Abstract
Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence—because they share a most recent common ancestor—when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection.
Highlights
There is a growing awareness that the genomic sequences available for closely related species or sub-species may provide detailed information on the population genetics process in the ancestors of these species and about the speciation process itself [1]
We present a hidden Markov model that uses variation in coalescence times between two distantly related populations, or closely related species, to infer population genetics parameters in ancestral population or species
We show that the model accurately estimates the divergence time between the two populations and the effective population size of the ancestral population
Summary
There is a growing awareness that the genomic sequences available for closely related species or sub-species may provide detailed information on the population genetics process in the ancestors of these species and about the speciation process itself [1]. This is because the divergence patterns of a set of (sub-)species vary along their genomes due to polymorphism in the ancestral species. Takahata [9] showed that including an outgroup improved the results, and Yang [10] showed that mutation rate heterogeneity is confounded with the estimate These early approaches estimated a fixed phylogeny for different sequence fragments. Wall [11] allowed for recombination and several species in the likelihood estimation of population parameters and Patterson et al [2], Hobolth et al [5], and Dutheil et al [12] made simple models of changes in genealogy along a multi-species alignment with incomplete lineage sorting
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