Literature DB >> 30030601

Coalescence times for three genes provide sufficient information to distinguish population structure from population size changes.

Simona Grusea1, Willy Rodríguez2, Didier Pinchon2, Lounès Chikhi3,4, Simon Boitard5, Olivier Mazet2.   

Abstract

The increasing amount of genomic data currently available is expanding the horizons of population genetics inference. A wide range of methods have been published allowing to detect and date major changes in population size during the history of species. At the same time, there has been an increasing recognition that population structure can generate genetic data similar to those generated under models of population size change. Recently, Mazet et al. (Heredity 116(4):362-371, 2016) introduced the idea that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size-change having an identical distribution of [Formula: see text] (the time of the first coalescence for a sample of size two). This implies that there is an identifiability problem between a panmictic and a structured model when we base our analysis only on [Formula: see text]. In this paper, based on an analytical study of the rate matrix of the ancestral lineage process, we obtain new theoretical results about the joint distribution of the coalescence times [Formula: see text] for a sample of three haploid genes in a n-island model with constant size. Even if, for any [Formula: see text], it is always possible to find a size-change scenario for a panmictic population such that the marginal distribution of [Formula: see text] is exactly the same as in a n-island model with constant population size, we show that the joint distribution of the coalescence times [Formula: see text] for a sample of three genes contains enough information to distinguish between a panmictic population and a n-island model of constant size.

Keywords:  Demographic history; Inverse instantaneous coalescence rate (IICR); Population size change; Population structure; Rate matrix; Structured coalescent

Mesh:

Year:  2018        PMID: 30030601     DOI: 10.1007/s00285-018-1272-4

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  29 in total

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Authors:  S Wright
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4.  Inbreeding coefficients and coalescence times.

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Journal:  Genet Res       Date:  1991-10       Impact factor: 1.588

5.  Demographic inference using genetic data from a single individual: Separating population size variation from population structure.

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Journal:  Theor Popul Biol       Date:  2015-06-25       Impact factor: 1.570

6.  Accuracy of Demographic Inferences from the Site Frequency Spectrum: The Case of the Yoruba Population.

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Journal:  Genetics       Date:  2017-03-24       Impact factor: 4.562

7.  Properties of a neutral allele model with intragenic recombination.

Authors:  R R Hudson
Journal:  Theor Popul Biol       Date:  1983-04       Impact factor: 1.570

8.  Evolutionary relationship of DNA sequences in finite populations.

Authors:  F Tajima
Journal:  Genetics       Date:  1983-10       Impact factor: 4.562

9.  Genetic data suggest a natural prehuman origin of open habitats in northern Madagascar and question the deforestation narrative in this region.

Authors:  Erwan Quéméré; Xavier Amelot; Julie Pierson; Brigitte Crouau-Roy; Lounès Chikhi
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-23       Impact factor: 11.205

10.  Genetic signature of anthropogenic population collapse in orang-utans.

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  2 in total

1.  Heterogeneity in effective size across the genome: effects on the inverse instantaneous coalescence rate (IICR) and implications for demographic inference under linked selection.

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Journal:  Genetics       Date:  2022-03-03       Impact factor: 4.562

2.  Inferring number of populations and changes in connectivity under the n-island model.

Authors:  Armando Arredondo; Beatriz Mourato; Khoa Nguyen; Simon Boitard; Willy Rodríguez; Olivier Mazet; Lounès Chikhi
Journal:  Heredity (Edinb)       Date:  2021-04-12       Impact factor: 3.821

  2 in total

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