A method for genome-wide genealogy estimation for thousands of samples

Abstract

Knowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We developed a method, Relate, scaling to > 10,000 sequences while simultaneously estimating branch lengths, mutational ages, and variable historical population sizes, as well as allowing for data errors. Application to 1000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations. Highly diverged lineages are present in all groups, but most frequent in Africa. Outside Africa, these mainly reflect ancient introgression from groups related to Neanderthals and Denisovans, while African signals instead reflect unknown events, unique to that continent. Our approach allows more powerful inferences of natural selection than previously possible. We identify multiple novel regions under strong positive selection, and multi-allelic traits including hair colour, BMI, and blood pressure, showing strong evidence of directional selection, varying among human groups.Large-scale genetic variation datasets are now available for a variety of species, including tens of thousands of humans. In principle, all information about a sample's genetic history is captured by their underlying genealogical history, which records the historical coalescence, recombination, and mutation events that produced the observed variation patterns. In practice, several key existing approaches (e.g., Refs. [1,2]) leverage an underlying coalescent model, because this provides a flexible modelling framework and is the limiting behaviour of a variety of finite-population models 3,4 . However, inference under the coalescent is complicated by the structure of the model, uncertainty over the correct genealogy conditional on observed data, and the large resulting space of possible sample histories 5 . Other approaches 6-11 use more heuristic approximations to the coalescent, sometimes reducing accuracy: regardless, all published existing methods scale to tens or a few hundred samples at most.As a result of these issues, the use of direct genealogy-based inference to detect recombination events, date mutations, and reveal evidence of positive selection has been limited to smaller datasets 1,2 , while for larger datasets approaches based on data summaries 12-14 or downsampling 15,16 have predominated. A diverse set of tools have detected genetic structure that is in good agreement with geopolitical separation over generations 17 .Admixtures of ancient populations have been identified and dated 18 . Other applications have found bottlenecks in population sizes that are consistent with anthropological evidence of initial human migration from the African continent 15,19-21 and evidence of subsequent introgression with archaic humans, such as Neanderthals 22 .We have developed a scalable method, Relate, to estimate genome-wide genealogies (see Figure 1; Methods;URLs for implementation). Relate separates two steps; firstly identifying a genealogical fra...

The spatiotemporal spread of human migrations during the European Holocene

“…These subtle patterns are hard to pick up by simple latent mixed-membership models (34), although there has recently been some progress in this regard (60,61). Other types of population-genetic frameworks are able to better detect some of these more subtle signals by, for example, modeling patterns of haplotype sharing (62,63), the full site-frequency spectrum (64,65), or an approximation to the full ancestral recombination graph (66,67). Nevertheless, these also have their own limitations and assumptions.…”

Inference of natural selection from ancient DNA

“…2019; Speidel et al. 2019) together with an accompanying perspective (Harris 2019) introduce new methods, relate and tsinfer , which estimate genealogies in the presence of recombination at an unprecedented scale. Recombination events result in small differences in the genealogy of contiguous sequences; tsinfer records these differences thereby efficiently encoding variation across the genomes of thousands of individuals.…”

Mutational signatures of replication timing and epigenetic modification persist through the global divergence of mutation spectra across the great ape phylogeny

“…10,000 to 20,000 years, Europeans experienced a temporary pulse of mutagenic activity that 72 more than doubled the rate of TCC>TTC mutations (Harris, 2015;Speidel et al, 2019). 73 74…”