Chen P, Carter TE, Li Z, Abdel-Haleem H, Matson KW, Schapaugh W, Purcell LC (2015) Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations. Theor Appl Genet 128:2047–2065
Hwang S, King CA, Chen P, Ray JD, Cregan PB, Carter TE, Li Z, Abdel-Haleem H, Matson KW, Schapaugh W, Purcell LC (2016) Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean. Mol Breeding 36:91
Hyten DL, Pantalone VR, Sams CE, Saxton AM, Landau-Ellis D, Stefaniak TR, Schmidt ME (2004) Seed quality QTL in a prominent soybean population. Theor Appl Genet 109:552–561
Jun TH, Van K, Kim MY, Lee SH, Walker DR (2008) Association analysis using SSR markers to find QTL for seed protein content in soybean. Euphytica 162:179–191
Kabelka EA, Diers BW, Fehr WR, LeRoy AR, Baianu IC, You T, Neece DJ, Nelson RL (2004) Putative alleles for increased yield from soybean plant introductions. Crop Sci 44:784–791
Kaler AS, Ray JD, Schapaugh WT, King CA, Purcell LC (2017) Genome-wide association mapping of canopy wilting in diverse soybean genotypes. Theor Appl Genet 130:2203–2217
Kisha TJ, Sneller CH, Diers BW (1997) Relationship between genetic distance among parents and genetic variance in populations of soybean. Crop Sci 37:1317–1325
Liang H, Yu Y, Wang S, Lian Y, Wang T, Wei Y, Gong P, Liu X, Fang X, Zhang M (2010) QTL mapping of isoflavone, oil and protein contents in soybean (Glycine max L. Merr.). Ag Sci China 9:1108–1116
Liao YD, Lin KH, Chen CC, Chiang CM (2016) Oryza sativa protein phosphatase 1a (OsPP1a) involved in salt stress tolerance in transgenic rice. Mol Breeding 36:22
Liu X (2009) Drought. In: Lam HM et al (ed) Research on tolerance to stresses in Chinese soyben. China Agriculture Press, Beijing
Liu KJ, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129
Liu W, Kim M, Van K, Lee Y, Li H, Liu X, Lee S (2011) QTL identification of yield-related traits and their association with flowering and maturity in soybean. J Crop Sci Biotech 14:65–70
Liu Z, Li H, Wen Z, Fan X, Li Y, Guan R, Guo Y, Wang S, Wang D, Qiu LJ (2017) Comparison of genetic diversity between Chinese and American soybean (Glycine max (L.)) accessions revealed by high-density SNPs. Front Plant Sci 8:11. https://doi.org/10.3389/fpls.2017.02014
Loiselle BA, Sork VL, Nason J, Graham C (1995) Spatial genetic structure of a tropical understory shrub, PSYCHOTRIA OFFICINALIS (Rubiaceae). Am J Bot 82:1420–1425
Lu W, Wen Z, Li H, Yuan D, Li J, Zhang H, Huang Z, Cui S, Du W (2012) Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean. Theor Appl Gen 126:425–433
Mao T, Jiang Z, Han Y, Teng W, Zhao X, Li W (2013) Identification of quantitative trait loci underlying seed protein and oil contents of soybean across multi-genetic backgrounds and environments. Plant Breed 132:630–641
Maughan PJ, Maroof MAS, Buss GR (2000) Identification of quantitative trait loci controlling sucrose content in soybean (Glycine max). Mol Breeding 6:105–111
Mederski HJ, Jeffers DL (1973) Yield response of soybean varieties grown at two soil moisture levels. Agron J 65:410–412
Meng L, Li H, Zhang L, Wang J (2015) QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J 3:269–283
Mian MAR, Bailey MA, Ashley DA, Wells R, Carter TE, Parrott WA, Boerma HR (1996) Molecular markers associated with water use efficiency and leaf ash in soybean. Crop Sci 36:1252–1257
Mian MAR, Ashley DA, Boerma HR (1998) An additional QTL for water use efficiency in soybean. Crop Sci 38:390–393
Mittler R, Blumwald E (2010) Genetic engineering for modern agriculture: challenges and perspectives. Annu Rev Plant Biol 61:443–462
Mohammadi PP, Moieni A, Hiraga S, Komatsu S (2012) Organ specific proteomic analysis of drought-stressed soybean seedlings. J Proteomics 75:1906–1923
Morison JIL, Baker NR, Mullineaux PM, Davies WJ (2008) Improving water use in crop production. Philos Trans R Soc Biol Sci 363:639–658
Oya T, Nepomuceno AL, Farias JRB, Tobita S, Ito O (2004) Drought tolerance characteristics of Brazilian soybean cultivars—evaluation and characterization of drought tolerance of various Brazilian soybean cultivars in the field. Plant Prod Sci 7:129–137
Park DY, Shim Y, Gi E, Lee BD, An G, Kang K, Paek NC (2018) The MYB-related transcription factor RADIALIS-LIKE3 (OsRL3) functions in ABA-induced leaf senescence and salt sensitivity in rice. Environ Exp Bot 156:86–95
Patterson NJ, Price AL, Reich D (2006) Population structure and eigenanalysis. PLoS Genet 2:e190
Pennisi E (2008) The blue revolution, drop by drop, gene by gene. Science 320:171–173
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Ribaut JM, Jiang C, Gonzalez-de-Leon D, Edmeades GO, Hoisington DA (1997) Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker assisted selection strategies. Theor Appl Genet 94:887–896
Rönnberg-Wästljung AC, Glynn C, Weih M (2005) QTL analyses of drought tolerance and growth for a Salix dasyclados × Salix viminalis hybrid in contrasting water regimes. Theor Appl Genet 110:537–549
SAS Institute Inc (2007) SAS/STAT software: Version 9.1.3. SAS Institute, Cary, NC
Serrano I, Campos L, Rivas S (2018) Roles of E3 ubiquitin-ligases in nuclear protein homeostasis during plant stress responses. Front Plant Sci 9:139
Sharma KK, Lavanya M (2002) Recent developments in transgenics for abiotic stress in legumes of the semi-arid tropics. In: JIRCAS Working Report. pp 61–73
Shu Y, Zhou Y, Shi X, Hu N, Shao Q, Du J (2015) Screening of appropriate PEG-6000 concentration for the identification of soybean drought tolerance at germination stage. Soybean Sci 1:56–59
Specht JE, Williams JH, Weidenbenner CJ (1986) Differential responses of soybean genotypes subjected to a seasonal soil water gradient. Crop Sci 26:922–934
Specht JE, Hume DJ, Kumudini SV (1999) Soybean yield potential—a genetic and physiological perspective. Crop Sci 39:1560–1570
Specht JE, Chase K, Macrander M, Graef GL, Chung J, Markwell JP, Germann M, Orf JH, Lark KG (2001) Soybean response to water: a QTL analysis of drought tolerance. Crop Sci 41:493–509
Tajuddin T, Watanabe S, Yamanaka N, Harada K (2003) Analysis of quantitative trait loci for protein and lipid contents in soybean seeds using recombinant inbred lines. Breed Sci 53:133–140
Takahashi Y, Kinoshita T, Matsumoto M, Shimazaki KI (2016) Inhibition of the Arabidopsis bHLH transcription factor by monomerization through abscisic acid-induced phosphorylation. Plant J 87:559–567
Teng W, Han Y, Du Y, Sun D, Zhang Z, Qiu L, Sun G, Li W (2009) QTL analyses of seed weight during the development of soybean (Glycine max L Merr). Heredity 102:372380
Thabet SG, Moursi YS, Karam MA, Graner A, Alqudah AM (2018) Genetic basis of drought tolerance during seed germination in barley. PLoS ONE 13:e0206682
Tiwari B, Kalim S, Tyagi N, Kumari R, Bangar P, Barman P, Kumar S, Gaikwad A, Bhat KV (2018) Identification of genes associated with stress tolerance in moth bean [Vigna aconitifolia (Jacq.) Marechal], a stress hardy crop. Physiol Mol Biol Pla 24:551–561
Tuberosa R, Salvi S (2006) Genomics-based approaches to improve drought tolerance of crops. Trends Plant Sci 11:405–412
Wang N, Zhang W, Qin M, Li S, Qiao M, Liu Z, Xiang F (2017) Drought tolerance conferred in soybean (Glycine max. L) by GmMYB84, a novel R2R3-MYB transcription factor. Plant Cell Physiol 58:1764–1776
Wen Z, Tan R, Yuan J, Bales C, Du W, Zhang S, Chilvers MI, Schmidt C, Song Q, Cregan PB, Wang D (2014) Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean. BMC Genomics 15:809
Xiong LM, Wang RG, Mao GH, Koczan JM (2006) Identification of drought tolerance determinants by genetic analysis of root response to drought stress and abscisic acid. Plant Physiol 142:1065–1074
Xu Z, Ge Y, Zhang W, Zhao Y, Yang G (2018) The walnut JrVHAG1 gene is involved in cadmium stress response through ABA-signal pathway and MYB transcription regulation. BMC Plant Biol 18:19
Yang Z, Xin D, Liu C, Jiang H, Han X, Sun Y, Qi Z, Hu G, Chen Q (2013) Identification of QTLs for seed and pod traits in soybean and analysis for additive effects and epistatic effects of QTLs among multiple environments. Mol Genet Genomics 288:651–667
Yao D, Liu Z, Zhang J, Liu S, Qu J, Guan S, Pan L, Wang D, Liu J, Wang P (2015) Analysis of quantitative trait loci for main plant traits in soybean. Genet Mol Res 14:6101–6109
Yuan J, Njiti VN, Meksem K, Iqbal MJ, Triwitayakorn K, Kassem MA, Davis GT, Schmidt ME, Lightfoot DA (2002) Quantitative trait loci in two soybean recombinant inbred line populations segregating for yield and disease resistance. Crop Sci 42:271–277
Zhang D, Cheng H, Wang H, Zhang H, Liu C, Yu D (2007) Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.). J Genet Genom 37:545–556
Zhang B, Chen P, Chen C, Wang D, Shi A, Hou A, Ishibashi T (2008) Quantitative trait loci mapping of seed hardness in soybean. Crop Sci 48:1341–1349
Zhao Y, Cheng X, Liu X, Wu H, Bi H, Xu H (2018) The wheat MYB transcription factor TaMYB31 is involved in drought stress responses in Arabidopsis. Front Plant Sci 9:1426
Acknowledgements
This work was supported by the National Key R & D Program for Crop Breeding (Grant No. 2016YFD0100304), the Development of Novel Elite Soybean Cultivars and Lines with High Oil Content (Grant No. Z161100000916005-06), the Crop Germplasm Resources Protection (Grant No. 2017NWB036-5), the Platform of National Crop Germplasm Resources of China (Grant Nos. 2018-004 and 2017-004), the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences (CAAS), and the Improvement of Soybean Abiotic Stress Tolerance to Address the Climate Change (Grant No. PJ0121092018).
Author information
Authors and Affiliations
Contributions
ZL, XQ, and LQ conceived and designed the experiments. ZL, ZG, YZ, XW, and HR performed the experiments. ZL, HL, ZW, BKW, YL, LY, HG, DW, XQ, and LQ analyzed data and wrote the manuscript. All authors read and approved the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have declared that no competing interests exist.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of authors.
Additional information
Communicated by Stefan Hohmann.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Liu, Z., Li, H., Gou, Z. et al. Genome-wide association study of soybean seed germination under drought stress. Mol Genet Genomics 295, 661–673 (2020). https://doi.org/10.1007/s00438-020-01646-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00438-020-01646-0