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Genetic architecture of grain yield in bread wheat based on genome-wide association studies

BACKGROUND: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieti...

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Autores principales: Li, Faji, Wen, Weie, Liu, Jindong, Zhang, Yong, Cao, Shuanghe, He, Zhonghu, Rasheed, Awais, Jin, Hui, Zhang, Chi, Yan, Jun, Zhang, Pingzhi, Wan, Yingxiu, Xia, Xianchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489268/
https://www.ncbi.nlm.nih.gov/pubmed/31035920
http://dx.doi.org/10.1186/s12870-019-1781-3
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author Li, Faji
Wen, Weie
Liu, Jindong
Zhang, Yong
Cao, Shuanghe
He, Zhonghu
Rasheed, Awais
Jin, Hui
Zhang, Chi
Yan, Jun
Zhang, Pingzhi
Wan, Yingxiu
Xia, Xianchun
author_facet Li, Faji
Wen, Weie
Liu, Jindong
Zhang, Yong
Cao, Shuanghe
He, Zhonghu
Rasheed, Awais
Jin, Hui
Zhang, Chi
Yan, Jun
Zhang, Pingzhi
Wan, Yingxiu
Xia, Xianchun
author_sort Li, Faji
collection PubMed
description BACKGROUND: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. RESULTS: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4–725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. CONCLUSIONS: The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12870-019-1781-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-64892682019-06-05 Genetic architecture of grain yield in bread wheat based on genome-wide association studies Li, Faji Wen, Weie Liu, Jindong Zhang, Yong Cao, Shuanghe He, Zhonghu Rasheed, Awais Jin, Hui Zhang, Chi Yan, Jun Zhang, Pingzhi Wan, Yingxiu Xia, Xianchun BMC Plant Biol Research Article BACKGROUND: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. RESULTS: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4–725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. CONCLUSIONS: The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12870-019-1781-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-29 /pmc/articles/PMC6489268/ /pubmed/31035920 http://dx.doi.org/10.1186/s12870-019-1781-3 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Li, Faji
Wen, Weie
Liu, Jindong
Zhang, Yong
Cao, Shuanghe
He, Zhonghu
Rasheed, Awais
Jin, Hui
Zhang, Chi
Yan, Jun
Zhang, Pingzhi
Wan, Yingxiu
Xia, Xianchun
Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title_full Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title_fullStr Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title_full_unstemmed Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title_short Genetic architecture of grain yield in bread wheat based on genome-wide association studies
title_sort genetic architecture of grain yield in bread wheat based on genome-wide association studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489268/
https://www.ncbi.nlm.nih.gov/pubmed/31035920
http://dx.doi.org/10.1186/s12870-019-1781-3
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