Evidence map›Paper›PMID 21697174›Full record

ArticleProceedings. Biological sciences2012

Impact of epistasis and pleiotropy on evolutionary adaptation.

Bjørn Ostman, Arend Hintze, Christoph Adami

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
–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

55 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Pooled it
  2. Fungicide DrivesEvolutionary applications · 2026
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  12. Testing for fitness epistasis in a transplant experiment identifies a candidate adaptive locus inPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
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  16. Adaptive Processes Change as Multiple Functions Evolve.Antimicrobial agents and chemotherapy · 2021
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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.

Bjørn OstmanKeck Graduate Institute of Applied Life Sciences, Claremont, CA 91711, USA. ostman@msu.edu
Arend Hintze
Christoph Adami

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evolutionary adaptation is often likened to climbing a hill or peak. While this process is simple for fitness landscapes where mutations are independent, the interaction between mutations (epistasis) as well as mutations at loci that affect more than one trait (pleiotropy) are crucial in complex and realistic fitness landscapes. We investigate the impact of epistasis and pleiotropy on adaptive evolution by studying the evolution of a population of asexual haploid organisms (haplotypes) in a model of N interacting loci, where each locus interacts with K other loci. We use a quantitative measure of the magnitude of epistatic interactions between substitutions, and find that it is an increasing function of K. When haplotypes adapt at high mutation rates, more epistatic pairs of substitutions are observed on the line of descent than expected. The highest fitness is attained in landscapes with an intermediate amount of ruggedness that balance the higher fitness potential of interacting genes with their concomitant decreased evolvability. Our findings imply that the synergism between loci that interact epistatically is crucial for evolving genetic modules with high fitness, while too much ruggedness stalls the adaptive process.

Indexed as

Adaptation, PhysiologicalBiological EvolutionEpistasis, GeneticGenetic PleiotropyModels, GeneticHaploidyReproduction, Asexual

Identifiers

PMID21697174
PMCPMC3223680

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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.