Landscape of genomic diversity and trait discovery in soybean

Abstract

Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces, and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered, and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity, and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution, and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Deploying Fourier Coefficients to Unravel Soybean Canopy Diversity

“…This is consistent with their status as centers of diversity for the domesticated soybean (Hymowitz and Harlan, 1983; Zhou et al, 2015; Valliyodan et al, 2016). No significant pattern/classification among the countries is observed in the PCs representation in Figure 7A.…”

Transcript Polymorphism Rates in Soybean Seed Tissue Are Increased in a Single Transformant ofGlycine max

“…However, given the possibility that mutations from transgenesis could occur within QTLs that control traits such as plant size, flower count, and seed quantity, identification of novel polymorphisms in these regions of soybean's transcriptome is of great importance to both plant breeders and in biotechnology applications. In fact, recent investigations have revealed an excess of 9 million unique SNPs that occur between 106 different cultivated soybean varieties [48]. Here, we have provided lists of exonic SNPs unique to each of the three transgenic groups and specific to transformation, as well as novel SNPs detected in our Williams 82 wild type controls.…”

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

“…In soybean, QTLomics has been applied for characterization of mapped QTLs as well as for mapping and characterization of new QTLs. Recently, several sequence based data-sets has been generated by re-sequencing efforts to facilitate QTLomics studies in soybean (Table 1; Lam et al, 2010; Li et al, 2013, 2014; Chung et al, 2014; Qiu et al, 2014; Zhou Z. et al, 2015; Valliyodan et al, 2016). The availability of well-annotated soybean genome sequence and re-sequencing based data-sets also facilitate development of large number of SNP and Indel markers which are being utilized in QTL mapping and molecular breeding in soybean.…”

“…Using microarray and high-throughput whole transcriptome sequencing approaches, 13 genes displaying significant seed transcript expression between NILs were identified which included a potential regulatory protein of the Mov34-1 family, a heat shock protein Hsp22.5, and an ATP synthase (Bolon et al, 2010). In a regional association study of genomic block on Gm20, Valliyodan et al (2016) identified that the copy number variations in candidate genes (HSP, Glyma20g19680 ; ammonium transporter, Glyma20g21030 ; ethylene receptor, Glyma20g21780 ) were associated with protein content. Lestari et al (2013) reported that parts of Gm20 and Gm10 showed synteny, however QTLs for seed protein content were detected only on Gm20.…”

“…At least 110 QTLs for soybean oil content have been mapped but the utilization of these QTLs for soybean breeding has some limitations. Recently, Valliyodan et al (2016) conducted comparative sequence analysis between high and low oil lines and showed differential variation in SNP and copy number for lipid biosynthesis and lipid degradation genes between high oil and low oil lines. The comparative analysis shows increased copy number of lipid transfer protein (LPT; Glyma16g31780, Glyma16g31840 , and Glyma16g31540 ) in high oil lines, whereas the negative regulators of lipid biosynthesis genes (ABC transporter, Glyma03g36310 , Lipase 3, and Glyma13g04561 ) showed more copies in low oil lines.…”