Despite the importance of soybean as a major crop, genome-wide variation and evolution of cultivated soybeans are largely unknown. Here, we catalogued genome variation in an annual soybean population by high-depth resequencing of 10 cultivated and 6 wild accessions and obtained 3.87 million high-quality single-nucleotide polymorphisms (SNPs) after excluding the sites with missing data in any accession. Nuclear genome phylogeny supported a single origin for the cultivated soybeans. We identified 10-fold longer linkage disequilibrium (LD) in the wild soybean relative to wild maize and rice. Despite the small population size, the long LD and large SNP data allowed us to identify 206 candidate domestication regions with significantly lower diversity in the cultivated, but not in the wild, soybeans. Some of the genes in these candidate regions were associated with soybean homologues of canonical domestication genes. However, several examples, which are likely specific to soybean or eudicot crop plants, were also observed. Consequently, the variation data identified in this study should be valuable for breeding and for identifying agronomically important genes in soybeans. However, the long LD of wild soybeans may hinder pinpointing causal gene(s) in the candidate regions.

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under-use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high-density genetic mapping and genome-wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome-wide association analyses. More than four million high-quality SNPs identified from high-depth genome re-sequencing of 16 soybean accessions and low-depth genome re-sequencing of 31 soybean accessions were used to select 180,961 SNPs for creation of the Axiom(®) SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170,223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene-rich chromosomal regions suggest that this array may be suitable for genome-wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.

Pigs have been one of the most important sources of meat for humans, and their productivity has been substantially improved by recent strong selection. Here, we present whole-genome resequencing analyses of 55 pigs of five breeds representing Korean native pigs, wild boar and three European origin breeds. 1,673.1 Gb of sequence reads were mapped to the Swine reference assembly, covering ∼99.2% of the reference genome, at an average of ∼11.7-fold coverage. We detected 20,123,573 single-nucleotide polymorphisms (SNPs), of which 25.5% were novel. We extracted 35,458 of non-synonymous SNPs in 9,904 genes, which may contribute to traits of interest. The whole SNP sets were further used to access the population structures of the breeds, using multiple methodologies, including phylogenetic, similarity matrix, and population structure analysis. They showed clear population clusters with respect to each breed. Furthermore, we scanned the whole genomes to identify signatures of selection throughout the genome. The result revealed several promising loci that might underlie economically important traits in pigs, such as the CLDN1 and TWIST1 genes. These discoveries provide useful genomic information for further study of the discrete genetic mechanisms associated with economically important traits in pigs.