Natural variation in human membrane transporter genes reveals evolutionary and functional constraints
Abstract
Membrane transporters maintain cellular and organismal homeostasis by importing nutrients and exporting toxic compounds. Transporters also play a crucial role in drug response, serving as drug targets and setting drug levels. As part of a pharmacogenetics project, we screened exons and flanking intronic regions for variation in a set of 24 membrane transporter genes (96 kb; 57% coding) in 247 DNA samples from ethnically diverse populations. We identified 680 single nucleotide polymorphisms (SNPs), of which 175 were synonymous and 155 caused amino acid changes, and 29 small insertions and deletions. Amino acid diversity (πNS) in transmembrane domains (TMDs) was significantly lower than in loop domains, suggesting that TMDs have special functional constraints. This difference was especially striking in the ATP-binding cassette superfamily and did not parallel evolutionary conservation: there was little variation in the TMDs, even in evolutionarily unconserved residues. We used allele frequency distribution to evaluate different scoring systems (Grantham, BLOSUM62, SIFT, and evolutionarily conserved/evolutionarily unconserved) for their ability to predict which SNPs affect function. Our underlying assumption was that alleles that are functionally deleterious will be selected against and thus under represented at high frequencies and over represented at low frequencies. We found that evolutionary conservation of orthologous sequences, as assessed by evolutionarily conserved/evolutionarily unconserved and SIFT, was the best predictor of allele frequency distribution and hence of function. European Americans had an excess of high frequency alleles in comparison to African Americans, consistent with a historic bottleneck. In addition, African Americans exhibited a much higher frequency of population specific medium-frequency alleles than did European Americans.
- Publication:
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Proceedings of the National Academy of Science
- Pub Date:
- May 2003
- DOI:
- 10.1073/pnas.0730857100
- Bibcode:
- 2003PNAS..100.5896L
- Keywords:
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- Genetics