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The public SNP databases are an important resource for groups performing genetic association and linkage studies. Both academic and commercial groups are developing large numbers of genotyping assays for SNPs in candidate genes or spread across the genome. These databases now contain in excess of 6 million SNPs that have been generated using a large number of methods and cohorts. Today, however, only a small fraction of these SNPs are well characterized and validated. The latest release of dbSNP contains approximately 3.7 million non-redundant entries, only 0.5 million of which are validated, and 0.2 million of which have frequency information. Users of these databases have several common questions. How many of the SNPs are real? What is the frequency spectrum of the SNPs in these databases? What is the distribution picture of these SNPs across different ethnic and geographical populations? What fraction of the total number of SNPs is already captured by these databases? In order to address these questions, we compared the public SNPs against a well-characterized collection of gene-centric SNPs that we have developed. From this comparison, we find that > 50% of high frequency SNPs in the genome (> 20% minor allele frequency) have already been captured by these databases. The coverage drops dramatically below frequencies of 10%. At high frequencies, there is no sampling bias with respect to ethnicity or to regions of the genome. Finally, a relatively large fraction (> 40%) of SNPs in these databases were not seen in our study, which means that they are either of very low frequency, mismapped, or not polymorphic at all.

We have surveyed and summarized several aspects of DNA variability among humans. The variation described is the result of mutation followed by a combination of drift, migration and selection bringing the frequencies high enough to be observed. This paper describes what we have learned about how DNA variability differs among genes and populations. We sequenced functional regions of a set of 3950 genes. DNA was sampled from 82 unrelated humans: 20 African-Americans, 20 East Asians, 21 Caucasians, 18 Hispanic-Latinos and 3 Native Americans. Different aspects of variability showed a great deal of concordance. In particular, we studied patterns of single nucleotide polymorphism (SNP) allele and haplotype sharing among the four, large sample populations. We also examined how linkage disequilibrium (LD) between SNPs relates to physical distance in the different populations. It is clear from our findings that while many variants are common to all populations, many others have a more restricted distribution. Research that attempts to find genetic variants that explain phenotypic variants must be careful in their choice of study population.

Recognition that there is a vast quantity of human genetic variation has had a pervasive impact on modern medicine, facilitating the identification of scores of genes that underlie monogenic clinical disorders, as well as genes involved in complex disease processes. The next logical step for human genetics is the exploration and elucidation of genes involved in differential pharmacological response: responders, nonresponders, and those with adverse side effects. An understanding of the role that genes have in pharmacological response is the cornerstone of personalized medicine. Pharmacogenetic activities have swiftly embraced these tenets, leading to a proliferation of resources and approaches meant to enable and expedite targeted drug discovery and development. To realize the potential of these efforts, it will be necessary to incorporate a better understanding of the population genetic and evolutionary processes that have shaped genetic variation in modern humans. This article introduces these concepts to provide context and guidelines for the use of this variation (primarily single-nucleotide polymorphisms and haplotypes) in pharmacogenetics.

The human genome has already been the subject of extensive research activity even though the Human Genome Project is only just officially starting. This review and the accompanying wall chart attempt to provide an integrated, quantitative, and detailed summary of the status of knowledge on the human genome in mid-1990. The analysis has highlighted the rudimentary nature of many of the information links needed for the task. While this overview could not be fully comprehensive and required simplifying assumptions, the results have provided estimates of relative progress on a region-by-region basis throughout the genome.