Major Soybean Maturity Gene Haplotypes Revealed by SNPViz Analysis of 72 Sequenced Soybean Genomes

Abstract

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.

Identification of mega‐environments in Europe and effect of allelic variation at maturity E loci on adaptation of European soybean

“…This conclusion is corroborated by a recent study by Langewisch et al . (), who did not observe the e1‐nl allele in later‐maturing US American lines of MGs II, III and IV but found the partially functional e1‐as allele to predominate, suggesting that this allele was essential for the development of productive lines, adapted to the North American growing areas. Xu et al .…”

Comprehensive description of genomewide nucleotide and structural variation in short‐season soya bean

“…Indeed, Glyma.10 g221500 (GmGIa) (one of these 30 genes) is the gene underlying the maturity locus E2. The mutation in exon 10 of this gene is the known causal variant for the e2 allele (Langewisch et al, 2014). As the lines characterized in this work are all adapted to a short growing season, it makes perfect sense that these are fixed for a nonfunctional allele that contributes to earliness.…”

“…At the E3 (GmPhyA3) locus, some early-flowering accessions are known to carry the e3-tr allele characterized by a 15.5-kb deletion that leads to a truncated and nonfunctional phytochrome (Tardivel et al, 2014). Similarly, at the E4 (GmPhyA2) locus, many early accessions carry the e4 (SORE-1) allele characterized by the insertion of a 6.2-kb retroelement (Langewisch et al, 2014). In previous work (Tardivel et al, 2014), allele-specific primers had been used to precisely identify the alleles present at these two loci for 50 of the soya bean lines used here and, in all cases, the SVs called on the basis of the WGS reads coincided perfectly with the PCR results (Table S4, Figure S6).…”

Genetic separation of southern and northern soybean breeding programs in North America and their associated allelic variation at four maturity loci

“…Although more than 100 genes may be involved in flowering pathways in soybean (Kim et al 2012), only ten loci ( E1–E9 , J ) have been mapped and reported to control time to flowering and maturity. Maturity genes E1 , E2 , E3 , and E4 have been identified and sequenced (Liu et al 2008; Tsubokura et al 2013; Watanabe et al 2012; Watanabe et al 2009; Watanabe et al 2011; Xia et al 2012), and various soybean cultivars have been screened for their allelic variants (Langewisch et al 2014; Tsubokura et al 2014; Zhai et al 2014). It has been estimated that the four maturity genes contribute between 62 and 66% of variation of flowering time in a population containing 63 soybean accessions (Tsubokura et al 2014).…”