Evidence map›Paper›PMID 30125248›Full record

ArticleeLife2018

Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences.

Fanny Pouyet, Simon Aeschbacher, Alexandre Thiéry, Laurent Excoffier

Abstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing 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

88 citing papers in PubMed.

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  11. ThebioRxiv : the preprint server for biology · 2026
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  18. Research on the Historical Dynamics of Baicheng Oil Chicken Populations.Animals : an open access journal from MDPI · 2025
    Article
  19. Article
  20. Article

28 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Fanny Pouyet *Computational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0001-5614-6998
Simon Aeschbacher *Computational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.
Alexandre ThiéryComputational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.
Laurent ExcoffierComputational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-7507-6494

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 310030B-166605University of Berkeley Visiting Miller ProfessorshipUniversity of California Berkeley Visiting Miller Professorship
6 · The paper itself

Abstract

Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.

Indexed as

Evolution, MolecularBase CompositionDemographyGene ConversionGenome, HumanGenomicsHumansModels, GeneticMutationRecombination, GeneticSelection, Geneticbackground selectiondemographyGC-biased gene conversiongeneticsgenomic diversitygenomicshumanrecombination

Identifiers

PMID30125248
PMCPMC6177262

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Registered trials

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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.