The genome of an anonymous Korean male has been sequenced using a broad spread of genomic techniques. This combinatorial approach allows for detailed characterization of sequence and structural variation. The first four individual genomes to have been determined spanned three distinct ethnic groups: a Yoruba African, northwest European (Craig Venter and James Watson) and Han Chinese. This new work, together with another Korean sequence reported elsewhere, adds the Altaic ethnic grouping to the list. Human genome sequences have so far been reported for individuals with ancestry in three distinct geographical regions: a Yoruba African, two individuals of northwest European origin, and a person from China. Here, using a combination of methods, a highly annotated, whole-genome sequence is provided for a Korean male. Recent advances in sequencing technologies have initiated an era of personal genome sequences. To date, human genome sequences have been reported for individuals with ancestry in three distinct geographical regions: a Yoruba African, two individuals of northwest European origin, and a person from China1,2,3,4. Here we provide a highly annotated, whole-genome sequence for a Korean individual, known as AK1. The genome of AK1 was determined by an exacting, combined approach that included whole-genome shotgun sequencing (27.8× coverage), targeted bacterial artificial chromosome sequencing, and high-resolution comparative genomic hybridization using custom microarrays featuring more than 24 million probes. Alignment to the NCBI reference, a composite of several ethnic clades5,6, disclosed nearly 3.45 million single nucleotide polymorphisms (SNPs), including 10,162 non-synonymous SNPs, and 170,202 deletion or insertion polymorphisms (indels). SNP and indel densities were strongly correlated genome-wide. Applying very conservative criteria yielded highly reliable copy number variants for clinical considerations. Potential medical phenotypes were annotated for non-synonymous SNPs, coding domain indels, and structural variants. The integration of several human whole-genome sequences derived from several ethnic groups will assist in understanding genetic ancestry, migration patterns and population bottlenecks.

Jeong-Sun Seo and colleagues report a catalog of common CNVs in Asians. The authors integrated high-resolution array CGH data with next-generation DNA sequencing data to discover 3,568 putative Asian-specific CNVs. Copy number variants (CNVs) account for the majority of human genomic diversity in terms of base coverage. Here, we have developed and applied a new method to combine high-resolution array comparative genomic hybridization (CGH) data with whole-genome DNA sequencing data to obtain a comprehensive catalog of common CNVs in Asian individuals. The genomes of 30 individuals from three Asian populations (Korean, Chinese and Japanese) were interrogated with an ultra-high-resolution array CGH platform containing 24 million probes. Whole-genome sequencing data from a reference genome (NA10851, with 28.3× coverage) and two Asian genomes (AK1, with 27.8× coverage and AK2, with 32.0× coverage) were used to transform the relative copy number information obtained from array CGH experiments into absolute copy number values. We discovered 5,177 CNVs, of which 3,547 were putative Asian-specific CNVs. These common CNVs in Asian populations will be a useful resource for subsequent genetic studies in these populations, and the new method of calling absolute CNVs will be essential for applying CNV data to personalized medicine.

Somatic genome mutations occur due to combinations of various intrinsic/extrinsic mutational processes and DNA repair mechanisms. Different molecular processes frequently generate different signatures of somatic mutations in their own favored contexts. As a result, the regional somatic mutation rate is dependent on the local DNA sequence, the DNA replication/RNA transcription dynamics and epigenomic chromatin organization landscape in the genome. Here, we propose an online computational framework, termed Mutalisk, which correlates somatic mutations with various genomic, transcriptional and epigenomic features in order to understand mutational processes that contribute to the generation of the mutations. This user-friendly tool explores the presence of localized hypermutations (kataegis), dissects the spectrum of mutations into the maximum likelihood combination of known mutational signatures and associates the mutation density with numerous regulatory elements in the genome. As a result, global patterns of somatic mutations in any query sample can be efficiently screened, thus enabling a deeper understanding of various mutagenic factors. This tool will facilitate more effective downstream analyses of cancer genome sequences to elucidate the diversity of mutational processes underlying the development and clonal evolution of cancer cells. Mutalisk is freely available at http://mutalisk.org.