The Signature of Positive Selection on Standing Genetic Variation

Abstract

Considerable interest is focused on the use of polymorphism data to identify regions of the genome that underlie recent adaptations. These searches are guided by a simple model of positive selection, in which a mutation is favored as soon as it arises. This assumption may not be realistic, as environmental changes and range expansions may lead previously neutral or deleterious alleles to become beneficial. We examine what effect this mode of selection has on patterns of variation at linked neutral sites by implementing a new coalescent model of positive directional selection on standing variation. In this model, a neutral allele arises and drifts in the population, then at frequency f becomes beneficial, and eventually reaches fixation. Depending on the value of f, this scenario can lead to a large variance in allele frequency spectra and in levels of linkage disequilibrium at linked, neutral sites. In particular, for intermediate f, the beneficial substitution often leads to a loss of rare alleles--a pattern that differs markedly from the signature of directional selection currently relied on by researchers. These findings highlight the importance of an accurate characterization of the effects of positive selection, if we are to reliably identify recent adaptations from polymorphism data.

Divergent patterns of linkage disequilibrium and haplotype structure across global populations at the interleukin-13 (IL13) locus

“…16,52,53 However, our simulations have also demonstrated that even very small levels of population substructure (F ST ¼ 0.01) can result in a negative skew in the distribution of Fay and Wu's H values, such that we can no longer reject neutrality. Therefore, population structure could be an alternative explanation for the observed significant H values in the current study and in the study of Zhou et al, 10 which is consistent with results of simulations by Wakeley and Aliacar, 54 and Przeworski 42 showing the effects of migration on Fay and Wu's H statistic. Our results suggest that one must consider demographic history, including population expansion and substructure, when testing for signatures of natural selection.…”

“…Our simulations show that population structure skews the distribution of H towards negative values (although the mean value of H remains nearly the same), and this effect is more accentuated as F ST increases (ie number of migrants decreases), in agreement with Przeworski. 42 The observed F ST for the two European groups considered in this study (North European and Russian) is 0.07 (although not significantly different from zero) and is 0.024 for the two East African groups (Hadza and Maasai). When we consider an F ST value as low as 0.01, the 95% confidence interval for H in the Europeans was (À5.90, 3.57), and for East Africans was (À6.23, 4.22) for the observed level of recombination in these populations ( Table 1).…”

“…Przeworski 42 has shown that the H statistic is sensitive to population structure. Therefore, we also tested the significance of the H values against null hypotheses that incorporate different levels of population structure (see Materials and methods for details).…”

“…The H test is informative for detecting positive directional selection, although it is also sensitive to the effects of population substructure. 42 In the case of D*, F* and H tests, we use the chimpanzee sequence as an outgroup and, thus, we include information about ancestral and derived states of polymorphisms. We tested the significance of these statistics using coalescent simulations conditioning on estimators of the parameter y (5000 repetitions).…”

Molecular population genetics of SLC4A1 and Southeast Asian Ovalocytosis

“…22 In addition, several studies have shown that some demographic scenarios can also cause negative skews in Fay and Wu's H. 42,43 To distinguish between these two possible causes of the pattern, it is useful to consider the pattern of polymorphism in the Memphis genomic region in a wider variety of human populations. Examination of HapMap (phase 3) SNP data from our resequenced region shows five overlapping SNPs that have been genotyped in 10 world populations (excluding the Japanese), including three where the derived allele is at high frequency in our sample (Supplementary Table S2).…”