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Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea
Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP ar...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7522997/ https://www.ncbi.nlm.nih.gov/pubmed/32985526 http://dx.doi.org/10.1038/s41598-020-72548-9 |
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author | Klein, Anthony Houtin, Hervé Rond-Coissieux, Céline Naudet-Huart, Myriam Touratier, Michael Marget, Pascal Burstin, Judith |
author_facet | Klein, Anthony Houtin, Hervé Rond-Coissieux, Céline Naudet-Huart, Myriam Touratier, Michael Marget, Pascal Burstin, Judith |
author_sort | Klein, Anthony |
collection | PubMed |
description | Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms. |
format | Online Article Text |
id | pubmed-7522997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75229972020-09-29 Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea Klein, Anthony Houtin, Hervé Rond-Coissieux, Céline Naudet-Huart, Myriam Touratier, Michael Marget, Pascal Burstin, Judith Sci Rep Article Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms. Nature Publishing Group UK 2020-09-28 /pmc/articles/PMC7522997/ /pubmed/32985526 http://dx.doi.org/10.1038/s41598-020-72548-9 Text en © The Author(s) 2020 Open Access This 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/. |
spellingShingle | Article Klein, Anthony Houtin, Hervé Rond-Coissieux, Céline Naudet-Huart, Myriam Touratier, Michael Marget, Pascal Burstin, Judith Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title | Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title_full | Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title_fullStr | Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title_full_unstemmed | Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title_short | Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea |
title_sort | meta-analysis of qtl reveals the genetic control of yield-related traits and seed protein content in pea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7522997/ https://www.ncbi.nlm.nih.gov/pubmed/32985526 http://dx.doi.org/10.1038/s41598-020-72548-9 |
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