Discovering functional DNA elements using population genomic information: A proof of concept using human mtDNA

Abstract

Identifying the complete set of functional elements within the human genome would be a windfall for multiple areas of biological research including medicine, molecular biology, and evolution. Complete knowledge of function would aid in the prioritization of loci when searching for the genetic bases of disease or adaptive phenotypes. Because mutations that disrupt function are disfavored by natural selection, purifying selection leaves a detectable signature within functional elements; accordingly this signal has been exploited through the use of genomic comparisons of distantly related species. However, the functional complement of the genome changes extensively across time and between lineages, therefore, evidence of the current action of purifying selection is essential. Because the removal of deleterious mutations by natural selection also reduces within-species genetic diversity within functional loci, dense population genetic data have the potential to reveal genomic elements that are currently functional. Here we assess the potential of this approach using 16,411 human mitochondrial genomes. We show that the high density of polymorphism in this dataset precisely delineates regions experiencing purifying selection. Further, we show that the number of segregating alleles at a site is strongly correlated with its divergence across species after accounting for known mutational biases in human mtDNA. These two measures track one another at a remarkably fine scale across many loci--a correlation that is purely the result of natural selection. Our results demonstrate that genetic variation has the potential to reveal exactly which nucleotides in the genome are currently performing important functions and likely to have deleterious fitness effects when mutated. As more complete genomes are sequenced, similar power to reveal purifying selection may be achievable in the human nuclear genome.