Pervasive hitchhiking at coding and regulatory sites in humans

Abstract

Much effort and interest have focused on assessing the importance of natural selection, particularly positive natural selection, in shaping the human genome. Although scans for positive selection have identified candidate loci that may be associated with positive selection in humans, such scans do not indicate whether adaptation is frequent in general in humans. Studies based on the reasoning of the MacDonald-Kreitman test, which, in principle, can be used to evaluate the extent of positive selection, suggested that adaptation is detectable in the human genome but that it is less common than in Drosophila or Escherichia coli. Both positive and purifying natural selection at functional sites should affect levels and patterns of polymorphism at linked nonfunctional sites. Here, we search for these effects by analyzing patterns of neutral polymorphism in humans in relation to the rates of recombination, functional density, and functional divergence with chimpanzees. We find that the levels of neutral polymorphism are lower in the regions of lower recombination and in the regions of higher functional density or divergence. These correlations persist after controlling for the variation in GC content, density of simple repeats, selective constraint, mutation rate, and depth of sequencing coverage. We argue that these results are most plausibly explained by the effects of natural selection at functional sites -- either recurrent selective sweeps or background selection -- on the levels of linked neutral polymorphism. Natural selection at both coding and regulatory sites appears to affect linked neutral polymorphism, reducing neutral polymorphism by 6% genome-wide and by 11% in the gene-rich half of the human genome. These findings suggest that the effects of natural selection at linked sites cannot be ignored in the study of neutral human polymorphism.

Figure 1. Correlations between recombination rate and neutral divergence rate and neutral polymorphism.

Scatter plots display values of two variables in orange dots for (A) recombination rate and the level of neutral divergence rate (d_neu), (B) recombination rate and the level of neutral polymorphism (θ_neu), and (C) recombination rate and the level of normalized neutral polymorphism (P_neu = θ_neu/d_neu). Black circles are average values for orange dots pooled in 100 bins each containing 1% of the data points.

Figure 2. Relationships among the levels of functional density and neutral polymorphism.

Scatter plots display values of two variables in orange dots for (A) the number of codons (FD_n) and the level of neutral polymorphism (θ_neu), (B) the number of conserved noncoding sites (FD_x) and the level of neutral polymorphism (θ_neu), (C) the number of codons (FD_n) and the level of normalized neutral polymorphism (P_neu = θ_neu/d_neu), and (D) the number of conserved noncoding sites (FD_x) and the level of normalized neutral polymorphism (P_neu = θ_neu/d_neu). Black circles are average values for orange dots pooled in 100 bins each containing 1% of the data points.

Figure 3. Relationships among the levels of functional divergence and neutral polymorphism.

Scatter plots display values of two variables in orange dots for (A) the divergence at coding sites (D_n) and the level of neutral polymorphism (θ_neu), (B) the divergence at conserved noncoding region (D_x) and the level of neutral polymorphism (θ_neu), (C) the divergence at coding sites (D_n) and the level of normalized neutral polymorphism (P_neu = θ_neu/d_neu), and (D) the divergence at conserved noncoding region (D_x) and the level of normalized neutral polymorphism (P_neu = θ_neu/d_neu). Black circles are average values for orange dots pooled in 100 bins each containing 1% of the data points.