Genome-Wide Association Study of Yield Traits in Drought-Stressed Wheat Populations

Authors

  • Marco Peeters Department of Biomedical and Health Sciences, Meuse Institute of Computational Biology, Belgium Author
  • Etienne Lefevre Department of Environmental and Agricultural Sciences, Meuse Institute of Computational Biology, Belgium Author
  • Nils Georgiou Department of Microbiology and Immunology, Nordic Institute of Environmental Biotechnology, Finland Author

DOI:

https://doi.org/10.5281/zenodo.22688072

Keywords:

genome-wide association study, wheat, drought stress, grain yield, single nucleotide polymorphism, Triticum aestivum

Abstract

Grain yield stability under water-limited conditions is among the most agronomically important yet genetically
complex traits in bread wheat (Triticum aestivum L.), shaped by numerous loci of individually modest effect that
interact with developmental stage and severity of water deficit. We conducted a genome-wide association study of
grain yield, thousand-kernel weight, grain number per spike and canopy temperature depression in a panel of 287
spring bread wheat accessions drawn from breeding programmes across southern and central Europe,
phenotyped across three seasons under both well-watered and managed post-anthesis drought-stress irrigation
regimes at a single field site. Accessions were genotyped with a 25K single-nucleotide-polymorphism array,
yielding 18,942 polymorphic, quality-filtered markers after linkage-disequilibrium pruning. Mixed-linear-model
association analysis, correcting for population structure and kinship, identified 23 quantitative trait loci significantly
associated with at least one measured trait under drought stress at a Bonferroni-corrected threshold, of which 14
were drought-specific, showing no significant association with the same trait under well-watered conditions. Two
loci on chromosomes 2B and 6A jointly explained 18.3% of phenotypic variance in drought-stressed grain yield
and co-localised with previously reported quantitative trait loci for stay-green and canopy temperature depression,
while a novel locus on chromosome 4D, not previously reported in the wheat drought literature, was associated
with grain number per spike specifically under drought and explained a further 7.6% of trait variance. Candidate
gene analysis within the 4D locus interval identified an ABA-responsive transcription factor homologue as the most
plausible causal candidate. These findings identify both previously validated and novel genomic regions for
marker-assisted selection of drought-resilient yield in bread wheat breeding programmes.

References

Shiferaw B, Smale M, Braun HJ, Duveiller E, Reynolds M, Muricho G (2013) Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Security 5:291-317. https://doi.org/10.1007/s12571-013-0263-y

Lobell DB, Schlenker W, Costa-Roberts J (2011) Climate trends and global crop production since 1980. Science 333(6042):616-620. https://doi.org/10.1126/science.1204531

Farooq M, Wahid A, Kobayashi N, Fujita D, Basra SMA (2009) Plant drought stress: effects, mechanisms and management. Agronomy for Sustainable Development 29:185-212. https://doi.org/10.1051/agro:2008021

Reynolds M, Foulkes MJ, Slafer GA, Berry P, Angus WJ, Bindraban PS, Braun HJ, Calderini D, Emrich K, Foulkes J, Griffiths S (2009) Raising yield potential in wheat. Journal of Experimental Botany 60(7):1899-1918. https://doi.org/10.1093/jxb/erp016

Huang X, Han B (2014) Natural variations and genome-wide association studies in crop plants. Annual Review of Plant Biology 65:531-551. https://doi.org/10.1146/annurev-arplant-050213-035715

Korte A, Farlow A (2013) The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9:29. https://doi.org/10.1186/1746-4811-9-29

Gupta PK, Kulwal PL, Jaiswal V (2014) Association mapping in crop plants: opportunities and challenges. Advances in Genetics 85:109-147. https://doi.org/10.1016/B978-0-12-800271-1.00002-0

Pinto RS, Reynolds MP, Mathews KL, McIntyre CL, Olivares-Villegas JJ, Chapman SC (2010) Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theoretical and Applied Genetics 121:1001-1021. https://doi.org/10.1007/s00122-010-1351-4

Maulana F, Ayalew H, Anderson JD, Kumssa TT, Huang W, Ma XF (2018) Genome-wide association mapping of seedling heat tolerance in winter wheat. Frontiers in Plant Science 9:1272. https://doi.org/10.3389/fpls.2018.01272

Merida-Garcia R, Bentley AR, Gogna A, Aguilar C, Cantalapiedra CP, Contreras-Moreira B, Igartua E, Casas AM (2020) Multi-parent advanced generation intercross population reveals loci for drought-related traits in durum wheat. Frontiers in Plant Science 11:991. https://doi.org/10.3389/fpls.2020.00991

Lopes MS, Reynolds MP, McIntyre CL, Mathews KL, Jalal Kamali MR, Mossad M, Feltaous Y, Tahir ISA, Chatrath R, Ogbonnaya F, Baum M (2013) QTL for yield and associated traits in the Seri/Babax population grown across several environments in Mexico, in the West Asia, North Africa, and South Asia regions. Theoretical and Applied Genetics 126:971-984. https://doi.org/10.1007/s00122-012-2030-4

Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM (2014) Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnology Journal 12(6):787-796. https://doi.org/10.1111/pbi.12183

Winfield MO, Allen AM, Burridge AJ, Barker GLA, Benbow HR, Wilkinson PA, Coghill J, Waterfall C, Davassi A, Scopes G, Pirani A (2016) High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pools. Plant Biotechnology Journal 14(5):1195-1206. https://doi.org/10.1111/pbi.12485

Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1(1):5-20. https://doi.org/10.3835/plantgenome2008.02.0089

Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38(2):203-208. https://doi.org/10.1038/ng1702

VanRaden PM (2008) Efficient methods to compute genomic predictions. Journal of Dairy Science 91(11):4414-4423. https://doi.org/10.3168/jds.2007-0980

Lipka AE, Tian F, Wang Q, Peiffer J, Li M, Bradbury PJ, Gore MA, Buckler ES, Zhang Z (2012) GAPIT: genome association and prediction integrated tool. Bioinformatics 28(18):2397-2399. https://doi.org/10.1093/bioinformatics/bts444

Appels R, Eversole K, Feuillet C, Keller B, Rogers J, Stein N, Pozniak CJ, Choulet F, Distelfeld A, Poland J, Ronen G (2018) Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 361(6403):eaar7191. https://doi.org/10.1126/science.aar7191

Zhu X, Leiser WL, Hahn V, Wurschum T (2020) Identification of QTL for canopy temperature depression and its association with yield in a wheat mapping population under drought stress. BMC Genetics 21:66. https://doi.org/10.1186/s12863-020-00877-z

Rebetzke GJ, Rattey AR, Farquhar GD, Richards RA, Condon AG (2013) Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat. Functional Plant Biology 40(1):14-33. https://doi.org/10.1071/FP12184

Bogard M, Jourdan M, Allard V, Martre P, Perretant MR, Ravel C, Heumez E, Orford S, Snape J, Griffiths S, Gaju O (2011) Anthesis date mainly explained correlations between post-anthesis leaf senescence, grain yield, and grain protein content in a winter wheat population segregating for flowering time QTLs. Journal of Experimental Botany 62(10):3621-3636. https://doi.org/10.1093/jxb/err061

Christopher J, Christopher M, Jennings R, Jones S, Fletcher S, Borrell A, Manschadi AM, Jordan D, Mace E, Hammer G (2013) QTL for stay-green traits in wheat cultivars Drysdale and Hartog under rain-fed and irrigated conditions. Molecular Breeding 31:883-897. https://doi.org/10.1007/s11032-013-9843-5

Kadam NN, Struik PC, Rebolledo MC, Yin X, Jagadish SVK (2018) Genome-wide association reveals novel genomic loci controlling rice grain yield and its component traits under water-deficit stress during the reproductive stage. Journal of Experimental Botany 69(15):4045-4066. https://doi.org/10.1093/jxb/ery209

Lopez-Cruz M, Olson E, Rovere G, Crossa J, Dreisigacker S, Mondal S, Singh R, de los Campos G (2020) Regularized selection indices for breeding value prediction using hyper-spectral image data. Scientific Reports 10:8195. https://doi.org/10.1038/s41598-020-65011-2

Sukumaran S, Reynolds MP, Sansaloni C (2018) Genome-wide association analyses identify QTL hotspots for yield and component traits in durum wheat grown under yield potential, drought, and heat stress environments. Frontiers in Plant Science 9:81. https://doi.org/10.3389/fpls.2018.00081

Edae EA, Byrne PF, Haley SD, Lopes MS, Reynolds MP (2014) Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes. Theoretical and Applied Genetics 127:791-807. https://doi.org/10.1007/s00122-013-2257-8

Mwadzingeni L, Shimelis H, Rees DJG, Tsilo TJ (2017) Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions. PLoS ONE 12(2):e0171692. https://doi.org/10.1371/journal.pone.0171692

Ballesta P, Mora F, del Pozo A (2020) Association mapping of drought tolerance indices in wheat: QTL and genomic prediction analyses using DArT markers. Functional Plant Biology 47(2):163-177. https://doi.org/10.1071/FP19067

Barnabas B, Jager K, Feher A (2008) The effect of drought and heat stress on reproductive processes in cereals. Plant, Cell & Environment 31(1):11-38. https://doi.org/10.1111/j.1365-3040.2007.01727.x

Ji X, Shiran B, Wan J, Lewis DC, Jenkins CL, Condon AG, Richards RA, Dolferus R (2010) Importance of pre-anthesis anther sink strength for maintenance of grain number during reproductive stage water stress in wheat. Plant, Cell & Environment 33(6):926-942. https://doi.org/10.1111/j.1365-3040.2010.02130.x

Licausi F, Ohme-Takagi M, Perata P (2013) APETALA2/Ethylene Responsive Factor (AP2/ERF) transcription factors: mediators of stress responses and developmental programs. New Phytologist 199(3):639-649. https://doi.org/10.1111/nph.12291

Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K (2012) AP2/ERF family transcription factors in plant abiotic stress responses. Biochimica et Biophysica Acta 1819(2):86-96. https://doi.org/10.1016/j.bbagrm.2011.08.004

Nakashima K, Takasaki H, Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K (2012) NAC transcription factors in plant abiotic stress responses. Biochimica et Biophysica Acta 1819(2):97-103. https://doi.org/10.1016/j.bbagrm.2011.10.005

Ravikumar G, Manimaran P, Voleti SR, Subrahmanyam D, Sundaram RM, Bansal KC, Viraktamath BC, Balachandran SM (2014) Stress-inducible expression of AtDREB1A transcription factor greatly improves drought stress tolerance in transgenic indica rice. Transgenic Research 23:421-439. https://doi.org/10.1007/s11248-013-9776-6

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 Crops Research 105(1-2):1-14. https://doi.org/10.1016/j.fcr.2007.07.004

Tuberosa R (2012) Phenotyping for drought tolerance of crops in the genomics era. Frontiers in Physiology 3:347. https://doi.org/10.3389/fphys.2012.00347

Araus JL, Slafer GA, Reynolds MP, Royo C (2002) Plant breeding and drought in C3 cereals: what should we breed for? Annals of Botany 89(7):925-940. https://doi.org/10.1093/aob/mcf049

Passioura J (2007) The drought environment: physical, biological and agricultural perspectives. Journal of Experimental Botany 58(2):113-117. https://doi.org/10.1093/jxb/erl212

Blum A (2011) Plant breeding for water-limited environments. Springer, New York. https://doi.org/10.1007/978-1-4419-7491-4

Fischer RA, Rebetzke GJ (2018) Indirect selection for potential yield in early-generation, spaced plantings of wheat and other small-grain cereals: a review. Crop and Pasture Science 69(5):439-459. https://doi.org/10.1071/CP17409

Poland JA, Rife TW (2012) Genotyping-by-sequencing for plant breeding and genetics. Plant Genome 5(3):92-102. https://doi.org/10.3835/plantgenome2012.05.0005

Voss-Fels KP, Cooper M, Hayes BJ (2019) Accelerating crop genetic gains with genomic selection. Theoretical and Applied Genetics 132:669-686. https://doi.org/10.1007/s00122-018-3270-8

Crossa J, Perez-Rodriguez P, Cuevas J, Montesinos-Lopez O, Jarquin D, de los Campos G, Burgueno J, Gonzalez-Camacho JM, Perez-Elizalde S, Beyene Y, Dreisigacker S (2017) Genomic selection in plant breeding: methods, models, and perspectives. Trends in Plant Science 22(11):961-975. https://doi.org/10.1016/j.tplants.2017.08.011

Langridge P, Reynolds M (2021) Breeding for drought and heat tolerance in wheat. Theoretical and Applied Genetics 134:1753-1769. https://doi.org/10.1007/s00122-021-03795-1

Collins NC, Tardieu F, Tuberosa R (2008) Quantitative trait loci and crop performance under abiotic stress: where do we stand? Plant Physiology 147(2):469-486. https://doi.org/10.1104/pp.108.118117

Zhu JK (2016) Abiotic stress signaling and responses in plants. Cell 167(2):313-324. https://doi.org/10.1016/j.cell.2016.08.029

Butler EE, Mueller ND, Huybers P (2018) Peculiarly pleasant weather for US maize. PNAS 115(47):11935-11940. https://doi.org/10.1073/pnas.1808035115

Sallam A, Alqudah AM, Dawood MFA, Baenziger PS, Borner A (2019) Drought stress tolerance in wheat and barley: advances in physiology, breeding and genetics research. International Journal of Molecular Sciences 20(13):3137. https://doi.org/10.3390/ijms20133137

Alexander DH, Novembre J, Lange K (2009) Fast model-based estimation of ancestry in unrelated individuals. Genome Research 19(9):1655-1664. https://doi.org/10.1101/gr.094052.109

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Published

2024-12-01