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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2017
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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. |
format | Online Article Text |
id | pubmed-5744402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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