Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models

Abstract Wheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by us...

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Autores principales:	Ali Muhammad, Jianguo Li, Weichen Hu, Jinsheng Yu, Shahid Ullah Khan, Muhammad Hafeez Ullah Khan, Guosheng Xie, Jibin Wang, Lingqiang Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b710f95703aa42fb964bdfa520b2d6de
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spelling	oai:doaj.org-article:b710f95703aa42fb964bdfa520b2d6de2021-12-02T16:36:11ZUncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models10.1038/s41598-021-86127-z2045-2322https://doaj.org/article/b710f95703aa42fb964bdfa520b2d6de2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86127-zhttps://doaj.org/toc/2045-2322Abstract Wheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by using Illumina iSelect 90K single nucleotide polymorphism (SNP) assay and finally 22,905 high-quality SNPs were used to perform a genome-wide association study (GWAS) for plant architectural traits employing four multi-locus GWAS (ML-GWAS) and three single-locus GWAS (SL-GWAS) models. As a result, 174 and 97 significant SNPs controlling plant architectural traits were detected by ML-GWAS and SL-GWAS methods, respectively. Among these SNP makers, 43 SNPs were consistently detected, including seven across multiple environments and 36 across multiple methods. Interestingly, five SNPs (Kukri_c34553_89, RAC875_c8121_1490, wsnp_Ex_rep_c66315_64480362, Ku_c5191_340, and tplb0049a09_1302) consistently detected across multiple environments and methods, played a role in modulating both plant height and flag leaf length. Furthermore, candidate SNPs (BS00068592_51, Kukri_c4750_452 and BS00022127_51) constantly repeated in different years and methods associated with flag leaf width and number of tillers. We also detected several SNPs (Jagger_c6772_80, RAC875_c8121_1490, BS00089954_51, Excalibur_01167_1207, and Ku_c5191_340) having common associations with more than one trait across multiple environments. By further appraising these GWAS methods, the pLARmEB and FarmCPU models outperformed in SNP detection compared to the other ML-GWAS and SL-GWAS methods, respectively. Totally, 152 candidate genes were found to be likely involved in plant growth and development. These finding will be helpful for better understanding of the genetic mechanism of architectural traits in wheat.Ali MuhammadJianguo LiWeichen HuJinsheng YuShahid Ullah KhanMuhammad Hafeez Ullah KhanGuosheng XieJibin WangLingqiang WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ali Muhammad Jianguo Li Weichen Hu Jinsheng Yu Shahid Ullah Khan Muhammad Hafeez Ullah Khan Guosheng Xie Jibin Wang Lingqiang Wang Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
description	Abstract Wheat is a major food crop worldwide. The plant architecture is a complex trait mostly influenced by plant height, tiller number, and leaf morphology. Plant height plays a crucial role in lodging and thus affects yield and grain quality. In this study, a wheat population was genotyped by using Illumina iSelect 90K single nucleotide polymorphism (SNP) assay and finally 22,905 high-quality SNPs were used to perform a genome-wide association study (GWAS) for plant architectural traits employing four multi-locus GWAS (ML-GWAS) and three single-locus GWAS (SL-GWAS) models. As a result, 174 and 97 significant SNPs controlling plant architectural traits were detected by ML-GWAS and SL-GWAS methods, respectively. Among these SNP makers, 43 SNPs were consistently detected, including seven across multiple environments and 36 across multiple methods. Interestingly, five SNPs (Kukri_c34553_89, RAC875_c8121_1490, wsnp_Ex_rep_c66315_64480362, Ku_c5191_340, and tplb0049a09_1302) consistently detected across multiple environments and methods, played a role in modulating both plant height and flag leaf length. Furthermore, candidate SNPs (BS00068592_51, Kukri_c4750_452 and BS00022127_51) constantly repeated in different years and methods associated with flag leaf width and number of tillers. We also detected several SNPs (Jagger_c6772_80, RAC875_c8121_1490, BS00089954_51, Excalibur_01167_1207, and Ku_c5191_340) having common associations with more than one trait across multiple environments. By further appraising these GWAS methods, the pLARmEB and FarmCPU models outperformed in SNP detection compared to the other ML-GWAS and SL-GWAS methods, respectively. Totally, 152 candidate genes were found to be likely involved in plant growth and development. These finding will be helpful for better understanding of the genetic mechanism of architectural traits in wheat.
format	article
author	Ali Muhammad Jianguo Li Weichen Hu Jinsheng Yu Shahid Ullah Khan Muhammad Hafeez Ullah Khan Guosheng Xie Jibin Wang Lingqiang Wang
author_facet	Ali Muhammad Jianguo Li Weichen Hu Jinsheng Yu Shahid Ullah Khan Muhammad Hafeez Ullah Khan Guosheng Xie Jibin Wang Lingqiang Wang
author_sort	Ali Muhammad
title	Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
title_short	Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
title_full	Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
title_fullStr	Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
title_full_unstemmed	Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models
title_sort	uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different gwas models
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b710f95703aa42fb964bdfa520b2d6de
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Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models

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