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

Abstract

The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has 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 nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single-nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes and to quantify genealogical relationships at different points in the past, as well as to describe and explore the evolutionary history of modern human populations.

A variant-centric perspective on geographic patterns of human allele frequency variation

“…The patterns observed here are interpretable in light of some basic principles of population genetics. Rare variants are typically the result of recent mutations ( Mathieson and McVean, 2014 ; Kiezun et al, 2013 ; Kimura and Ohta, 1973 ; Albers and McVean, 2020 ). Thus, we interpret the localized rare variants (such as ‘Ruuuu’ or ‘uuuRu’) as mostly young mutations that have not had time to spread geographically.…”

“…Another future direction would be to shift from visualizing patterns of allele sharing to the patterns of sharing of ancestral lineages in coalescent genealogies. Recent advances in the inference of genome-wide tree sequences ( Kelleher et al, 2019 ; Speidel et al, 2019 ) and allele ages ( Albers and McVean, 2020 ) allow for quantitative summaries of ancestral lineage sharing. Such quantities have a close relationship to the multi-population SFS properties that are studied here, yet are more fundamental in a sense and less subject to the stochasticity of the mutation process.…”

Shared ancestral polymorphisms and chromosomal rearrangements as potential drivers of local adaptation in a marine fish

“…Kern & Schrider, 2018). Further use of coalescent methods would also allow us to directly infer the age of the variants relative to the most recent common ancestor of the lineage (Albers & McVean, 2020).…”

Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations

“…For each previously reported gene-phenotype association, we identified all sequenced individuals with a rare LoF variant (mirroring the definition of LoF from Van Hout et al 49 ) and any IBD segments they shared with individuals in the non-sequenced cohort (we refer to these as putative LoF-segments, though they will also include sharing of the non-LoF haplotypes because the phase of the LoF is unknown). As expected due to the effects of natural selection 54 , the LoF variants belonging to a small subset for which an age estimate has recently been computed 55 are slightly younger than other exome-sequenced variants (Supplementary Table 6 ). Note that the majority of these variants are singletons or doubletons 49 and would be excluded from imputation by most current algorithms 56 .…”