Evidence map›Paper›PMID 38798350›Full record

ArticlebioRxiv : the preprint server for biology2024

Neandertal ancestry through time: Insights from genomes of ancient and present-day humans.

Leonardo N M Iasi, Manjusha Chintalapati, Laurits Skov, Alba Bossoms Mesa, Mateja Hajdinjak, Benjamin M Peter, Priya Moorjani

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

7 authors.

Leonardo N M IasiDepartment for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany.ORCID 0009-0005-8020-0380
Manjusha ChintalapatiDepartment of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA.ORCID 0000-0002-9808-5991
Laurits SkovDepartment of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA.ORCID 0000-0001-9582-0391
Alba Bossoms MesaDepartment for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany.
Mateja HajdinjakDepartment for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany.ORCID 0000-0002-4064-0331
Benjamin M PeterDepartment for Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology; Leipzig, 04301, Germany.ORCID 0000-0003-2526-8081
Priya MoorjaniDepartment of Molecular and Cell Biology, University of California Berkeley; Berkeley, CA 94720, USA.ORCID 0000-0002-0947-5673

Funding

Genomic Insights into Human Population Mixture and its Role in Adaptation and DiseaseR35GM142978 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI Priya Moorjani · 2021 to 2026
$2.5M
NIGMS NIH HHS R35 GM142978
6 · The paper itself

Abstract

Gene flow from Neandertals has shaped the landscape of genetic and phenotypic variation in modern humans. We identify the location and size of introgressed Neandertal ancestry segments in more than 300 genomes spanning the last 50,000 years. We study how Neandertal ancestry is shared among individuals to infer the time and duration of the Neandertal gene flow. We find the correlation of Neandertal segment locations across individuals and their divergence to sequenced Neandertals, both support a model of single major Neandertal gene flow. Our catalog of introgressed segments through time confirms that most natural selection-positive and negative-on Neandertal ancestry variants occurred immediately after the gene flow, and provides new insights into how the contact with Neandertals shaped human origins and adaptation.

Identifiers

PMID38798350
PMCPMC11118355

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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.