Evidence map›Paper›PMID 42693085›Full record

ArticleNature communications2026

Archaic ancestry inference in imputed ancient human genomes.

Marco Rosario Capodiferro, Léo Planche, Emily M Breslin, Linda Ongaro, María C Ávila-Arcos, Flora Jay, Lara M Cassidy, Emilia Huerta-Sanchez

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

8 authors.

Marco Rosario Capodiferro *Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland. marcorosario.capodiferro@gmail.com.ORCID http://orcid.org/0000-0003-2494-5423
Léo Planche *Interdisciplinary Laboratory of Digital Sciences, Université Paris-Saclay, CNRS, INRIA, Orsay, France. leo.planche@lisn.fr.
Emily M BreslinSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.ORCID http://orcid.org/0000-0001-5973-3194
Linda OngaroSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.ORCID http://orcid.org/0000-0003-1900-3394
María C Ávila-ArcosInternational Laboratory for Human Genome Research, Universidad Nacional Autónoma de México, Querétaro, México.ORCID http://orcid.org/0000-0003-1691-1696
Flora JayInterdisciplinary Laboratory of Digital Sciences, Université Paris-Saclay, CNRS, INRIA, Orsay, France.
Lara M CassidySmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
Emilia Huerta-SanchezSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland. ehuertas@tcd.ie.ORCID http://orcid.org/0000-0002-1506-5494

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-20-CE45-0010EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) ERC-2018-STG, 804994Human Frontier Science Program (HFSP) RGY0075/2019
6 · The paper itself

Abstract

When modern humans expanded from Africa into Eurasia, they interbred with archaic hominins such as Neanderthals and Denisovans. This introgression shaped human evolution, yet most insights have been gained from present-day genomes, leaving little known about how archaic variants evolved after interbreeding. Ancient genomes offer a direct view of this process, but low coverage and poor quality have limited their use. Recent advances in genotype imputation offer a way to overcome these challenges by reconstructing missing information from reference panels and recovering evolutionary signals from low-coverage data. Here, we show that imputation enables accurate detection and quantification of archaic introgression in ancient genomes, improves local archaic ancestry inference, and that regions of archaic ancestry are imputed with especially high accuracy. We further demonstrate that imputed genomes can reconstruct the trajectories of introgressed haplotypes, distinguish populations across time and geography, and identify both known and additional candidates for adaptive introgression.

Indexed as

Genome, HumanHominidaeNeanderthalsAnimalsDNA, AncientEvolution, MolecularGenetic IntrogressionGenetics, PopulationGenotypeHaplotypesHumansPolymorphism, Single NucleotideDNA, Ancient

Identifiers

PMID42693085
PMCPMC13542231

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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.