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Differences in local population history at the finest level: the case of the Estonian population.
Pankratov, Vasili; Montinaro, Francesco; Kushniarevich, Alena; Hudjashov, Georgi; Jay, Flora; Saag, Lauri; Flores, Rodrigo; Marnetto, Davide; Seppel, Marten; Kals, Mart; Võsa, Urmo; Taccioli, Cristian; Möls, Märt; Milani, Lili; Aasa, Anto; Lawson, Daniel John; Esko, Tõnu; Mägi, Reedik; Pagani, Luca; Metspalu, Andres; Metspalu, Mait.
Afiliação
  • Pankratov V; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia. vasilipankratov@gmail.com.
  • Montinaro F; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Kushniarevich A; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Hudjashov G; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Jay F; Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, 4474, New Zealand.
  • Saag L; Laboratoire de Recherche en Informatique, CNRS, UMR 8623, Université Paris-Saclay, 91405, Inria, Orsay, France.
  • Flores R; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Marnetto D; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Seppel M; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Kals M; Institute of History and Archaeology, University of Tartu, 51005, Tartu, Estonia.
  • Võsa U; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Taccioli C; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Möls M; Department of Biology, University of Padova, 35131, Padova, Italy.
  • Milani L; Institute of Mathematical Statistics, University of Tartu, 50409, Tartu, Estonia.
  • Aasa A; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Lawson DJ; Institute of Geography University of Tartu, 51003, Tartu, Estonia.
  • Esko T; Medical Research Council Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
  • Mägi R; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Pagani L; Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Metspalu A; Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia.
  • Metspalu M; Department of Biology, University of Padova, 35131, Padova, Italy.
Eur J Hum Genet ; 28(11): 1580-1591, 2020 11.
Article em En | MEDLINE | ID: mdl-32712624
Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10-15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Linhagem / Polimorfismo Genético / População Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Eur J Hum Genet Assunto da revista: GENETICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estônia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Linhagem / Polimorfismo Genético / População Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Eur J Hum Genet Assunto da revista: GENETICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estônia