Cargando…

Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study

Seed weight per plant (SWPP) of soybean (Glycine max (L.) Merr.), a complicated quantitative trait controlled by multiple genes, was positively associated with soybean seed yields. In the present study, a natural soybean population containing 185 diverse accessions primarily from China was used to a...

Descripción completa

Detalles Bibliográficos
Autores principales: Jing, Yan, Zhao, Xue, Wang, Jinyang, Teng, Weili, Qiu, Lijuan, Han, Yingpeng, Li, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194254/
https://www.ncbi.nlm.nih.gov/pubmed/30369935
http://dx.doi.org/10.3389/fpls.2018.01392
_version_ 1783364202108289024
author Jing, Yan
Zhao, Xue
Wang, Jinyang
Teng, Weili
Qiu, Lijuan
Han, Yingpeng
Li, Wenbin
author_facet Jing, Yan
Zhao, Xue
Wang, Jinyang
Teng, Weili
Qiu, Lijuan
Han, Yingpeng
Li, Wenbin
author_sort Jing, Yan
collection PubMed
description Seed weight per plant (SWPP) of soybean (Glycine max (L.) Merr.), a complicated quantitative trait controlled by multiple genes, was positively associated with soybean seed yields. In the present study, a natural soybean population containing 185 diverse accessions primarily from China was used to analyze the genetic basis of SWPP via genome-wide association analysis (GWAS) based on high-throughput single-nucleotide polymorphisms (SNPs) generated by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) method. A total of 33,149 SNPs were finally identified with minor allele frequencies (MAF) > 5% which were present in 97% of all the genotypes. Twenty association signals associated with SWPP were detected via GWAS. Among these signals, eight SNPs were novel loci, and the other twelve SNPs were overlapped or located in the linked genomic regions of the reported QTL from SoyBase database. Several genes belonging to the categories of hormone pathways, RNA regulation of transcription in plant development, ubiquitin, transporting systems, and other metabolisms were considered as candidate genes associated with SWPP. Furthermore, nine genes from the flanking region of Gm07:19488264, Gm08:15768591, Gm08:15768603, or Gm18:23052511 were significantly associated with SWPP and were stable among multiple environments. Nine out of 18 haplotypes from nine genes showed the effect of increasing SWPP. The identified loci along with the beneficial alleles and candidate genes could be of great value for studying the molecular mechanisms underlying SWPP and for improving the potential seed yield of soybean in the future.
format Online
Article
Text
id pubmed-6194254
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-61942542018-10-26 Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study Jing, Yan Zhao, Xue Wang, Jinyang Teng, Weili Qiu, Lijuan Han, Yingpeng Li, Wenbin Front Plant Sci Plant Science Seed weight per plant (SWPP) of soybean (Glycine max (L.) Merr.), a complicated quantitative trait controlled by multiple genes, was positively associated with soybean seed yields. In the present study, a natural soybean population containing 185 diverse accessions primarily from China was used to analyze the genetic basis of SWPP via genome-wide association analysis (GWAS) based on high-throughput single-nucleotide polymorphisms (SNPs) generated by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) method. A total of 33,149 SNPs were finally identified with minor allele frequencies (MAF) > 5% which were present in 97% of all the genotypes. Twenty association signals associated with SWPP were detected via GWAS. Among these signals, eight SNPs were novel loci, and the other twelve SNPs were overlapped or located in the linked genomic regions of the reported QTL from SoyBase database. Several genes belonging to the categories of hormone pathways, RNA regulation of transcription in plant development, ubiquitin, transporting systems, and other metabolisms were considered as candidate genes associated with SWPP. Furthermore, nine genes from the flanking region of Gm07:19488264, Gm08:15768591, Gm08:15768603, or Gm18:23052511 were significantly associated with SWPP and were stable among multiple environments. Nine out of 18 haplotypes from nine genes showed the effect of increasing SWPP. The identified loci along with the beneficial alleles and candidate genes could be of great value for studying the molecular mechanisms underlying SWPP and for improving the potential seed yield of soybean in the future. Frontiers Media S.A. 2018-10-11 /pmc/articles/PMC6194254/ /pubmed/30369935 http://dx.doi.org/10.3389/fpls.2018.01392 Text en Copyright © 2018 Jing, Zhao, Wang, Teng, Qiu, Han and Li. 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
Jing, Yan
Zhao, Xue
Wang, Jinyang
Teng, Weili
Qiu, Lijuan
Han, Yingpeng
Li, Wenbin
Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title_full Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title_fullStr Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title_full_unstemmed Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title_short Identification of the Genomic Region Underlying Seed Weight per Plant in Soybean (Glycine max L. Merr.) via High-Throughput Single-Nucleotide Polymorphisms and a Genome-Wide Association Study
title_sort identification of the genomic region underlying seed weight per plant in soybean (glycine max l. merr.) via high-throughput single-nucleotide polymorphisms and a genome-wide association study
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194254/
https://www.ncbi.nlm.nih.gov/pubmed/30369935
http://dx.doi.org/10.3389/fpls.2018.01392
work_keys_str_mv AT jingyan identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT zhaoxue identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT wangjinyang identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT tengweili identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT qiulijuan identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT hanyingpeng identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy
AT liwenbin identificationofthegenomicregionunderlyingseedweightperplantinsoybeanglycinemaxlmerrviahighthroughputsinglenucleotidepolymorphismsandagenomewideassociationstudy