Evidence map›Paper›PMID 41542486›Full record

ArticlebioRxiv : the preprint server for biology2026

Global patterns of natural selection inferred using ancient DNA.

Laura L Colbran, Jonathan Terhorst, Iain Mathieson

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Laura L ColbranDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0002-7752-6671
Jonathan TerhorstDepartment of Statistics, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID 0000-0001-7765-2101
Iain MathiesonDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0002-4256-3982

Funding

Postdoctoral Training Program in Genomic MedicineT32HG009495 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI Katherine L. Nathanson, Bogdan Pasaniuc · 2017 to 2026
$4.2M
Polygenic prediction and evolution of complex traitsR35GM133708 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Iain Neil Mathieson · 2019 to 2026
$2.9M
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
NHGRI NIH HHS T32 HG009495NIGMS NIH HHS R35 GM133708NIGMS NIH HHS R35 GM151145
6 · The paper itself

Abstract

Ancient DNA has revolutionized our understanding of human history, and is now yielding important insights into evolution and natural selection. However, studies of selection using ancient DNA have largely been limited to Europe, excluding populations in other parts of the world. While many selective pressures were local to specific populations others, for example those related to the development of agriculture, may have been universal. By studying a broader range of global populations, we can identify examples of local adaption but also more general principles of adaptation to climatic, social and technological changes. We therefore leverage ancient DNA to test for selection in 7244 individuals from 13 ancient and 19 present-day populations across five regions: Europe, East Asia, South Asia, Africa and the Americas. In each region, we tested for selection using multiple approaches that account for complex demographic histories. We identify 31 genome-wide significant signals of selection, including both known and novel loci. We find a high degree of shared signal across regions, suggesting extensive parallel or shared adaptation. Using a novel admixture-aware time series method, we find that the strength of selection on many variants changed over time, for example decreasing selection at

Identifiers

PMID41542486
PMCPMC12803250

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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.