AbstractWhile there has been extensive work on patterns of linkage disequilibrium (LD) for neutral loci, the extent to which negative selection impacts LD is less clear. Forces like Hill-Robertson interference and negative epistasis are expected to lead to deleterious mutations being found on distinct haplotypes. However, the extent to which these forces depend on the selection and dominance coefficients of deleterious mutations and shape genome-wide patterns of LD in natural populations with complex demographic histories has not been tested. In this study, we first used forward-in-time simulations to generate predictions as to how selection impacts LD. Under models where deleterious mutations have additive effects on fitness, deleterious variants less than 10 kb apart tend to be carried on different haplotypes, generating an excess of negative LD relative to pairs of synonymous SNPs. In contrast, for recessive mutations, there is no consistent ordering of how selection coefficients affect r2 decay. We then examined empirical data of modern humans from the 1000 Genomes Project. LD between derived nonsynonymous SNPs is more negative compared to pairs of derived synonymous variants. This result holds when matching SNPs for frequency in the sample (allele count), physical distance, magnitude of background selection, and genetic distance between pairs of variants, suggesting that this result is not due to these potential confounding factors. Lastly, we introduce a new statistic HR(j) which allows us to detect interference using unphased genotypes. Application of this approach to high-coverage human genome sequences confirms our finding that deleterious alleles tend to be located on different haplotypes more often than are neutral alleles. Our findings suggest that either interference or negative epistasis plays a pervasive role in shaping patterns of LD between deleterious variants in the human genome, and consequently influencing genome-wide patterns of LD.
Approximately independent linkage disequilibrium blocks in human populations
