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Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds

Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessi...

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Autores principales: Qin, Jun, Shi, Ainong, Song, Qijian, Li, Song, Wang, Fengmin, Cao, Yinghao, Ravelombola, Waltram, Song, Qi, Yang, Chunyan, Zhang, Mengchen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873630/
https://www.ncbi.nlm.nih.gov/pubmed/31803203
http://dx.doi.org/10.3389/fpls.2019.01445
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author Qin, Jun
Shi, Ainong
Song, Qijian
Li, Song
Wang, Fengmin
Cao, Yinghao
Ravelombola, Waltram
Song, Qi
Yang, Chunyan
Zhang, Mengchen
author_facet Qin, Jun
Shi, Ainong
Song, Qijian
Li, Song
Wang, Fengmin
Cao, Yinghao
Ravelombola, Waltram
Song, Qi
Yang, Chunyan
Zhang, Mengchen
author_sort Qin, Jun
collection PubMed
description Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.
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spelling pubmed-68736302019-12-04 Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds Qin, Jun Shi, Ainong Song, Qijian Li, Song Wang, Fengmin Cao, Yinghao Ravelombola, Waltram Song, Qi Yang, Chunyan Zhang, Mengchen Front Plant Sci Plant Science Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality. Frontiers Media S.A. 2019-11-15 /pmc/articles/PMC6873630/ /pubmed/31803203 http://dx.doi.org/10.3389/fpls.2019.01445 Text en Copyright © 2019 Qin, Shi, Song, Li, Wang, Cao, Ravelombola, Song, Yang and Zhang 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
Qin, Jun
Shi, Ainong
Song, Qijian
Li, Song
Wang, Fengmin
Cao, Yinghao
Ravelombola, Waltram
Song, Qi
Yang, Chunyan
Zhang, Mengchen
Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title_full Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title_fullStr Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title_full_unstemmed Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title_short Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds
title_sort genome wide association study and genomic selection of amino acid concentrations in soybean seeds
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873630/
https://www.ncbi.nlm.nih.gov/pubmed/31803203
http://dx.doi.org/10.3389/fpls.2019.01445
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