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Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population

BACKGROUND: Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across...

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Autores principales: Chen, Weiguo, Sun, Daizhen, Li, Runzhi, Wang, Shuguang, Shi, Yugang, Zhang, Wenjun, Jing, Ruilian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296640/
https://www.ncbi.nlm.nih.gov/pubmed/32539793
http://dx.doi.org/10.1186/s12870-020-02488-z
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author Chen, Weiguo
Sun, Daizhen
Li, Runzhi
Wang, Shuguang
Shi, Yugang
Zhang, Wenjun
Jing, Ruilian
author_facet Chen, Weiguo
Sun, Daizhen
Li, Runzhi
Wang, Shuguang
Shi, Yugang
Zhang, Wenjun
Jing, Ruilian
author_sort Chen, Weiguo
collection PubMed
description BACKGROUND: Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years. RESULTS: In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments (drought stressed and well-watered) for 5 years. In total, 44 additive QTLs for the above agronomic traits were detected on 15 chromosomes. Among these, qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A were detected across seven, six, five, five and four environments, respectively. The means in the phenotypic variation explained by these five QTLs were 12.26, 9.51, 7.77, 7.23, and 8.49%, respectively. CONCLUSIONS: We identified five stable QTLs, which includes qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A. They play a critical role in wheat agronomic traits. One of the dwarf genes Rht14, Rht16, Rht18 and Rht25 on chromosome 6A might be the candidate gene for qPH-6A. The qHD-1A and qHD-2D were novel stable QTLs for heading date and they differed from known vernalization genes, photoperiod genes and earliness per se genes.
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spelling pubmed-72966402020-06-16 Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population Chen, Weiguo Sun, Daizhen Li, Runzhi Wang, Shuguang Shi, Yugang Zhang, Wenjun Jing, Ruilian BMC Plant Biol Research Article BACKGROUND: Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years. RESULTS: In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments (drought stressed and well-watered) for 5 years. In total, 44 additive QTLs for the above agronomic traits were detected on 15 chromosomes. Among these, qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A were detected across seven, six, five, five and four environments, respectively. The means in the phenotypic variation explained by these five QTLs were 12.26, 9.51, 7.77, 7.23, and 8.49%, respectively. CONCLUSIONS: We identified five stable QTLs, which includes qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A. They play a critical role in wheat agronomic traits. One of the dwarf genes Rht14, Rht16, Rht18 and Rht25 on chromosome 6A might be the candidate gene for qPH-6A. The qHD-1A and qHD-2D were novel stable QTLs for heading date and they differed from known vernalization genes, photoperiod genes and earliness per se genes. BioMed Central 2020-06-15 /pmc/articles/PMC7296640/ /pubmed/32539793 http://dx.doi.org/10.1186/s12870-020-02488-z Text en © The Author(s) 2020 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/. 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 in a credit line to the data.
spellingShingle Research Article
Chen, Weiguo
Sun, Daizhen
Li, Runzhi
Wang, Shuguang
Shi, Yugang
Zhang, Wenjun
Jing, Ruilian
Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title_full Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title_fullStr Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title_full_unstemmed Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title_short Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population
title_sort mining the stable quantitative trait loci for agronomic traits in wheat (triticum aestivum l.) based on an introgression line population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296640/
https://www.ncbi.nlm.nih.gov/pubmed/32539793
http://dx.doi.org/10.1186/s12870-020-02488-z
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