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Analysis of historical selection in winter wheat

KEY MESSAGE: Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. ABSTRACT: Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically...

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Autores principales: Yang, Chin Jian, Ladejobi, Olufunmilayo, Mott, Richard, Powell, Wayne, Mackay, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9482581/
https://www.ncbi.nlm.nih.gov/pubmed/35864201
http://dx.doi.org/10.1007/s00122-022-04163-3
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author Yang, Chin Jian
Ladejobi, Olufunmilayo
Mott, Richard
Powell, Wayne
Mackay, Ian
author_facet Yang, Chin Jian
Ladejobi, Olufunmilayo
Mott, Richard
Powell, Wayne
Mackay, Ian
author_sort Yang, Chin Jian
collection PubMed
description KEY MESSAGE: Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. ABSTRACT: Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-022-04163-3.
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spelling pubmed-94825812022-09-19 Analysis of historical selection in winter wheat Yang, Chin Jian Ladejobi, Olufunmilayo Mott, Richard Powell, Wayne Mackay, Ian Theor Appl Genet Original Article KEY MESSAGE: Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. ABSTRACT: Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-022-04163-3. Springer Berlin Heidelberg 2022-07-21 2022 /pmc/articles/PMC9482581/ /pubmed/35864201 http://dx.doi.org/10.1007/s00122-022-04163-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Yang, Chin Jian
Ladejobi, Olufunmilayo
Mott, Richard
Powell, Wayne
Mackay, Ian
Analysis of historical selection in winter wheat
title Analysis of historical selection in winter wheat
title_full Analysis of historical selection in winter wheat
title_fullStr Analysis of historical selection in winter wheat
title_full_unstemmed Analysis of historical selection in winter wheat
title_short Analysis of historical selection in winter wheat
title_sort analysis of historical selection in winter wheat
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9482581/
https://www.ncbi.nlm.nih.gov/pubmed/35864201
http://dx.doi.org/10.1007/s00122-022-04163-3
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