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Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models

Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pastin...

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Autores principales: Xu, Yang, Yang, Tiantian, Zhou, Yao, Yin, Shuangyi, Li, Pengcheng, Liu, Jun, Xu, Shuhui, Yang, Zefeng, Xu, Chenwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134291/
https://www.ncbi.nlm.nih.gov/pubmed/30233634
http://dx.doi.org/10.3389/fpls.2018.01311
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author Xu, Yang
Yang, Tiantian
Zhou, Yao
Yin, Shuangyi
Li, Pengcheng
Liu, Jun
Xu, Shuhui
Yang, Zefeng
Xu, Chenwu
author_facet Xu, Yang
Yang, Tiantian
Zhou, Yao
Yin, Shuangyi
Li, Pengcheng
Liu, Jun
Xu, Shuhui
Yang, Zefeng
Xu, Chenwu
author_sort Xu, Yang
collection PubMed
description Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS.
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spelling pubmed-61342912018-09-19 Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models Xu, Yang Yang, Tiantian Zhou, Yao Yin, Shuangyi Li, Pengcheng Liu, Jun Xu, Shuhui Yang, Zefeng Xu, Chenwu Front Plant Sci Plant Science Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS. Frontiers Media S.A. 2018-09-05 /pmc/articles/PMC6134291/ /pubmed/30233634 http://dx.doi.org/10.3389/fpls.2018.01311 Text en Copyright © 2018 Xu, Yang, Zhou, Yin, Li, Liu, Xu, Yang and Xu. 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
Xu, Yang
Yang, Tiantian
Zhou, Yao
Yin, Shuangyi
Li, Pengcheng
Liu, Jun
Xu, Shuhui
Yang, Zefeng
Xu, Chenwu
Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title_full Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title_fullStr Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title_full_unstemmed Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title_short Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
title_sort genome-wide association mapping of starch pasting properties in maize using single-locus and multi-locus models
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134291/
https://www.ncbi.nlm.nih.gov/pubmed/30233634
http://dx.doi.org/10.3389/fpls.2018.01311
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