An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data

English version

Autoři: Aaron J. Stern ^aff001; Peter R. Wilton ^aff002; Rasmus Nielsen ^aff002
Působiště autorů: Graduate Group in Computation Biology, University of California, Berkeley, Berkeley, California, United States of America ^aff001; Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America ^aff002; Department of Statistics, University of California, Berkeley, Berkeley, California, United States of America ^aff003
Vyšlo v časopise: An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data. PLoS Genet 15(9): e32767. doi:10.1371/journal.pgen.1008384
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008384

Souhrn

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method CLUES treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele’s age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1.

Klíčová slova:

Biology and life sciences – Evolutionary biology – Evolutionary systematics – Phylogenetics – Phylogenetic analysis – Evolutionary processes – Natural selection – Taxonomy – Genetics – Heredity – Genetic mapping – Haplotypes – Molecular genetics – Population biology – Population dynamics – Geographic distribution – Molecular biology – Computer and information sciences – Data management – Physical sciences – Mathematics – Probability theory – Markov models – Hidden Markov models – Research and analysis methods – Simulation and modeling – People and places – Geographical locations – Europe

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