Evidence map›Paper›PMID 39589398›Full record

ArticleeLife2024

Estimating dispersal rates and locating genetic ancestors with genome-wide genealogies.

Matthew Osmond, Graham Coop

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  15. Life-history trade-offs explain local adaptation inbioRxiv : the preprint server for biology · 2025
    Article
  16. A geographic history of human genetic ancestry.Science (New York, N.Y.) · 2025
    Article
  17. Likelihoods for a general class of ARGs under the SMC.bioRxiv : the preprint server for biology · 2025
    Article
  18. Review
  19. Article
  20. Review
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

2 authors.

Matthew OsmondDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Canada.ORCID https://orcid.org/0000-0001-6170-8182
Graham CoopDepartment of Evolution & Ecology and Center for Population Biology, University of California, Davis, Davis, United States.ORCID https://orcid.org/0000-0001-8431-0302

Funding

The impact of natural selection and population structure on human genomic variationR35GM136290 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Graham Coop · 2020 to 2026
$2.6M
Genome-wide approaches to polygenic adaptationR01GM108779 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI COOP, GRAHAM · 2014 to 2019
$1.0M
Natural Sciences and Engineering Research Council of Canada DGECR-2021-00114Natural Sciences and Engineering Research Council of Canada RGPIN-2021-03207NIGMS NIH HHS R01 GM108779NIGMS NIH HHS R35 GM136290
6 · The paper itself

Abstract

Spatial patterns in genetic diversity are shaped by individuals dispersing from their parents and larger-scale population movements. It has long been appreciated that these patterns of movement shape the underlying genealogies along the genome leading to geographic patterns of isolation-by-distance in contemporary population genetic data. However, extracting the enormous amount of information contained in genealogies along recombining sequences has, until recently, not been computationally feasible. Here, we capitalize on important recent advances in genome-wide gene-genealogy reconstruction and develop methods to use thousands of trees to estimate per-generation dispersal rates and to locate the genetic ancestors of a sample back through time. We take a likelihood approach in continuous space using a simple approximate model (branching Brownian motion) as our prior distribution of spatial genealogies. After testing our method with simulations we apply it to

Indexed as

ArabidopsisComputer SimulationGenetics, PopulationGenetic VariationModels, Geneticancestral recombination graphA. thalianabranching Brownian motionevolutionary biologyimportance samplingphylogeographypopulation geneticsspatial inferencetree sequence

Identifiers

PMID39589398
PMCPMC11658769

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Registered trials

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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.