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Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phe...

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Autores principales: White, Jon, Sharma, Rajiv, Balding, David, Cockram, James, Mackay, Ian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314726/
https://www.ncbi.nlm.nih.gov/pubmed/35915786
http://dx.doi.org/10.1002/csc2.20692
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author White, Jon
Sharma, Rajiv
Balding, David
Cockram, James
Mackay, Ian J.
author_facet White, Jon
Sharma, Rajiv
Balding, David
Cockram, James
Mackay, Ian J.
author_sort White, Jon
collection PubMed
description Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R(2) ≥ .5 with the same QTL. Genome‐wide association studies identified marker‐trait associations for all four traits. For HFN (h (2 )= .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h (2 )= 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h (2 )= 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.
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spelling pubmed-93147262022-07-30 Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat White, Jon Sharma, Rajiv Balding, David Cockram, James Mackay, Ian J. Crop Sci ORIGINAL RESEARCH ARTICLES Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R(2) ≥ .5 with the same QTL. Genome‐wide association studies identified marker‐trait associations for all four traits. For HFN (h (2 )= .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h (2 )= 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h (2 )= 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement. John Wiley and Sons Inc. 2022-03-04 2022 /pmc/articles/PMC9314726/ /pubmed/35915786 http://dx.doi.org/10.1002/csc2.20692 Text en © 2022 The Authors. Crop Science published by Wiley Periodicals LLC on behalf of Crop Science Society of America. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle ORIGINAL RESEARCH ARTICLES
White, Jon
Sharma, Rajiv
Balding, David
Cockram, James
Mackay, Ian J.
Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title_full Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title_fullStr Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title_full_unstemmed Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title_short Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
title_sort genome‐wide association mapping of hagberg falling number, protein content, test weight, and grain yield in u.k. wheat
topic ORIGINAL RESEARCH ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314726/
https://www.ncbi.nlm.nih.gov/pubmed/35915786
http://dx.doi.org/10.1002/csc2.20692
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