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Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies
Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality s...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378803/ https://www.ncbi.nlm.nih.gov/pubmed/32765581 http://dx.doi.org/10.3389/fgene.2020.00689 |
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author | Qi, Zhongying Song, Jie Zhang, Kaixin Liu, Shulin Tian, Xiaocui Wang, Yue Fang, Yanlong Li, Xiyu Wang, Jiajing Yang, Chang Jiang, Sitong Sun, Xu Tian, Zhixi Li, Wenxia Ning, Hailong |
author_facet | Qi, Zhongying Song, Jie Zhang, Kaixin Liu, Shulin Tian, Xiaocui Wang, Yue Fang, Yanlong Li, Xiyu Wang, Jiajing Yang, Chang Jiang, Sitong Sun, Xu Tian, Zhixi Li, Wenxia Ning, Hailong |
author_sort | Qi, Zhongying |
collection | PubMed |
description | Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties. |
format | Online Article Text |
id | pubmed-7378803 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73788032020-08-05 Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies Qi, Zhongying Song, Jie Zhang, Kaixin Liu, Shulin Tian, Xiaocui Wang, Yue Fang, Yanlong Li, Xiyu Wang, Jiajing Yang, Chang Jiang, Sitong Sun, Xu Tian, Zhixi Li, Wenxia Ning, Hailong Front Genet Genetics Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties. Frontiers Media S.A. 2020-07-16 /pmc/articles/PMC7378803/ /pubmed/32765581 http://dx.doi.org/10.3389/fgene.2020.00689 Text en Copyright © 2020 Qi, Song, Zhang, Liu, Tian, Wang, Fang, Li, Wang, Yang, Jiang, Sun, Tian, Li and Ning. 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 | Genetics Qi, Zhongying Song, Jie Zhang, Kaixin Liu, Shulin Tian, Xiaocui Wang, Yue Fang, Yanlong Li, Xiyu Wang, Jiajing Yang, Chang Jiang, Sitong Sun, Xu Tian, Zhixi Li, Wenxia Ning, Hailong Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title | Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title_full | Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title_fullStr | Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title_full_unstemmed | Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title_short | Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies |
title_sort | identification of qtns controlling 100-seed weight in soybean using multilocus genome-wide association studies |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378803/ https://www.ncbi.nlm.nih.gov/pubmed/32765581 http://dx.doi.org/10.3389/fgene.2020.00689 |
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