Evidence map›Paper›PMID 31155285›Full record

ArticleAmerican journal of human genetics2019

Impact and Evolutionary Determinants of Neanderthal Introgression on Transcriptional and Post-Transcriptional Regulation.

Martin Silvert, Lluis Quintana-Murci, Maxime Rotival

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
50.5field-weighted citation impact, top 1% of its field
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

28 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
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  3. Article
  4. Denisovan admixture facilitated environmental adaptation in Papua New Guinean populations.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  7. Article
  8. Review
  9. Review
  10. Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Predicting Archaic Hominin Phenotypes from Genomic Data.Annual review of genomics and human genetics · 2022
    Review
  17. The genetic and evolutionary determinants of COVID-19 susceptibility.European journal of human genetics : EJHG · 2022
    Review
  18. Article
  19. Apportioning archaic variants among modern populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  20. 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

3 authors at 2 institutions in 1 country.

Martin SilvertHuman Evolutionary Genetics Unit, Institut Pasteur, Centre National de la Recherche Scientifique, UMR 2000, 75015 Paris, France; Sorbonne Universités, École Doctorale Complexité du Vivant, 75005 Paris, France.
Lluis Quintana-MurciHuman Evolutionary Genetics Unit, Institut Pasteur, Centre National de la Recherche Scientifique, UMR 2000, 75015 Paris, France. Electronic address: quintana@pasteur.fr.
Maxime RotivalHuman Evolutionary Genetics Unit, Institut Pasteur, Centre National de la Recherche Scientifique, UMR 2000, 75015 Paris, France. Electronic address: maxime.rotival@pasteur.fr.
Institut Pasteur · FRCentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Archaic admixture is increasingly recognized as an important source of diversity in modern humans, and Neanderthal haplotypes cover 1%-3% of the genome of present-day Eurasians. Recent work has shown that archaic introgression has contributed to human phenotypic diversity, mostly through the regulation of gene expression. Yet the mechanisms through which archaic variants alter gene expression and the forces driving the introgression landscape at regulatory regions remain elusive. Here, we explored the impact of archaic introgression on transcriptional and post-transcriptional regulation. We focused on promoters and enhancers across 127 different tissues as well as on microRNA (miRNA)-mediated regulation. Although miRNAs themselves harbor few archaic variants, we found that some of these variants may have a strong impact on miRNA-mediated gene regulation. Enhancers were by far the regulatory elements most affected by archaic introgression: up to one-third of the tissues we tested presented significant enrichments. Specifically, we found strong enrichments of archaic variants in adipose-related tissues and primary T cells, even after accounting for various genomic and evolutionary confounders such as recombination rate and background selection. Interestingly, we identified signatures of adaptive introgression at enhancers of some key regulators of adipogenesis, raising the interesting hypothesis of a possible adaptation of early Eurasians to colder climates. Collectively, this study sheds new light on the mechanisms through which archaic admixture has impacted gene regulation in Eurasians and, more generally, increases our understanding of the contribution of Neanderthals to the regulation of acquired immunity and adipose homeostasis in modern humans.

Indexed as

Evolution, MolecularGene Expression Regulation, DevelopmentalPolymorphism, Single NucleotideRNA Processing, Post-TranscriptionalSelection, GeneticTranscription, GeneticAdaptation, PhysiologicalAdipogenesisAdipose TissueAnimalsGenome, HumanGenomicsHumansMicroRNAsNeanderthalsRecombination, GeneticMicroRNAsadaptationadipose tissuearchaic introgressionenhancersgene regulationimmunitymiRNAsNeanderthalpromotersT-cells

Identifiers

PMID31155285
PMCPMC6557732
OpenAlexW2911559590

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.