Evidence map›Paper›PMID 26637555›Full record

ArticleMolecular biology and evolution2016

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia.

Isabel Alves, Miguel Arenas, Mathias Currat, Anna Sramkova Hanulova, Vitor C Sousa, Nicolas Ray, Laurent Excoffier

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. A geometric relationship ofPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
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  2. Article
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  7. The impact of long-range dispersal on gene surfing.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  8. Article
  9. Article
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  11. Review
  12. Microbial sequence typing in the genomic era.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2018
    Review
  13. Article
  14. Article
  15. Article
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Isabel AlvesComputational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland Population and Conservation Genetics Group, Instituto Gulbenkian de Ciência, Oeiras, Portugal isabel.alves@iee.unibe.ch laurent.excoffier@iee.unibe.ch.
Miguel ArenasComputational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal.
Mathias CurratAnthropology, Genetics and Peopling History Lab, Department of Genetics & Evolution-Anthropology Unit, University of Geneva, Geneva, Switzerland.
Anna Sramkova HanulovaComputational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Vitor C SousaComputational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Nicolas RayEnviroSPACE Lab, Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland.
Laurent ExcoffierComputational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland isabel.alves@iee.unibe.ch laurent.excoffier@iee.unibe.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations.

Indexed as

DemographyGenetics, PopulationGenetic VariationHuman MigrationAsiaEcosystemEuropeGene FlowGenotypeGeographyHumansInbreedingPopulation Dynamicshuman evolutionlast glacial maximumlong-distance dispersalout of Africa.

Identifiers

PMID26637555
PMCPMC4776706

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.