Whole genome sequencing of 35 individuals provides insights into the genetic architecture of Korean population

Abstract

BackgroundDue to a significant decline in the costs associated with next-generation sequencing, it has become possible to decipher the genetic architecture of a population by sequencing a large number of individuals to a deep coverage. The Korean Personal Genomes Project (KPGP) recently sequenced 35 Korean genomes at high coverage using the Illumina Hiseq platform and made the deep sequencing data publicly available, providing the scientific community opportunities to decipher the genetic architecture of the Korean population.MethodsIn this study, we used two single nucleotide variant (SNV) calling pipelines: mapping the raw reads obtained from whole genome sequencing of 35 Korean individuals in KPGP using BWA and SOAP2 followed by SNV calling using SAMtools and SOAPsnp, respectively. The consensus SNVs obtained from the two SNV pipelines were used to represent the SNVs of the Korean population. We compared these SNVs to those from 17 other populations provided by the HapMap consortium and the 1000 Genomes Project (1KGP) and identified SNVs that were only present in the Korean population. We studied the mutation spectrum and analyzed the genes of non-synonymous SNVs only detected in the Korean population.ResultsWe detected a total of 8,555,726 SNVs in the 35 Korean individuals and identified 1,213,613 SNVs detected in at least one Korean individual (SNV-1) and 12,640 in all of 35 Korean individuals (SNV-35) but not in 17 other populations. In contrast with the SNVs common to other populations in HapMap and 1KGP, the Korean only SNVs had high percentages of non-silent variants, emphasizing the unique roles of these Korean only SNVs in the Korean population. Specifically, we identified 8,361 non-synonymous Korean only SNVs, of which 58 SNVs existed in all 35 Korean individuals. The 5,754 genes of non-synonymous Korean only SNVs were highly enriched in some metabolic pathways. We found adhesion is the top disease term associated with SNV-1 and Nelson syndrome is the only disease term associated with SNV-35. We found that a significant number of Korean only SNVs are in genes that are associated with the drug term of adenosine.ConclusionWe identified the SNVs that were found in the Korean population but not seen in other populations, and explored the corresponding genes and pathways as well as the associated disease terms and drug terms. The results expand our knowledge of the genetic architecture of the Korean population, which will benefit the implementation of personalized medicine for the Korean population.

An ethnically relevant consensus Korean reference genome is a step towards personal reference genomes

“…1). Furthermore, we integrate information from 40 high-coverage whole genomes (based on short reads) from the Korean PGP (KPGP)28 to generate a population-wide consensus Korean reference, KOREF_C. We compare the genomic structure of KOREF_C with other human genome assemblies, uncovering many structural differences, including ethnic-specific highly frequent structural variants.…”

Detection of novel germline mutations in six breast cancer predisposition genes by targeted next-generation sequencing

“…For example, rare variants of A1708E, G1738R, and R1699Q in the BRCA1 gene lead to amino acid changes that are found to be associated with the susceptibility to breast cancer (Lovelock et al., ). NGS has a higher accuracy and sensitivity for rare genetic variants (Hong et al., ; Su et al., ; Zhang et al., ). Therefore, it is anticipated that NGS will significantly contribute to the comprehension of the genetics of complex diseases and phenotypic traits, and may even explain the “missing variance” (Londin, Yadav, Surrey, Kricka, & Fortina, ; Marian, ; Wagner, ).…”

KoVariome: Korean National Standard Reference Variome database of whole genomes with comprehensive SNV, indel, CNV, and SV analyses

“…By merging the variants of 50 unrelated Korean individuals, we identified 12.7M SNVs and 1.7M small indels shorter than 100bp (Table 1); approximately 1.5 times the number of SNVs previously reported from preliminary KPGP data (0.8M) 33 . Both types of variants were primarily distributed in the non-coding regions (about 98%), including intergenic and intron regions (Supplementary Table S6).…”