Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have b...

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Main Authors: Simon Boitard, Willy Rodríguez, Flora Jay, Stefano Mona, Frédéric Austerlitz
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-03-01
Series:PLoS Genetics
Online Access:http://europepmc.org/articles/PMC4778914?pdf=render
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author Simon Boitard
Willy Rodríguez
Flora Jay
Stefano Mona
Frédéric Austerlitz
author_facet Simon Boitard
Willy Rodríguez
Flora Jay
Stefano Mona
Frédéric Austerlitz
author_sort Simon Boitard
collection DOAJ
description Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
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spelling doaj.art-0fcac4982ab848e096cae30c4e149da72022-12-21T22:32:32ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042016-03-01123e100587710.1371/journal.pgen.1005877Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.Simon BoitardWilly RodríguezFlora JayStefano MonaFrédéric AusterlitzInferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.http://europepmc.org/articles/PMC4778914?pdf=render
spellingShingle Simon Boitard
Willy Rodríguez
Flora Jay
Stefano Mona
Frédéric Austerlitz
Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
PLoS Genetics
title Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
title_full Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
title_fullStr Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
title_full_unstemmed Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
title_short Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.
title_sort inferring population size history from large samples of genome wide molecular data an approximate bayesian computation approach
url http://europepmc.org/articles/PMC4778914?pdf=render
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AT florajay inferringpopulationsizehistoryfromlargesamplesofgenomewidemoleculardataanapproximatebayesiancomputationapproach
AT stefanomona inferringpopulationsizehistoryfromlargesamplesofgenomewidemoleculardataanapproximatebayesiancomputationapproach
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