Stephen T. Sherry

dbSNP: the NCBI database of genetic variation

In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Center for Biotechnology Information (NCBI) has established the dbSNP database [S.T.Sherry, M.Ward and K. Sirotkin (1999) Genome Res., 9, 677-679]. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. The complete contents of dbSNP can also be downloaded in multiple formats via anonymous FTP at ftp://ncbi.nlm.nih.gov/snp/.

The variant call format and VCFtools

Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: rd@sanger.ac.uk

The NCBI dbGaP database of genotypes and phenotypes

The National Center for Biotechnology Information has created the dbGaP public repository for individual-level phenotype, exposure, genotype and sequence data and the associations between them. dbGaP assigns stable, unique identifiers to studies and subsets of information from those studies, including documents, individual phenotypic variables, tables of trait data, sets of genotype data, computed phenotype-genotype associations, and groups of study subjects who have given similar consents for use of their data.

ClinGen — The Clinical Genome Resource

On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography. Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data. A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic. Family members are retested, and one member who previously tested negative is now found to be positive for this new variant. An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death.

dbSNP: a database of single nucleotide polymorphisms

In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Cancer for Biotechnology Information (NCBI) has established the dbSNP database. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. Submitted SNPs can also be downloaded via anonymous FTP at ftp://ncbi.nlm.nih.gov/snp/

New models of collaboration in genome-wide association studies: the Genetic Association Information Network.

The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

The Allele Frequency Spectrum in Genome-Wide Human Variation Data Reveals Signals of Differential Demographic History in Three Large World Populations

We have studied a genome-wide set of single-nucleotide polymorphism (SNP) allele frequency measures for African-American, East Asian, and European-American samples. For this analysis we derived a simple, closed mathematical formulation for the spectrum of expected allele frequencies when the sampled populations have experienced nonstationary demographic histories. The direct calculation generates the spectrum orders of magnitude faster than coalescent simulations do and allows us to generate spectra for a large number of alternative histories on a multidimensional parameter grid. Model-fitting experiments using this grid reveal significant population-specific differences among the demographic histories that best describe the observed allele frequency spectra. European and Asian spectra show a bottleneck-shaped history: a reduction of effective population size in the past followed by a recent phase of size recovery. In contrast, the African-American spectrum shows a history of moderate but uninterrupted population expansion. These differences are expected to have profound consequences for the design of medical association studies. The analytical methods developed for this study, i.e., a closed mathematical formulation for the allele frequency spectrum, correcting the ascertainment bias introduced by shallow SNP sampling, and dealing with variable sample sizes provide a general framework for the analysis of public variation data.

The structure of human mitochondrial DNA variation

SummaryRestriction analysis of mitochondrial DNA (mtDNA) of 3065 humans from 62 geographic samples identified 149 haplotypes and 81 polymorphic sites. These data were used to test several aspects of the evolutionary past of the human species. A dendrogram depicting the genetic relatedness of all haplotypes shows that the native African populations have the greatest diversity and, consistent with evidence from a variety of sources, suggests an African origin for our species. The data also indicate that two individuals drawn, at random from the entire sample will differ at approximately 0.4% of their mtDNA nucleotide sites, which is somewhat higher than previous estimates. Human mtDNA also exhibits more interpopulation heterogeneity (GST=0.351±0.025) than does nuclear DNA (GST=0.12). Moreover, the virtual absence of intermediate levels of linkage disequilibrium between pairs of sites is consistent with the absence of genetic recombination and places constraints on the rate of mutation. Tests of the selective neutrality of mtDNA variation, including the Ewens-Watterson and Tajima tests, indicate a departure in the direction consistent with purifying selection, but this departure is more likely due to the rapid growth of the human population and the geographic heterogeneity of the variation. The lack of a good fit to neutrality poses problems for the estimation of times of coalescence from human mtDNA data.

Completing the map of human genetic variation

Large-scale studies of human genetic variation have focused largely on understanding the pattern and nature of single-nucleotide differences within the human genome. Recent studies that have identified larger polymorphisms, such as insertions, deletions and inversions, emphasize the value of investing in more comprehensive and systematic studies of human structural genetic variation. We describe a community resource project recently launched by the National Human Genome Research Institute (NHGRI) to sequence large-insert clones from many individuals, systematically discovering and resolving these complex variants at the DNA sequence level. The project includes the discovery of variants through development of clone resources, sequence resolution of variants, and accurate typing of variants in individuals of African, European or Asian ancestry. Sequence resolution of both single-nucleotide and larger-scale genomic variants will improve our picture of natural variation in human populations and will enhance our ability to link genetics and human health.

The 1000 Genomes Project: data management and community access

The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access.