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Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping

Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing...

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Autores principales: Chen, Lin, An, Yixin, Li, Yong-xiang, Li, Chunhui, Shi, Yunsu, Song, Yanchun, Zhang, Dengfeng, Wang, Tianyu, Li, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744402/
https://www.ncbi.nlm.nih.gov/pubmed/29312420
http://dx.doi.org/10.3389/fpls.2017.02190
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author Chen, Lin
An, Yixin
Li, Yong-xiang
Li, Chunhui
Shi, Yunsu
Song, Yanchun
Zhang, Dengfeng
Wang, Tianyu
Li, Yu
author_facet Chen, Lin
An, Yixin
Li, Yong-xiang
Li, Chunhui
Shi, Yunsu
Song, Yanchun
Zhang, Dengfeng
Wang, Tianyu
Li, Yu
author_sort Chen, Lin
collection PubMed
description Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci.
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spelling pubmed-57444022018-01-08 Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping Chen, Lin An, Yixin Li, Yong-xiang Li, Chunhui Shi, Yunsu Song, Yanchun Zhang, Dengfeng Wang, Tianyu Li, Yu Front Plant Sci Plant Science Maize grain yield and related traits are complex and are controlled by a large number of genes of small effect or quantitative trait loci (QTL). Over the years, a large number of yield-related QTLs have been identified in maize and deposited in public databases. However, integrating and re-analyzing these data and mining candidate loci for yield-related traits has become a major issue in maize. In this study, we collected information on QTLs conferring maize yield-related traits from 33 published studies. Then, 999 of these QTLs were iteratively projected and subjected to meta-analysis to obtain metaQTLs (MQTLs). A total of 76 MQTLs were found across the maize genome. Based on a comparative genomics strategy, several maize orthologs of rice yield-related genes were identified in these MQTL regions. Furthermore, three potential candidate genes (Gene ID: GRMZM2G359974, GRMZM2G301884, and GRMZM2G083894) associated with kernel size and weight within three MQTL regions were identified using regional association mapping, based on the results of the meta-analysis. This strategy, combining MQTL analysis and regional association mapping, is helpful for functional marker development and rapid identification of candidate genes or loci. Frontiers Media S.A. 2017-12-22 /pmc/articles/PMC5744402/ /pubmed/29312420 http://dx.doi.org/10.3389/fpls.2017.02190 Text en Copyright © 2017 Chen, An, Li, Li, Shi, Song, Zhang, Wang and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Chen, Lin
An, Yixin
Li, Yong-xiang
Li, Chunhui
Shi, Yunsu
Song, Yanchun
Zhang, Dengfeng
Wang, Tianyu
Li, Yu
Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title_full Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title_fullStr Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title_full_unstemmed Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title_short Candidate Loci for Yield-Related Traits in Maize Revealed by a Combination of MetaQTL Analysis and Regional Association Mapping
title_sort candidate loci for yield-related traits in maize revealed by a combination of metaqtl analysis and regional association mapping
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744402/
https://www.ncbi.nlm.nih.gov/pubmed/29312420
http://dx.doi.org/10.3389/fpls.2017.02190
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