Evidence map›Paper›PMID 41915739›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits.

Xinyi Li, Jeremy J Berg

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 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. Evolution of quantitative traits with background selection.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Xinyi LiCommittee on Genetics, Genomics, Systems and Biology, University of Chicago, Chicago, IL 60637.ORCID 0000-0002-1624-2704
Jeremy J BergCommittee on Genetics, Genomics, Systems and Biology, University of Chicago, Chicago, IL 60637.ORCID 0000-0001-5411-6840

Funding

Theory, Methods, and Resources for Understanding and Leveraging Spatial Variation in Population Genetic DataR35GM149521 · NIGMS · UNIVERSITY OF CHICAGO · PI John Novembre · 2023 to 2026
$1.7M
Refining mutation rates and measures of purifying selection with an application to understanding the impact of non-coding variation on neuropsychiatric diseasesR01HG010773 · NHGRI · UNIVERSITY OF CHICAGO · PI HE, XIN, NOVEMBRE, JOHN · 2020 to 2023
$1.7M
Population genetic modeling of genetic variation for complex traits and diseasesR35GM151257 · NIGMS · UNIVERSITY OF CHICAGO · PI Jeremy Jackson Berg · 2023 to 2026
$1.6M
NHGRI NIH HHS R01 HG010773NIGMS NIH HHS R35 GM149521NIGMS NIH HHS R35 GM151257
6 · The paper itself

Abstract

Background selection (BGS)-the reduction of linked neutral diversity via the purging of deleterious mutations-is a pervasive force in genomic evolution. However, its impact on complex phenotypes remains poorly understood because classical theory treats fitness effects as fixed rather than emerging from a phenotype-to-fitness map. Here, we investigate the impact of BGS across three phenotypic selection frameworks: exponential directional, a liability threshold model, and stabilizing selection. First, we develop an effectively nonrecombining block approximation for the site frequency spectrum (SFS) and show that this framework accurately describes the skew in the SFS in the weak mutation regime typical of humans. Second, we show that phenotypic impacts of BGS depend on how selection is coupled across loci. In the liability threshold model, strong synergistic epistasis generates a global compensation mechanism-driven by tiny shifts in the mean phenotype-that propagates BGS effects to strongly selected variants otherwise immune to linked selection. This coupling reduces genetic variance across almost the entire effect-size distribution by an amount determined by a nonlinear average of local effective population size reductions across the genome. Conversely, under stabilizing selection, BGS can counterintuitively increase genetic variance. This occurs because BGS shifts strongly selected sites into the weakly selected underdominant regime where they persist at intermediate frequencies longer than in the equivalent directional selection model. Our results inform both longstanding evolutionary conversations regarding synergistic epistasis and efforts to model the impact of background selection on individual variants in recombining genomes.

Indexed as

GenomeModels, GeneticRecombination, GeneticSelection, GeneticEpistasis, GeneticEvolution, MolecularGenetic VariationHumansMutationPhenotypebackground selectionmutation–selection–drift balancepopulation genetics

Identifiers

PMID41915739
PMCPMC13056065

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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.