Evidence map›Paper›PMID 25625594›Full record

ArticlePloS one2015

Dynamic epistasis under varying environmental perturbations.

Brandon Barker, Lin Xu, Zhenglong Gu

Abstract read
In one paragraph

Article in PloS one, 2015. 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
–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

4 citing papers in PubMed.

  1. Article
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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.

Brandon BarkerCenter for Advanced Computing, Cornell University, Ithaca, New York, United States of America.
Lin XuDivision of Hematology/Oncology, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
Zhenglong GuDivision of Nutritional Sciences, Cornell University, Ithaca, New York, United States of America; Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York, United States of America.

Funding

Tri-Institutional Training Program in Computational Biology & MedicineT32GM083937 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHRISTINI, DAVID J. · 2009 to 2018
$3.1M
Genetic and Evolutionary Basis of Fungal Drug ResistanceR01AI085286 · NIAID · CORNELL UNIVERSITY · PI GU, ZHENGLONG · 2010 to 2014
$1.7M
NIAID NIH HHS 1R01AI085286NIAID NIH HHS R01 AI085286NIGMS NIH HHS T32 GM083937
6 · The paper itself

Abstract

Epistasis describes the phenomenon that mutations at different loci do not have independent effects with regard to certain phenotypes. Understanding the global epistatic landscape is vital for many genetic and evolutionary theories. Current knowledge for epistatic dynamics under multiple conditions is limited by the technological difficulties in experimentally screening epistatic relations among genes. We explored this issue by applying flux balance analysis to simulate epistatic landscapes under various environmental perturbations. Specifically, we looked at gene-gene epistatic interactions, where the mutations were assumed to occur in different genes. We predicted that epistasis tends to become more positive from glucose-abundant to nutrient-limiting conditions, indicating that selection might be less effective in removing deleterious mutations in the latter. We also observed a stable core of epistatic interactions in all tested conditions, as well as many epistatic interactions unique to each condition. Interestingly, genes in the stable epistatic interaction network are directly linked to most other genes whereas genes with condition-specific epistasis form a scale-free network. Furthermore, genes with stable epistasis tend to have similar evolutionary rates, whereas this co-evolving relationship does not hold for genes with condition-specific epistasis. Our findings provide a novel genome-wide picture about epistatic dynamics under environmental perturbations.

Indexed as

Epistasis, GeneticEvolution, MolecularComputer SimulationGene-Environment InteractionGene Regulatory NetworksGenes, FungalMetabolic Flux AnalysisModels, BiologicalSaccharomyces cerevisiae

Identifiers

PMID25625594
PMCPMC4308068

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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.