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Genome-wide association and epistatic interactions of flowering time in soybean cultivar

Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP...

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Autores principales: Kim, Kyoung Hyoun, Kim, Jae-Yoon, Lim, Won-Jun, Jeong, Seongmun, Lee, Ho-Yeon, Cho, Youngbum, Moon, Jung-Kyung, Kim, Namshin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6975553/
https://www.ncbi.nlm.nih.gov/pubmed/31968016
http://dx.doi.org/10.1371/journal.pone.0228114
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author Kim, Kyoung Hyoun
Kim, Jae-Yoon
Lim, Won-Jun
Jeong, Seongmun
Lee, Ho-Yeon
Cho, Youngbum
Moon, Jung-Kyung
Kim, Namshin
author_facet Kim, Kyoung Hyoun
Kim, Jae-Yoon
Lim, Won-Jun
Jeong, Seongmun
Lee, Ho-Yeon
Cho, Youngbum
Moon, Jung-Kyung
Kim, Namshin
author_sort Kim, Kyoung Hyoun
collection PubMed
description Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom(®) SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.
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spelling pubmed-69755532020-02-04 Genome-wide association and epistatic interactions of flowering time in soybean cultivar Kim, Kyoung Hyoun Kim, Jae-Yoon Lim, Won-Jun Jeong, Seongmun Lee, Ho-Yeon Cho, Youngbum Moon, Jung-Kyung Kim, Namshin PLoS One Research Article Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom(®) SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean. Public Library of Science 2020-01-22 /pmc/articles/PMC6975553/ /pubmed/31968016 http://dx.doi.org/10.1371/journal.pone.0228114 Text en © 2020 Kim et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kim, Kyoung Hyoun
Kim, Jae-Yoon
Lim, Won-Jun
Jeong, Seongmun
Lee, Ho-Yeon
Cho, Youngbum
Moon, Jung-Kyung
Kim, Namshin
Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title_full Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title_fullStr Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title_full_unstemmed Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title_short Genome-wide association and epistatic interactions of flowering time in soybean cultivar
title_sort genome-wide association and epistatic interactions of flowering time in soybean cultivar
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6975553/
https://www.ncbi.nlm.nih.gov/pubmed/31968016
http://dx.doi.org/10.1371/journal.pone.0228114
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