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Characterization of single-nucleotide polymorphisms in coding regions of human genes

doi: 10.1038/10290
pmid: 10391209
Characterization of single-nucleotide polymorphisms in coding regions of human genes
A major goal in human genetics is to understand the role of common genetic variants in susceptibility to common diseases. This will require characterizing the nature of gene variation in human populations, assembling an extensive catalogue of single-nucleotide polymorphisms (SNPs) in candidate genes and performing association studies for particular diseases. At present, our knowledge of human gene variation remains rudimentary. Here we describe a systematic survey of SNPs in the coding regions of human genes. We identified SNPs in 106 genes relevant to cardiovascular disease, endocrinology and neuropsychiatry by screening an average of 114 independent alleles using 2 independent screening methods. To ensure high accuracy, all reported SNPs were confirmed by DNA sequencing. We identified 560 SNPs, including 392 coding-region SNPs (cSNPs) divided roughly equally between those causing synonymous and non-synonymous changes. We observed different rates of polymorphism among classes of sites within genes (non-coding, degenerate and non-degenerate) as well as between genes. The cSNPs most likely to influence disease, those that alter the amino acid sequence of the encoded protein, are found at a lower rate and with lower allele frequencies than silent substitutions. This likely reflects selection acting against deleterious alleles during human evolution. The lower allele frequency of missense cSNPs has implications for the compilation of a comprehensive catalogue, as well as for the subsequent application to disease association.
- Massachusetts General Hospital United States
- Massachusetts Institute of Technology United States
Polymorphism, Genetic, Gene Frequency, Genes, Genetic Variation, Humans, Proteins, Sequence Analysis, DNA, Biological Evolution, Alleles
Polymorphism, Genetic, Gene Frequency, Genes, Genetic Variation, Humans, Proteins, Sequence Analysis, DNA, Biological Evolution, Alleles
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