Evidence map›Paper›PMID 35730151›Full record

ArticleProceedings. Biological sciences2022

Background selection under evolving recombination rates.

Tom R Booker, Bret A Payseur, Anna Tigano

Open access · greenAbstract read
In one paragraph

Article in Proceedings. Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. ThebioRxiv : the preprint server for biology · 2026
    Article
  2. Review
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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 2 countries.

Tom R BookerDepartment of Zoology, University of British Columbia, Vancouver Campus, Vancouver, BC, Canada.ORCID 0000-0001-8403-6219
Bret A PayseurLaboratory of Genetics, University of Wisconsin - Madison, Madison, WI, USA.
Anna TiganoDepartment of Biology, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.ORCID 0000-0001-9240-3058
University of British Columbia · CAUniversity of Wisconsin–Madison · US

Funding

Evolution of Phenotypic Extremes: Genetic Determinants of Gigantism, Boldness, and RecombinationR35GM139412 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Bret A. Payseur · 2021 to 2026
$5.7M
NIGMS NIH HHS R35 GM139412
6 · The paper itself

Abstract

Background selection (BGS), the effect that purifying selection exerts on sites linked to deleterious alleles, is expected to be ubiquitous across eukaryotic genomes. The effects of BGS reflect the interplay of the rates and fitness effects of deleterious mutations with recombination. A fundamental assumption of BGS models is that recombination rates are invariant over time. However, in some lineages, recombination rates evolve rapidly, violating this central assumption. Here, we investigate how recombination rate evolution affects genetic variation under BGS. We show that recombination rate evolution modifies the effects of BGS in a manner similar to a localized change in the effective population size, potentially leading to underestimation or overestimation of the genome-wide effects of selection. Furthermore, we find evidence that recombination rate evolution in the ancestors of modern house mice may have impacted inferences of the genome-wide effects of selection in that species.

Indexed as

Evolution, MolecularSelection, GeneticAllelesAnimalsGenetic VariationMicePopulation DensityRecombination, Geneticbackground selectionchromosomal rearrangementsevolutionary geneticsMus musculusrecombination rate

Identifiers

PMID35730151
PMCPMC9233929
OpenAlexW4283313127

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.