  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.
