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Comparative Study
. 2007 Apr;80(4):727-39.
doi: 10.1086/513473. Epub 2007 Mar 8.

Most rare missense alleles are deleterious in humans: implications for complex disease and association studies

Affiliations
Comparative Study

Most rare missense alleles are deleterious in humans: implications for complex disease and association studies

Gregory V Kryukov et al. Am J Hum Genet. 2007 Apr.

Abstract

The accumulation of mildly deleterious missense mutations in individual human genomes has been proposed to be a genetic basis for complex diseases. The plausibility of this hypothesis depends on quantitative estimates of the prevalence of mildly deleterious de novo mutations and polymorphic variants in humans and on the intensity of selective pressure against them. We combined analysis of mutations causing human Mendelian diseases, of human-chimpanzee divergence, and of systematic data on human genetic variation and found that ~20% of new missense mutations in humans result in a loss of function, whereas ~27% are effectively neutral. Thus, the remaining 53% of new missense mutations have mildly deleterious effects. These mutations give rise to many low-frequency deleterious allelic variants in the human population, as is evident from a new data set of 37 genes sequenced in >1,500 individual human chromosomes. Surprisingly, up to 70% of low-frequency missense alleles are mildly deleterious and are associated with a heterozygous fitness loss in the range 0.001-0.003. Thus, the low allele frequency of an amino acid variant can, by itself, serve as a predictor of its functional significance. Several recent studies have reported a significant excess of rare missense variants in candidate genes or pathways in individuals with extreme values of quantitative phenotypes. These studies would be unlikely to yield results if most rare variants were neutral or if rare variants were not a significant contributor to the genetic component of phenotypic inheritance. Our results provide a justification for these types of candidate-gene (pathway) association studies and imply that mutation-selection balance may be a feasible evolutionary mechanism underlying some common diseases.

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Figures

Figure  1.
Figure 1.
Spectrum of effects of de novo missense mutations. A, Fraction of strongly detrimental mutations among de novo amino acid substitutions. Disease-causing nonsense mutations in HGMD were used as a standard of “strong detrimentality.” B, Fraction of strongly detrimental mutations among de novo amino acid substitutions. Disease-causing splice-site mutations in HGMD were used as a standard of “strong detrimentality.” C, Fraction of effectively neutral mutations among de novo amino acid substitutions. Synonymous substitutions fixed in the human lineage after divergence from chimpanzee were used as a standard of “effective neutrality.”
Figure  2.
Figure 2.
Fraction of de novo missense mutations represented at different levels of allele frequency. The normalized fraction of de novo amino acid substitutions detected in a given data set was calculated from the difference of observed Na/Ns ratio and theoretical N0a/N0s ratio expected under neutrality. Data for rare polymorphisms are shown in orange, data for common polymorphisms are in yellow, and data for substitutions (subst.) fixed in the human lineage after divergence from chimpanzee are in green. SEs are shown by gray error bars.
Figure  3.
Figure 3.
A, R1/m(s) and RMAF>0.25(s) (see eq. [1]) calculated using equations derived from diffusion theory under the assumption of constant population size and an infinite number of sites. The expected shift of R1/m(s) curves due to recent population expansion is shown by red arrows. Black arrows illustrate estimation of characteristic selection coefficients for a mildly deleterious class of missense mutations (see the “Results” section and eq. [2]). B, R1/m(s) and RMAF>0.25(s) calculated by direct computer simulation of molecular evolution under the assumption of an infinite number of sites and simple population history—a stable-population-size epoch followed by bottleneck and then fast expansion.

References

Web Resources

    1. Consensus CDS (CCDS) Project, http://www.ncbi.nlm.nih.gov/CCDS/
    1. dbSNP, http://www.ncbi.nlm.nih.gov/SNP/
    1. Human Gene Mutation Database (HGMD), http://www.hgmd.cf.ac.uk/ac/index.php
    1. JSNP, http://snp.ims.u-tokyo.ac.jp/ (for database of Japanese SNPs)
    1. NIEHS SNPs Program, http://egp.gs.washington.edu/

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