Published January 18, 2018 | Version v1
Journal article Open

Estimating Time to the Common Ancestor for a Beneficial Allele

  • 1. University of Chicago
  • 2. University of California, Davis

Description

The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele's age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the surrounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to approaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.

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Additional details

Identifiers

DOI
10.1093/molbev/msy006
Other
oai:uchicago.tind.io:5757

Related works

Funding

National Science Foundation
Graduate Research Fellowship
National Institute of General Medical Sciences
DGE-1144082
National Institute of General Medical Sciences
T32GM007197
National Institute of General Medical Sciences
RO1GM83098
National Institute of General Medical Sciences
RO1GM107374
National Institute of General Medical Sciences
R01HG007089

UChicago Information

Division(s)
Biological Sciences Division, Physical Sciences Division
Department(s)
Ecology and Evolution, Human Genetics, Statistics