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Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping

Soybean varieties suitable for high planting density allow greater yields. However, the seed protein and oil contents, which determine the value of this crop, can be influenced by planting density. Thus, it is important to understand the genetic basis of the responses of different soybean genotypes...

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Autores principales: Tian, Xiaocui, Zhang, Kaixin, Liu, Shulin, Sun, Xu, Li, Xiyu, Song, Jie, Qi, Zhongying, Wang, Yue, Fang, Yanlong, Wang, Jiajing, Jiang, Sitong, Yang, Chang, Tian, Zhixi, Li, Wen-Xia, Ning, Hailong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330087/
https://www.ncbi.nlm.nih.gov/pubmed/32670348
http://dx.doi.org/10.3389/fgene.2020.00563
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author Tian, Xiaocui
Zhang, Kaixin
Liu, Shulin
Sun, Xu
Li, Xiyu
Song, Jie
Qi, Zhongying
Wang, Yue
Fang, Yanlong
Wang, Jiajing
Jiang, Sitong
Yang, Chang
Tian, Zhixi
Li, Wen-Xia
Ning, Hailong
author_facet Tian, Xiaocui
Zhang, Kaixin
Liu, Shulin
Sun, Xu
Li, Xiyu
Song, Jie
Qi, Zhongying
Wang, Yue
Fang, Yanlong
Wang, Jiajing
Jiang, Sitong
Yang, Chang
Tian, Zhixi
Li, Wen-Xia
Ning, Hailong
author_sort Tian, Xiaocui
collection PubMed
description Soybean varieties suitable for high planting density allow greater yields. However, the seed protein and oil contents, which determine the value of this crop, can be influenced by planting density. Thus, it is important to understand the genetic basis of the responses of different soybean genotypes to planting density. In this study, we quantified the protein and oil contents in a four-way recombinant inbred line (FW-RIL) soybean population under two planting densities and the response to density. We performed quantitative trait locus (QTL) mapping using a single nucleotide polymorphism (SNP) linkage map generated by inclusive composite interval mapping. We identified 14 QTLs for protein content and 17 for oil content at a planting density of 2.15 × 10(5) plant/ha (D1) and 14 QTLs for protein content and 20 for oil content at a planting density 3.0 × 10(5) plant/ha (D2). Among the QTLs detected, two oil-content QTLs was detected at both plant densities. In addition, we identified 38 QTLs for the responses of protein and oil contents to planting density. Of the QTLs detected, 70 were identified in previous studies, while 33 were newly identified. Fourty-five QTLs accounted for over 10% of the phenotypic variation of the corresponding trait, based on 23 QTLs at a marker interval distance of ~600 kb detected under different densities and with the responses to density difference. Pathway analysis revealed four candidate genes involved in protein and oil biosynthesis/metabolism. These results improve our understanding of the genetic underpinnings of protein and oil biosynthesis in soybean, laying the foundation for enhancing protein and oil contents and increasing yields in soybean.
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spelling pubmed-73300872020-07-14 Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping Tian, Xiaocui Zhang, Kaixin Liu, Shulin Sun, Xu Li, Xiyu Song, Jie Qi, Zhongying Wang, Yue Fang, Yanlong Wang, Jiajing Jiang, Sitong Yang, Chang Tian, Zhixi Li, Wen-Xia Ning, Hailong Front Genet Genetics Soybean varieties suitable for high planting density allow greater yields. However, the seed protein and oil contents, which determine the value of this crop, can be influenced by planting density. Thus, it is important to understand the genetic basis of the responses of different soybean genotypes to planting density. In this study, we quantified the protein and oil contents in a four-way recombinant inbred line (FW-RIL) soybean population under two planting densities and the response to density. We performed quantitative trait locus (QTL) mapping using a single nucleotide polymorphism (SNP) linkage map generated by inclusive composite interval mapping. We identified 14 QTLs for protein content and 17 for oil content at a planting density of 2.15 × 10(5) plant/ha (D1) and 14 QTLs for protein content and 20 for oil content at a planting density 3.0 × 10(5) plant/ha (D2). Among the QTLs detected, two oil-content QTLs was detected at both plant densities. In addition, we identified 38 QTLs for the responses of protein and oil contents to planting density. Of the QTLs detected, 70 were identified in previous studies, while 33 were newly identified. Fourty-five QTLs accounted for over 10% of the phenotypic variation of the corresponding trait, based on 23 QTLs at a marker interval distance of ~600 kb detected under different densities and with the responses to density difference. Pathway analysis revealed four candidate genes involved in protein and oil biosynthesis/metabolism. These results improve our understanding of the genetic underpinnings of protein and oil biosynthesis in soybean, laying the foundation for enhancing protein and oil contents and increasing yields in soybean. Frontiers Media S.A. 2020-06-25 /pmc/articles/PMC7330087/ /pubmed/32670348 http://dx.doi.org/10.3389/fgene.2020.00563 Text en Copyright © 2020 Tian, Zhang, Liu, Sun, Li, Song, Qi, Wang, Fang, Wang, Jiang, Yang, 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
Tian, Xiaocui
Zhang, Kaixin
Liu, Shulin
Sun, Xu
Li, Xiyu
Song, Jie
Qi, Zhongying
Wang, Yue
Fang, Yanlong
Wang, Jiajing
Jiang, Sitong
Yang, Chang
Tian, Zhixi
Li, Wen-Xia
Ning, Hailong
Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title_full Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title_fullStr Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title_full_unstemmed Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title_short Quantitative Trait Locus Analysis of Protein and Oil Content in Response to Planting Density in Soybean (Glycine max [L.] Merri.) Seeds Based on SNP Linkage Mapping
title_sort quantitative trait locus analysis of protein and oil content in response to planting density in soybean (glycine max [l.] merri.) seeds based on snp linkage mapping
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330087/
https://www.ncbi.nlm.nih.gov/pubmed/32670348
http://dx.doi.org/10.3389/fgene.2020.00563
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