Abstract
Key message
Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant.
Abstract
Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker–trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.
Similar content being viewed by others
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48
Cao P, Liang X, Zhao H, Feng B, Xu E, Wang L, Hu Y (2019) Identification of the quantitative trait loci controlling spike-related traits in hexaploid wheat (Triticum aestivum L.). Planta 250:1967–1981
Chai L, Xin M, Dong C, Chen Z, Zhai H, Zhuang J, Cheng X, Wang N, Geng J, Wang X, Bian R, Yao Y, Guo W, Hu Z, Peng H, Bai G, Sun Q, Su Z, Liu J, Ni Z (2022) A natural variation in Ribonuclease H-like gene underlies Rht8 to confer “Green Revolution” trait in wheat. Mol Plant 15:377–380
Charmet G, Tran L, Auzanneau J, Rincent R, Bouchet S (2020) BWGS: a R package for genomic selection and its application to a wheat breeding programme. PLoS ONE 15:e222733
Chang C, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ (2015) Second-generation plink: rising to the challenge of larger and richer datasets. Gigascience 4:7
Chen ZC, Yamaji N, Fujii-Kashino M, Ma JF (2016) A cation-chloride cotransporter gene is required for cell elongation and osmoregulation in rice. Plant Physiol 171:494–507
Crossa J, Pérez-Rodríguez P, Cuevas J, Montesinos-López O, Jarquín D, de Los CG, Burgueño J, González-Camacho JM, Pérez-Elizalde S, Beyene Y, Dreisigacker S, Singh R, Zhang X, Gowda M, Roorkiwal M, Rutkoski J, Varshney RK (2017) Genomic selection in plant breeding: methods, Models, and Perspectives. Trends Plant Sci 22:961–975
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R (2011) The variant call format and vcftools. Bioinformatics 27:2156–2158
Deng Z, Cui Y, Han Q, Fang W, Li J, Tian J (2017) Discovery of consistent QTLs of wheat spike-related traits under nitrogen treatment at different development stages. Front Plant Sci 8:2120
Epskamp S, Cramer AOJ, Waldorp LJ, Schmittmann VD, Borsboom D (2012) qgraph: network visualizations of relationships in psychometric data. J Stat Softw 48:1–18
Govta N, Polda I, Sela H, Cohen Y, Beckles DM, Korol AB, Fahima T, Saranga Y, Krugman T (2022) Genome-wide association study in bread wheat identifies genomic regions associated with grain yield and quality under contrasting water availability. Int J Mol Sci 23:10575
Guan P, Lu L, Jia L, Kabir MR, Zhang J, Lan T, Zhao Y, Xin M, Hu Z, Yao Y, Ni Z, Sun Q, Peng H (2018) Global QTL analysis identifies genomic regions on chromosomes 4A and 4B harboring stable loci for yield-related traits across different environments in wheat (Triticum aestivum L.). Front Plant Sci 9:529
Guo J, Guo J, Li L, Bai X, Huo X, Shi W, Gao L, Dai K, Jing R, Hao C (2023) Combined linkage analysis and association mapping identifies genomic regions associated with yield-related and drought-tolerance traits in wheat (Triticum aestivum L.). Theor Appl Genet 136:250
Halder J, Gill HS, Zhang J, Altameemi R, Olson E, Turnipseed B, Sehgal SK (2023) Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat. Plant Genome-US 16, e20300.
Hassani-Pak K, Singh A, Brandizi M, Hearnshaw J, Parsons JD, Amberkar S, Phillips AL, Doonan JH, Rawlings C (2021) KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species. Plant Biotechnol J 19:1670–1678
Hu J, Wang X, Zhang G, Jiang P, Chen W, Hao Y, Ma X, Xu S, Jia J, Kong L, Wang H (2020) QTL mapping for yield-related traits in wheat based on four RIL populations. Theor Appl Genet 133:917–933
Huang M, Liu X, Zhou Y, Summers RM, Zhang Z (2018) BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions. GigaScience 8:giy154
Jiao C, Hao C, Li T, Bohra A, Wang L, Hou J, Liu H, Liu H, Zhao J, Wang Y, Liu Y, Wang Z, Jing X, Wang X, Varshney RK, Fu J, Zhang X (2023) Fast integration and accumulation of beneficial breeding alleles through an AB–NAMIC strategy in wheat. Plant Commun 4:100549
Kassambara A, Kassambara MA (2019) Package ‘ggcorrplot’. R package version 0.1 3:908
Khan H, Krishnappa G, Kumar S, Mishra CN, Krishna H, Devate NB, Rathan ND, Parkash O, Yadav SS, Srivastava P, Biradar S, Kumar M, Singh GP (2022) Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.). Front Genet 13:982589
Kuzay S, Xu Y, Zhang J, Katz A, Pearce S, Su Z, Fraser M, Anderson JA, Brown-Guedira G, DeWitt N, Peters Haugrud A, Faris JD, Akhunov E, Bai G, Dubcovsky J (2019) Identification of a candidate gene for a QTL for spikelet number per spike on wheat chromosome arm 7AL by high-resolution genetic mapping. Theor Appl Genet 132:2689–2705
Li J, Wang S, Yu J, Wang L, Zhou S (2013) A modified CTAB protocol for plant DNA extraction. Chinese Bull Botany 48:72
Li C, Lin H, Chen A, Lau M, Jernstedt J, Dubcovsky J (2019) Wheat VRN1, FUL2 and FUL3 play critical and redundant roles in spikelet development and spike determinacy. Development 146:dev175398
Li C, Tang H, Luo W, Zhang X, Mu Y, Deng M, Liu Y, Jiang Q, Chen G, Wang J, Qi P, Pu Z, Jiang Y, Wei Y, Zheng Y, Lan X, Ma J (2020) A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat. Theor Appl Genet 133:3381–3393
Li T, Deng G, Su Y, Yang Z, Tang Y, Wang J, Qiu X, Pu X, Li J, Liu Z, Zhang H, Liang J, Yang W, Yu M, Wei Y, Long H (2021) Identification and validation of two major QTLs for spike compactness and length in bread wheat (Triticum aestivum L.) showing pleiotropic effects on yield-related traits. Theor Appl Genet 134:3625–3641
Li A, Hao C, Wang Z, Geng S, Jia M, Wang F, Han X, Kong X, Yin L, Tao S, Deng Z, Liao R, Sun G, Wang K, Ye X, Jiao C, Lu H, Zhou Y, Liu D, Fu X, Zhang X, Mao L (2022) Wheat breeding history reveals synergistic selection of pleiotropic genomic sites for plant architecture and grain yield. Mol Plant 15:504–519
Liu J, Xu Z, Fan X, Zhou Q, Cao J, Wang F, Ji G, Yang L, Feng B, Wang T (2018) A genome-wide association study of wheat spike related traits in China. Front Plant Sci 9:1584
Miao L, Mao X, Wang J, Liu Z, Zhang B, Li W, Chang X, Reynolds M, Wang Z, Jing R (2017) Elite haplotypes of a protein kinase gene TaSnRK23 associated with important agronomic traits in common wheat. Front Plant Sci 8:368
Pang Y, Liu C, Wang D, St Amand P, Bernardo A, Li W, He F, Li L, Wang L, Yuan X, Dong L, Su Y, Zhang H, Zhao M, Liang Y, Jia H, Shen X, Lu Y, Jiang H, Wu Y, Li A, Wang H, Kong L, Bai G, Liu S (2020) High-resolution genome-wide association study identifies genomic regions and candidate genes for important agronomic traits in wheat. Mol Plant 13:1311–1327
Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8:e66428
Roth L, Fossati D, Krahenbuhl P, Walter A, Hund A (2023) Image-based phenomic prediction can provide valuable decision support in wheat breeding. Theor Appl Genet 136:162
Sakuma S, Golan G, Guo Z, Ogawa T, Tagiri A, Sugimoto K, Bernhardt N, Brassac J, Mascher M, Hensel G, Ohnishi S, Jinno H, Yamashita Y, Ayalon I, Peleg Z, Schnurbusch T, Komatsuda T (2019) Unleashing floret fertility in wheat through the mutation of a homeobox gene. P Natl Acad Sci 116:5182–5187
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideke T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504
Sentoku N, Kato H, Kitano H, Imai R (2005) OsMADS22, an STMADS11-like MADS-box gene of rice, is expressed in non-vegetative tissues and its ectopic expression induces spikelet meristem indeterminacy. Mol Genet Genom 273:1–9
Simons KJ, Fellers JP, Trick HN, Zhang Z, Tai Y, Gill BS, Faris JD (2006) Molecular Characterization of the major wheat domestication gene Q. Genetics 172:547–555
Sun L, Yang W, Li Y, Shan Q, Ye X, Wang D, Yu K, Lu W, Xin P, Pei Z, Guo X, Liu D, Sun J, Zhan K, Chu J, Zhang A (2019) A wheat dominant dwarfing line with Rht12, which reduces stem cell length and affects gibberellic acid synthesis, is a 5AL terminal deletion line. Plant J 97:887–900
Tao Y, Yi X, Lin Y, Wang Z, Wu F, Jiang X, Liu S, Deng M, Ma J, Chen G, Wei Y, Zheng Y, Liu Y (2019) Quantitative trait locus mapping for panicle exsertion length in common wheat using two related recombinant inbred line populations. Euphytica 215:1–13
Tiwari P, Indoliya Y, Singh PK, Singh PC, Chauhan PS, Pande V, Chakrabarty D (2019) Role of dehydrin-FK506-binding protein complex in enhancing drought tolerance through the ABA-mediated signaling pathway. Environ Exper Botany 158:136–149
Wang J, Zhang Z (2021) GAPIT version 3: boosting power and accuracy for genomic association and prediction. Genom Proteom Bioinf 19: 629-640
Wang D, Yu K, Jin D, Sun L, Chu J, Wu W, Xin P, Gregová E, Li X, Sun J, Yang W, Zhan K, Zhang A, Liu D (2020) Natural variations in the promoter of Awn Length Inhibitor 1 (ALI-1) are associated with awn elongation and grain length in common wheat. Plant J 101:1075–1090
Wang X, Guan P, Xin M, Wang Y, Chen X, Zhao A, Liu M, Li H, Zhang M, Lu L, Zhang J, Ni Z, Yao Y, Hu Z, Peng H, Sun Q (2021) Genome-wide association study identifies QTL for thousand grain weight in winter wheat under normal- and late-sown stressed environments. Theor Appl Genet 134:143–157
Wickham H, Chang W, Wickham MH (2016) Package ‘ggplot2’. Create Elegant Data Visualisations Using the Grammar of Graphics. Version 1:1–189
Würschum T, Leiser WL, Langer SM, Tucker MR, Longin CFH (2018) Phenotypic and genetic analysis of spike and kernel characteristics in wheat reveals long-term genetic trends of grain yield components. Theor Appl Genet 131:2071–2084
Xu H, Sun H, Dong J, Ma C, Li J, Li Z, Wang Y, Ji J, Hu X, Wu M, Zhao C, Qin R, Wu J, Ni F, Cui F, Wu Y (2022) The brassinosteroid biosynthesis gene TaD11-2A controls grain size and its elite haplotype improves wheat grain yields. Theor Appl Genet 135:2907–2923
Yang Y, Amo A, Wei D, Chai Y, Zheng J, Qiao P, Cui C, Lu S, Chen L, Hu Y (2021) Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. Theor Appl Genet 134:3083–3109
Yao FQ, Li XH, Wang H, Song YN, Li ZQ, Li XG, Gao X, Zhang XS, Bie XM (2021) Down-expression of TaPIN1s increases the tiller number and grain yield in wheat. BMC Plant Biol 21:443
Yin L, Zhang H, Tang Z, Xu J, Yin D, Zhang Z, Yuan X, Zhu M, Zhao S, Li X, Liu X (2021) rMVP: a memory-efficient, visualization-enhanced, and parallel-accelerated tool for genome-wide association study. Genom Proteom Bioinf 19: 619–628
Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14:415–421
Zhai H, Feng Z, Li J, Liu X, Xiao S, Ni Z, Sun Q (2016) QTL analysis of spike morphological traits and plant height in winter wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Front Plant Sci 7:1617
Zhang D, Hao C, Wang L, Zhang X (2012) Identifying loci influencing grain number by microsatellite screening in bread wheat (Triticum aestivum L.). Planta 236:1507–1517
Zhang B, Liu X, Xu W, Chang J, Li A, Mao X, Zhang X, Jing R (2015) Novel function of a putative MOC1 ortholog associated with spikelet number per spike in common wheat. Sci Rep-Uk 5:12211
Zhang C, Dong S, Xu J, He W, Yang T (2019) PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics 35:1786–1788
Zheng J, Liu H, Wang Y, Wang L, Chang X, Jing R, Hao C, Zhang X (2014) TEF-7A, a transcript elongation factor gene, influences yield-related traits in bread wheat (Triticum aestivum L.). J Exp Bot 65:5351–5365
Zhou Y, Conway B, Miller D, Marshall D, Cooper A, Murphy P, Chao S, Brown Guedira G, Costa J (2017) Quantitative trait loci mapping for spike characteristics in hexaploid wheat. Plant Genome 10:1–15
Zhu T, Wang L, Rimbert H, Rodriguez J, Deal K, De Oliveira R, Choulet F, Keeble-Gagnère G, Tibbits J, Rogers J, Eversole K, Appels R, Gu Y, Mascher M, Dvorak J, Luo M (2021) Optical maps refine the bread wheat Triticum aestivum cv. Chin Spring Genome Assembly Plant J 107:303–314
Funding
This work was supported by the Agricultural Variety Improvement Project of Shandong Province (Grant No. 2021LZGC013), the Shandong Provincial Fund for Excellent Young Scholars (Grant No. ZR2022YQ19), the National Natural Science Foundation of China (Grant Nos. 32072051 and 32272119), the Major Basic Research Project of Natural Science Foundation of Shandong Province, China (Grant No. ZR2019ZD16), the Youth Innovation Technology Support Planning Project for Institution of Higher Education of Shandong Province, China (Grant No. 2019KJF002), and the Innovation Project for graduate students of Ludong University (Grant No. IPGS2024-093).
Author information
Authors and Affiliations
Contributions
YW, FC, and HS designed the experiments and managed the project. HX, ZW, FW, XH, CM, HJ, CX, YG, and GD performed experiments. CZ, RQ, and DC supervised the project and provided technical assistance. YW, HX, and ZW analyzed data and wrote the manuscript. All authors have read and agreed to the final published version of the manuscript.
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Additional information
Communicated by Andreas Graner.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Xu, H., Wang, Z., Wang, F. et al. Genome-wide association study and genomic selection of spike-related traits in bread wheat. Theor Appl Genet 137, 131 (2024). https://doi.org/10.1007/s00122-024-04640-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00122-024-04640-x