Estimating recent migration and population-size surfaces

In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however, this relationship is often complex, and may vary across space and time. Methods to uncover and visualize such relationships have widespread use for analyses in molecular ec...

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Bibliographic Details
Published in:PLoS genetics Vol. 15; no. 1; p. e1007908
Main Authors: Al-Asadi, Hussein, Petkova, Desislava, Stephens, Matthew, Novembre, John
Format: Journal Article
Language:English
Published: United States Public Library of Science 14.01.2019
Public Library of Science (PLoS)
Subjects:
Biodiversity
Bioinformatics
Biological Evolution
Biological research
Biology and Life Sciences
Conservation genetics
Demography
Earth Sciences
Ecology and Environmental Sciences
Europe
Evolution
Evolutionary biology
Evolutionary genetics
Funding
Gene mapping
Genetic diversity
Genetic Variation - genetics
Genetics
Genetics, Population
Genomes
Haplotypes - genetics
Humans
Methods
Migration
People and Places
Population biology
Population Density
Population Dynamics - statistics & numerical data
Population structure
Principal components analysis
Research and Analysis Methods
Social Sciences
Software
Supervision
Visualization
Europe
Scotland
Chicago Illinois
United States > US
Illinois
ISSN:1553-7404, 1553-7390, 1553-7404
Online Access:Get full text
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Summary:In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however, this relationship is often complex, and may vary across space and time. Methods to uncover and visualize such relationships have widespread use for analyses in molecular ecology, conservation genetics, evolutionary genetics, and human genetics. While several frameworks exist, a promising approach is to infer maps of how migration rates vary across geographic space. Such maps could, in principle, be estimated across time to reveal the full complexity of population histories. Here, we take a step in this direction: we present a method to infer maps of population sizes and migration rates associated with different time periods from a matrix of genetic similarity between every pair of individuals. Specifically, genetic similarity is measured by counting the number of long segments of haplotype sharing (also known as identity-by-descent tracts). By varying the length of these segments we obtain parameter estimates associated with different time periods. Using simulations, we show that the method can reveal time-varying migration rates and population sizes, including changes that are not detectable when using a similar method that ignores haplotypic structure. We apply the method to a dataset of contemporary European individuals (POPRES), and provide an integrated analysis of recent population structure and growth over the last ∼3,000 years in Europe.
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The authors have declared that no competing interests exist.
ISSN:1553-7404
1553-7390
1553-7404
DOI:10.1371/journal.pgen.1007908