Evidence map›Paper›PMID 40146820›Full record

ArticleScience (New York, N.Y.)2025

A geographic history of human genetic ancestry.

Michael C Grundler, Jonathan Terhorst, Gideon S Bradburd

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. An inverse correlation between structural linguistic and human genetic diversity.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. A geographic history of human genetic ancestry.Science (New York, N.Y.) · 2025
    Article
  18. Likelihoods for a general class of ARGs under the SMC.bioRxiv : the preprint server for biology · 2025
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Michael C GrundlerDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-0729-6687
Jonathan TerhorstDepartment of Statistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0001-7765-2101
Gideon S BradburdDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0001-8009-0154

Funding

Incorporating geography into statistical methods for analysis of population genomic DNAR35GM137919 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Gideon Bradburd · 2020 to 2026
$2.3M
Large-scale phylodynamics under non-neutral and non-treelike models of evolutionR35GM151145 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jonathan G Terhorst · 2023 to 2026
$1.5M
NIGMS NIH HHS R35 GM137919NIGMS NIH HHS R35 GM151145
6 · The paper itself

Abstract

Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. We present a method that capitalizes on the rich genealogical information encoded in genomic tree sequences to infer the geographic locations of the shared ancestors of a sample of sequenced individuals. We used this method to infer the geographic history of genetic ancestry of a set of human genomes sampled from Europe, Asia, and Africa, accurately recovering major population movements on those continents. Our findings demonstrate the importance of defining the spatiotemporal context of genetic ancestry when describing human genetic variation and caution against the oversimplified interpretations of genetic data prevalent in contemporary discussions of race and ancestry.

Indexed as

Genetics, PopulationGenetic VariationGenome, HumanHuman MigrationRacial GroupsAfricaAsiaEuropeHumans

Identifiers

PMID40146820
PMCPMC12132082

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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.