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Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat

Genome-wide association studies (GWAS) have been widely used to dissect the complex biosynthetic processes of plant metabolome. Most studies have used single-locus GWAS approaches, such as mixed linear model (MLM), and little is known about more efficient algorithms to implement multi-locus GWAS. He...

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Autores principales: Peng, Yanchun, Liu, Hongbo, Chen, Jie, Shi, Taotao, Zhang, Chi, Sun, Dongfa, He, Zhonghu, Hao, Yuanfeng, Chen, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103272/
https://www.ncbi.nlm.nih.gov/pubmed/30154817
http://dx.doi.org/10.3389/fpls.2018.01196
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author Peng, Yanchun
Liu, Hongbo
Chen, Jie
Shi, Taotao
Zhang, Chi
Sun, Dongfa
He, Zhonghu
Hao, Yuanfeng
Chen, Wei
author_facet Peng, Yanchun
Liu, Hongbo
Chen, Jie
Shi, Taotao
Zhang, Chi
Sun, Dongfa
He, Zhonghu
Hao, Yuanfeng
Chen, Wei
author_sort Peng, Yanchun
collection PubMed
description Genome-wide association studies (GWAS) have been widely used to dissect the complex biosynthetic processes of plant metabolome. Most studies have used single-locus GWAS approaches, such as mixed linear model (MLM), and little is known about more efficient algorithms to implement multi-locus GWAS. Here, we report a comprehensive GWAS of 20 free amino acid (FAA) levels in kernels of bread wheat (Triticum aestivum L.) based on 14,646 SNPs by six multi-locus models (FASTmrEMMA, FASTmrMLM, ISISEM-BLASSO, mrMLM, pKWmEB, and pLARmEB). Our results showed that 328 significant quantitative trait nucleotides (QTNs) were identified in total (38, 8, 92, 45, 117, and 28, respectively, for the above six models). Among them, 66 were repeatedly detected by more than two models, and 155 QTNs appeared only in one model, indicating the reliability and complementarity of these models. We also found that the number of significant QTNs for different FAAs varied from 8 to 41, which revealed the complexity of the genetic regulation of metabolism, and further demonstrated the necessity of the multi-locus GWAS. Around these significant QTNs, 15 candidate genes were found to be involved in FAA biosynthesis, and one candidate gene (TraesCS1D01G052500, annotated as tryptophan decarboxylase) was functionally identified to influence the content of tryptamine in vitro. Our study demonstrated the power and efficiency of multi-locus GWAS models in crop metabolome research and provided new insights into understanding FAA biosynthesis in wheat.
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spelling pubmed-61032722018-08-28 Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat Peng, Yanchun Liu, Hongbo Chen, Jie Shi, Taotao Zhang, Chi Sun, Dongfa He, Zhonghu Hao, Yuanfeng Chen, Wei Front Plant Sci Plant Science Genome-wide association studies (GWAS) have been widely used to dissect the complex biosynthetic processes of plant metabolome. Most studies have used single-locus GWAS approaches, such as mixed linear model (MLM), and little is known about more efficient algorithms to implement multi-locus GWAS. Here, we report a comprehensive GWAS of 20 free amino acid (FAA) levels in kernels of bread wheat (Triticum aestivum L.) based on 14,646 SNPs by six multi-locus models (FASTmrEMMA, FASTmrMLM, ISISEM-BLASSO, mrMLM, pKWmEB, and pLARmEB). Our results showed that 328 significant quantitative trait nucleotides (QTNs) were identified in total (38, 8, 92, 45, 117, and 28, respectively, for the above six models). Among them, 66 were repeatedly detected by more than two models, and 155 QTNs appeared only in one model, indicating the reliability and complementarity of these models. We also found that the number of significant QTNs for different FAAs varied from 8 to 41, which revealed the complexity of the genetic regulation of metabolism, and further demonstrated the necessity of the multi-locus GWAS. Around these significant QTNs, 15 candidate genes were found to be involved in FAA biosynthesis, and one candidate gene (TraesCS1D01G052500, annotated as tryptophan decarboxylase) was functionally identified to influence the content of tryptamine in vitro. Our study demonstrated the power and efficiency of multi-locus GWAS models in crop metabolome research and provided new insights into understanding FAA biosynthesis in wheat. Frontiers Media S.A. 2018-08-14 /pmc/articles/PMC6103272/ /pubmed/30154817 http://dx.doi.org/10.3389/fpls.2018.01196 Text en Copyright © 2018 Peng, Liu, Chen, Shi, Zhang, Sun, He, Hao and Chen. 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) and the copyright owner(s) 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
Peng, Yanchun
Liu, Hongbo
Chen, Jie
Shi, Taotao
Zhang, Chi
Sun, Dongfa
He, Zhonghu
Hao, Yuanfeng
Chen, Wei
Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title_full Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title_fullStr Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title_full_unstemmed Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title_short Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat
title_sort genome-wide association studies of free amino acid levels by six multi-locus models in bread wheat
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103272/
https://www.ncbi.nlm.nih.gov/pubmed/30154817
http://dx.doi.org/10.3389/fpls.2018.01196
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