The first Korean genome sequence and analysis: Full genome sequencing for a socio-ethnic group

Abstract

We present the first Korean individual genome sequence (SJK) and analysis results. The diploid genome of a Korean male was sequenced to 28.95-fold redundancy using the Illumina paired-end sequencing method. SJK covered 99.9% of the NCBI human reference genome. We identified 420,083 novel single nucleotide polymorphisms (SNPs) that are not in the dbSNP database. Despite a close similarity, significant differences were observed between the Chinese genome (YH), the only other Asian genome available, and SJK: (1) 39.87% (1,371,239 out of 3,439,107) SNPs were SJK-specific (49.51% against Venter's, 46.94% against Watson's, and 44.17% against the Yoruba genomes); (2) 99.5% (22,495 out of 22,605) of short indels (< 4 bp) discovered on the same loci had the same size and type as YH; and (3) 11.3% (331 out of 2920) deletion structural variants were SJK-specific. Even after attempting to map unmapped reads of SJK to unanchored NCBI scaffolds, HGSV, and available personal genomes, there were still 5.77% SJK reads that could not be mapped. All these findings indicate that the overall genetic differences among individuals from closely related ethnic groups may be significant. Hence, constructing reference genomes for minor socio-ethnic groups will be useful for massive individual genome sequencing.

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

“…Another commonly used approach is to apply quality filters that are aimed at selectively removing errors. Every whole-genome sequence reported so far has used filtering to some extent: the most commonly used filters being those that remove sequences with a too-low coverage depth, discard variants with a low-confidence score or eliminate variants located within a cluster of variants 3,7,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] . Surprisingly, there is little consensus with respect to which filters should be used and at which threshold they should be applied.…”

“…As a result, each reported study developed its own heterogeneous set of filters and applied them at various (suboptimal) thresholds. For instance, in the case of the coverage depth filter, thresholds removing sequences with a coverage depth <4×, <10× or <11× were applied 6,10,11,16,17,23,24 . Additionally, it has not been assessed to which extent filters discard true variants, and how each filter can be optimized in terms of sensitivity and specificity.…”

The pursuit of genome-wide association studies: where are we now?

“…So far, seven human diploid genomes have been fully sequenced, and some important insights have been gained from these resequencing studies. [145][146][147][148][149][150][151] The most prominent finding from these studies is that, besides SNPs, other genetic variants are also abundant in the human genome. These studies found that in addition to the 3-4 million SNPs, several hundred-thousand of short indels (for example, sizes defined as 3 and 16 bp or less in the Bentley et al 147 and Wang et al 148 study, respectively) are also present in each individual human genome.…”

The discovery of human genetic variations and their use as disease markers: past, present and future

“…As such, the remaining several hundred thousands of indels in the range of several nucleotides to tens of nucleotides, which were identified in the recent whole genome resequencing experiments, do not currently have their own category. [27][28][29][30][31][32][33] For example, Wang et al (2008) 29 found B140 000 indels within 1-3 bp in the Han Chinese YH genome, and B400 000 indels defined from 1 to 16 bp were also detected in the African NA18507 genome by Bentley et al (2008). 30 Perhaps a new category such as 'short indels' needs to be created to fit them in, and those indels between 100 bp to 1 kb should probably be renamed as 'intermediate indels' (Figures 1c and d).…”

“…2 However, the richness of genetic variations in the human genome has recently been further corroborated by the several whole genome resequencing studies, revealing plenty of new SNPs, indels, CNVs and other structural variations. [27][28][29][30][31][32][33] The technological developments have facilitated and accelerated the process of identifying genetic variations, especially with the arrival of next generation sequencing technologies, which have made whole genome resequencing and the 1000 Genomes Project feasible. [53][54][55] In recent years, many studies have been done to directly examine the associations of CNVs with complex diseases using SNP genotyping arrays.…”