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Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights
Plants produce a variety of metabolites that have a critical role in growth and development. Here we present a comprehensive study of maize metabolism, combining genetic, metabolite and expression profiling methodologies to dissect the genetic basis of metabolic diversity in maize kernels. We quanti...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959190/ https://www.ncbi.nlm.nih.gov/pubmed/24633423 http://dx.doi.org/10.1038/ncomms4438 |
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author | Wen, Weiwei Li, Dong Li, Xiang Gao, Yanqiang Li, Wenqiang Li, Huihui Liu, Jie Liu, Haijun Chen, Wei Luo, Jie Yan, Jianbing |
author_facet | Wen, Weiwei Li, Dong Li, Xiang Gao, Yanqiang Li, Wenqiang Li, Huihui Liu, Jie Liu, Haijun Chen, Wei Luo, Jie Yan, Jianbing |
author_sort | Wen, Weiwei |
collection | PubMed |
description | Plants produce a variety of metabolites that have a critical role in growth and development. Here we present a comprehensive study of maize metabolism, combining genetic, metabolite and expression profiling methodologies to dissect the genetic basis of metabolic diversity in maize kernels. We quantify 983 metabolite features in 702 maize genotypes planted at multiple locations. We identify 1,459 significant locus–trait associations (P≤1.8 × 10(−6)) across three environments through metabolite-based genome-wide association mapping. Most (58.5%) of the identified loci are supported by expression QTLs, and some (14.7%) are validated through linkage mapping. Re-sequencing and candidate gene association analysis identifies potential causal variants for five candidate genes involved in metabolic traits. Two of these genes were further validated by mutant and transgenic analysis. Metabolite features associated with kernel weight could be used as biomarkers to facilitate genetic improvement of maize. |
format | Online Article Text |
id | pubmed-3959190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-39591902014-03-20 Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights Wen, Weiwei Li, Dong Li, Xiang Gao, Yanqiang Li, Wenqiang Li, Huihui Liu, Jie Liu, Haijun Chen, Wei Luo, Jie Yan, Jianbing Nat Commun Article Plants produce a variety of metabolites that have a critical role in growth and development. Here we present a comprehensive study of maize metabolism, combining genetic, metabolite and expression profiling methodologies to dissect the genetic basis of metabolic diversity in maize kernels. We quantify 983 metabolite features in 702 maize genotypes planted at multiple locations. We identify 1,459 significant locus–trait associations (P≤1.8 × 10(−6)) across three environments through metabolite-based genome-wide association mapping. Most (58.5%) of the identified loci are supported by expression QTLs, and some (14.7%) are validated through linkage mapping. Re-sequencing and candidate gene association analysis identifies potential causal variants for five candidate genes involved in metabolic traits. Two of these genes were further validated by mutant and transgenic analysis. Metabolite features associated with kernel weight could be used as biomarkers to facilitate genetic improvement of maize. Nature Pub. Group 2014-03-17 /pmc/articles/PMC3959190/ /pubmed/24633423 http://dx.doi.org/10.1038/ncomms4438 Text en Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ |
spellingShingle | Article Wen, Weiwei Li, Dong Li, Xiang Gao, Yanqiang Li, Wenqiang Li, Huihui Liu, Jie Liu, Haijun Chen, Wei Luo, Jie Yan, Jianbing Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title | Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title_full | Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title_fullStr | Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title_full_unstemmed | Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title_short | Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
title_sort | metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959190/ https://www.ncbi.nlm.nih.gov/pubmed/24633423 http://dx.doi.org/10.1038/ncomms4438 |
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