Evidence map›Paper›PMID 27756828›Full record

ArticleMolecular biology and evolution2017

Signatures of Archaic Adaptive Introgression in Present-Day Human Populations.

Fernando Racimo, Davide Marnetto, Emilia Huerta-Sánchez

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers.

0numbers the graph read from it
0cells of the map it votes in
125citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

125 citing papers in PubMed.

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  14. Global impact of micronutrients in modern human evolution.American journal of human genetics · 2025
    Article
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  17. TheScience (New York, N.Y.) · 2025
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65 more citing papers are in PubMed but not listed here.

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.

Fernando RacimoDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA.
Davide MarnettoDepartment of Molecular Biotechnology and Health Sciences, University of Torino, Turin, Italy.
Emilia Huerta-SánchezSchool of Natural Sciences, University of California Merced, Merced, CA.

Funding

Population Genetic Inferences From Dense Genotype DataR01HG003229 · NHGRI · CORNELL UNIVERSITY ITHACA · PI BUSTAMANTE, CARLOS DANIEL, CLARK, ANDREW G · 2004 to 2013
$4.8M
NHGRI NIH HHS R01 HG003229
6 · The paper itself

Abstract

Comparisons of DNA from archaic and modern humans show that these groups interbred, and in some cases received an evolutionary advantage from doing so. This process-adaptive introgression-may lead to a faster rate of adaptation than is predicted from models with mutation and selection alone. Within the last couple of years, a series of studies have identified regions of the genome that are likely examples of adaptive introgression. In many cases, once a region was ascertained as being introgressed, commonly used statistics based on both haplotype as well as allele frequency information were employed to test for positive selection. Introgression by itself, however, changes both the haplotype structure and the distribution of allele frequencies, thus confounding traditional tests for detecting positive selection. Therefore, patterns generated by introgression alone may lead to false inferences of positive selection. Here we explore models involving both introgression and positive selection to investigate the behavior of various statistics under adaptive introgression. In particular, we find that the number and allelic frequencies of sites that are uniquely shared between archaic humans and specific present-day populations are particularly useful for detecting adaptive introgression. We then examine the 1000 Genomes dataset to characterize the landscape of uniquely shared archaic alleles in human populations. Finally, we identify regions that were likely subject to adaptive introgression and discuss some of the most promising candidate genes located in these regions.

Indexed as

Adaptation, BiologicalAllelesAnimalsBiological EvolutionComputer SimulationDatabases, Nucleic AcidDNA, AncientEvolution, MolecularGene FrequencyGenetics, PopulationHaplotypesHumansNeanderthalsPhylogenySelection, GeneticSequence Analysis, DNADNA, Ancientadaptive introgressionancient DNAdenisovaneanderthal

Identifiers

PMID27756828
PMCPMC5400396

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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.