Original Research ARTICLE
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
- 1Northeast Agricultural University, China
- 2National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, China
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 (SNP) 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 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.
Keywords: Seed weight per plant, Soybean, Single nucleotide polymorphism, GWAS (genome-wide association study), candidate genes
Received: 21 May 2018;
Accepted: 03 Sep 2018.
Edited by:Maoteng Li, Huazhong University of Science and Technology, China
Reviewed by:Steven B. Cannon, Agricultural Research Service (USDA), United States
Yan Long, Institute of Biotechnology (CAAS), China
Copyright: © 2018 Jing, Zhao, Wang, Teng, Qiu, Han and Li. 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.
PhD. Yingpeng Han, Northeast Agricultural University, Harbin, China, email@example.com
PhD. Wenbin Li, Northeast Agricultural University, Harbin, China, firstname.lastname@example.org