Simultaneous inference of selection and population growth from patterns of variation in the human genome

Abstract

Natural selection and demographic forces can have similar effects on patterns of DNA polymorphism. Therefore, to infer selection from samples of DNA sequences, one must simultaneously account for demographic effects. Here we take a model-based approach to this problem by developing predictions for patterns of polymorphism in the presence of both population size change and natural selection. If data are available from different functional classes of variation, and a priori information suggests that mutations in one of those classes are selectively neutral, then the putatively neutral class can be used to infer demographic parameters, and inferences regarding selection on other classes can be performed given demographic parameter estimates. This procedure is more robust to assumptions regarding the true underlying demography than previous approaches to detecting and analyzing selection. We apply this method to a large polymorphism data set from 301 human genes and find (i) widespread negative selection acting on standing nonsynonymous variation, (ii) that the fitness effects of nonsynonymous mutations are well predicted by several measures of amino acid exchangeability, especially site-specific methods, and (iii) strong evidence for very recent population growth.

Fig. 1.

The normalized site-frequency spectra of noncoding, synonymous, and nonsynonymous SNPs discovered in a set of 301 human genes sequenced in 90 individuals, represented as the expected site-frequency spectra of a subsample of size 40. Nonsynonymous SNPs show a relative excess of SNPs with rare alleles. Also note the slight excess of very high-frequency variants, which we explain by ancestral misspecification.

Fig. 2.

The sampling distribution of the scaled selection parameter (2N_As)(a) and the likelihood ratio test statistic (b), under selective neutrality (2N_As = 0) for a variety of demographic models. Note that, for ease of comparison among models, the selection parameter is scaled relative to the ancestral, rather than the current, population size. The heavy black line in b represents the χ² distribution with one degree of freedom.