Evidence map›Paper›PMID 26451700›Full record

ArticlePLoS computational biology2015

Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks.

Jeewoen Shin, Thomas MacCarthy

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

2 authors.

Jeewoen ShinDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America.
Thomas MacCarthyDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, United States of America.

Funding

High-throughput informatics for antibodiesR01GM111741 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI MACCARTHY, THOMAS · 2015 to 2018
$1.1M
NIGMS NIH HHS 1R01GM111741-01A1NIGMS NIH HHS R01 GM111741
6 · The paper itself

Abstract

Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability--the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. We consider a two-species model of coevolution involving one host and one parasite population. By using two interacting species, key model parameters that determine the fitness landscapes become emergent properties of the model, avoiding the need to impose these parameters externally. In our study, parasites are modeled on species such as cuckoos where mimicry of the host phenotype confers high fitness to the parasite but lower fitness to the host. Here, frequent phenotype changes are favored as each population continually adapts to the other population. Sensitivity evolves at the network level such that point mutations can induce large phenotype changes. Crucially, the sensitive points of the network are broadly distributed throughout the network and continually relocate. Each time sensitive points in the network are mutated, new ones appear to take their place. We have therefore named this phenomenon "whack-a-mole" sensitivity, after a popular fun park game. We predict that this type of sensitivity will evolve under conditions of strong directional selection, an observation that helps interpret existing experimental evidence, for example, during the emergence of bacterial antibiotic resistance.

Indexed as

Evolution, MolecularGame TheoryModels, GeneticAnimalsFeedback, PhysiologicalGene Expression RegulationGene Regulatory NetworksMutationPredatory BehaviorSelection, Genetic

Identifiers

PMID26451700
PMCPMC4599961

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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.