Evidence map›Paper›PMID 24675740›Full record

ArticlePLoS genetics2014

Genetic diversity in the interference selection limit.

Benjamin H Good, Aleksandra M Walczak, Richard A Neher, Michael M Desai

Abstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
  2. 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
  3. ThebioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. Article
  6. A model for background selection in non-equilibrium populations.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
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  17. Article
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  19. Article
  20. A dynamical limit to evolutionary adaptation.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article

8 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

4 authors.

Benjamin H GoodDepartments of Organismic and Evolutionary Biology and of Physics, Harvard University, Cambridge, Massachusetts, United States of America; FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Aleksandra M WalczakCNRS-Laboratoire de Physique Théorique de l'École Normale Supérieure, Paris, France.
Richard A NeherMax Planck Institute for Developmental Biology, Tübingen, Germany.
Michael M DesaiDepartments of Organismic and Evolutionary Biology and of Physics, Harvard University, Cambridge, Massachusetts, United States of America; FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.

Funding

Microbial Adaptation and the Statistics of Epistasis and PleiotropyR01GM104239 · NIGMS · HARVARD UNIVERSITY · PI DESAI, MICHAEL M · 2013 to 2025
$4.5M
NIGMS NIH HHS GM104239NIGMS NIH HHS R01 GM104239
6 · The paper itself

Abstract

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.

Indexed as

Evolution, MolecularGenetic VariationGenetic LinkageGenetics, PopulationHumansMutationPolymorphism, GeneticRecombination, GeneticSelection, Genetic

Identifiers

PMID24675740
PMCPMC3967937

What OpenQuestion holds

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LicenceCC BY
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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.