Dating genomic variants and shared ancestry in population-scale sequencing data

The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while previous efforts have been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a non-parametric approach for estimating the date of origin of genetic variants that can be applied to large-scale genomic variation data sets. We demonstrate the accuracy and robustness of the approach through simulation and apply it to over 16 million single nucleotide polymorphisms (SNPs) from two publicly available human genomic diversity resources. We characterize the differential relationship between variant frequency and age in different geographical regions and demonstrate the value of allele age in interpreting variants of known functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the genealogical history of a single genome or a group of individuals.