PanSNPdb: the Pan-Asian SNP genotyping database.

The HUGO Pan-Asian SNP consortium conducted the largest survey to date of human genetic diversity among Asians by sampling 1,719 unrelated individuals among 71 populations from China, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand. We have constructed a database (PanSNPdb), which contains these data and various new analyses of them. PanSNPdb is a research resource in the analysis of the population structure of Asian peoples, including linkage disequilibrium patterns, haplotype distributions, and copy number variations. Furthermore, PanSNPdb provides an interactive comparison with other SNP and CNV databases, including HapMap3, JSNP, dbSNP and DGV and thus provides a comprehensive resource of human genetic diversity. The information is accessible via a widely accepted graphical interface used in many genetic variation databases. Unrestricted access to PanSNPdb and any associated files is available at: http://www4a.biotec.or.th/PASNP.

COMUS: Clinician-Oriented locus-specific MUtation detection and deposition System.

BACKGROUND: A disease-causing mutation refers to a heritable genetic change that is associated with a specific phenotype (disease). The detection of a mutation from a patient's sample is critical for the diagnosis, treatment, and prognosis of the disease. There are numerous databases and applications with which to archive mutation data. However, none of them have been implemented with any automated bioinformatics tools for mutation detection and analysis starting from raw data materials from patients. We present a Locus Specific mutation DB (LSDB) construction system that supports both mutation detection and deposition in one package. RESULTS: COMUS (Clinician-Oriented locus specific MUtation detection and deposition System) is a mutation detection and deposition system for developing specific LSDBs. COMUS contains 1) a DNA sequence mutation analysis method for clinicians' mutation data identification and deposition and 2) a curation system for variation detection from clinicians' input data. To embody the COMUS system and to validate its clinical utility, we have chosen the disease hemophilia as a test database. A set of data files from bench experiments and clinical information from hemophilia patients were tested on the LSDB, KoHemGene http://www.kohemgene.org, which has proven to be a clinician-friendly interface for mutation detection and deposition. CONCLUSION: COMUS is a bioinformatics system for detecting and depositing new mutations from patient DNA with a clinician-friendly interface. LSDBs made using COMUS will promote the clinical utility of LSDBs. COMUS is available at http://www.comus.info.

Gevab: a prototype genome variation analysis browsing server.

BACKGROUND: The first Korean individual diploid genome sequence data (KOREF) was publicized in December 2008. RESULTS: A Korean genome variation analysis and browsing server (Gevab) was constructed as a database and web server for the exploration and downloading of Korean personal genome(s). Information in the Gevab includes SNPs, short indels, and structural variation (SV) and comparison analysis between the NCBI human reference and the Korean genome(s). The user can find information on assembled consensus sequences, sequenced short reads, genetic variations, and relationships between genotype and phenotypes. CONCLUSION: This server is openly and publicly available online at http://koreagenome.org/en/ or directly http://gevab.org.

Mapping human genetic diversity in Asia.

Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.

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

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.

Planning the human variome project: the Spain report.

The remarkable progress in characterizing the human genome sequence, exemplified by the Human Genome Project and the HapMap Consortium, has led to the perception that knowledge and the tools (e.g., microarrays) are sufficient for many if not most biomedical research efforts. A large amount of data from diverse studies proves this perception inaccurate at best, and at worst, an impediment for further efforts to characterize the variation in the human genome. Because variation in genotype and environment are the fundamental basis to understand phenotypic variability and heritability at the population level, identifying the range of human genetic variation is crucial to the development of personalized nutrition and medicine. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) was proposed initially to systematically collect mutations that cause human disease and create a cyber infrastructure to link locus specific databases (LSDB). We report here the discussions and recommendations from the 2008 HVP planning meeting held in San Feliu de Guixols, Spain, in May 2008.