A map of genetic variation from 781 soybean genomes Soon-Chun Jeong1,*, Myung-Shin Kim1, Roberto Lozano2, Ji Hong Kim1, Dong Nyuk Bae1, Man Soo Choi3, Soo-Kwon Park3, Michael A. Gore2, and Jung-Kyung Moon4 1Bio-evaluation center, Korea Research Institute of Bioscience and Biotechnology, Cheongju, Korea 2Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA 3National Institute of Crop Science, Rural Development Administration, Wanju, Korea 4Agricultural Genome Center, National Academy of Agricultural Sciences, Jeonju, Korea *Corresponding author: scjeong@kribb.re.kr Introduction Soybean (Glycine max [L.] Merr.) is an important crop species. The cultivation of soybean has been historically confined to East Asia. Its cultivation area has been recently expanded to North America, South America, and India, positioning it as one top crop in terms of growing area worldwide. After the release of the draft soybean genome sequence, efforts to map soybean genetic variation by single nucleotide polymorphism (SNP) array genotyping have resulted in the global picture of common and rare SNPs across the genome. However, those data have been poorly used as an integrated manner to serve as haplotype information by imputation approaches that enrich the above SNP genotype data with whole genome SNP data. The resultant genomic data set could also be leveraged as a reference panel to enrich sparse data sets generated from platforms such as low-density SNP array, genotyping- by-sequencing (GBS) or skim sequencing. In addition, genetic variation of wild soybean, which contains a large amount of untapped and unexplored soybean diversity, remains poorly characterized relative to that of domesticated soybean. Here we report genomes of 781 soybean accessions consisting of 418 G. max, 345 G. soja, and 18 hybrid (G. max x G. soja) accessions obtained through high-coverage (> 13x) whole-genome sequence data. We conducted a comprehensive characterization of genetic variation including profiling and functional significance of rare and common genetic variants and detection of domestication-selective sweeps. We are then attempting to show the usefulness of our data in soybean genetics by imputing the SNP data set from 50K US SNP array genotyping using variants identified here for association analyses of protein and oil traits. Materials and Methods Resequencing data from a total of 855 samples were obtained for initial variant calling in this study. We then essentially followed procedures described in the Genome Analysis Toolkit (GATK) Best Practices for data pre-processing and variant calling. Principal component, fastStructure Bayesian clustering, and Neighbor-joining tree construction was used to infer population structure. Historical recombination rate, linkage disequilibrium decay, genomic evolutionary rate profiling, Sorting Intolerant From Tolerant 4G, cross-population composite likelihood ratio test, and genome-wide association studies were performed to infer nucleotide variation pattern, identify selective sweeps, and find association between genotypes and phenotypes. Results and Discussion High heterozygous samples were excluded from further analyses. Distributions of inbreeding coefficient per individuals in subgroups divided by species and heterozygosity indicated that most samples excluded by the high heterozygosity showed an inbreeding coefficient of less than 0.8. Final 781 accessions consisted of 418 G. max, 345 G. soja, and 18 hybrid (G. max x G. soja) accessions. Results and Discussion As observed in the previous study, the 781 accessions were clearly divided into one G. max group and two G. soja groups with a distinct subgroup of G. soja accessions collected from the middle region of the Yellow River basin. Abstract Soybean is an economically and environmentally important major crop worldwide. It is a predominant plant protein and oil source of both food and feed and has capacity to fix atmospheric n