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Genetics, Vol. 158, 1657-1664, August 2001, Copyright © 2001

Excess of Rare Amino Acid Polymorphisms in the Toll-like Receptor 4 in Humans

Irina Smirnovaa, Martha T. Hamblinb, Colleen McBridea, Bruce Beutlera, and Anna Di Rienzob
a Department of Internal Medicine and the Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390
b Department of Human Genetics, University of Chicago, Chicago, Illinois 60637

Corresponding author: Bruce Beutler, The Scripps Research Institute, Department of Immunology (IMM-31), 10550 N. Torrey Pines Rd., La Jolla, CA 92037., bruce{at}scripps.edu (E-mail)

Communicating editor: D. CHARLESWORTH

The Toll-like receptor 4 protein acts as the transducing subunit of the lipopolysaccharide receptor complex and assists in the detection of Gram-negative pathogens within the mammalian host. Several lines of evidence support the view that variation at the TLR4 locus may alter host susceptibility to Gram-negative infection or the outcome of infection. Here, we surveyed TLR4 sequence variation in the complete coding region (2.4 kb) in 348 individuals from several population samples; in addition, a subset of the individuals was surveyed at 1.1 kb of intronic sequence. More than 90% of the chromosomes examined encoded the same structural isoform of TLR4, while the rest harbored 12 rare amino acid variants. Conversely, the variants at silent sites (intronic and synonymous positions) occur at both low and high frequencies and are consistent with a neutral model of mutation and random drift. The spectrum of allele frequencies for amino acid variants shows a significant skew toward lower frequencies relative to both the neutral model and the pattern observed at linked silent sites. This is consistent with the hypothesis that weak purifying selection acted on TLR4 and that most mutations affecting TLR4 protein structure have at least mildly deleterious phenotypic effects. These results may imply that genetic variants contributing to disease susceptibility occur at low frequencies in the population and suggest strategies for optimizing the design of disease-mapping studies.





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