Evidence map›Paper›PMID 28251865›Full record

ArticleBMC evolutionary biology2017

In silico evolution of the Drosophila gap gene regulatory sequence under elevated mutational pressure.

Aleksandra A Chertkova, Joshua S Schiffman, Sergey V Nuzhdin, Konstantin N Kozlov, Maria G Samsonova, Vitaly V Gursky

Abstract read
In one paragraph

Article in BMC evolutionary biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. System drift and speciation.Evolution; international journal of organic evolution · 2022
    Article
  2. Article
  3. Evolutionary biology at BGRS\SB-2016.BMC evolutionary biology · 2017
    Article
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

6 authors.

Aleksandra A ChertkovaSystems Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia.
Joshua S SchiffmanMolecular and Computational Biology, University of Southern California, Los Angeles, 90089, CA, USA.
Sergey V NuzhdinSystems Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia.
Konstantin N KozlovSystems Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia.
Maria G SamsonovaSystems Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia.
Vitaly V GurskySystems Biology and Bioinformatics Laboratory, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia. gursky@math.ioffe.ru.

Funding

Multi-scale modeling of genetic variation in a developmental networkU01GM103804 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DEPACE, ANGELA H, MARJORAM, PAUL · 2013 to 2016
$2.0M
Blended Inheritance As a Genetic Consequence of Unlimited RegenerationR01GM098741 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI NUZHDIN, SERGEY V · 2011 to 2014
$1.3M
NIGMS NIH HHS R01 GM098741NIGMS NIH HHS U01 GM103804
6 · The paper itself

Abstract

backgroundCis-regulatory sequences are often composed of many low-affinity transcription factor binding sites (TFBSs). Determining the evolutionary and functional importance of regulatory sequence composition is impeded without a detailed knowledge of the genotype-phenotype map.

resultsWe simulate the evolution of regulatory sequences involved in Drosophila melanogaster embryo segmentation during early development. Natural selection evaluates gene expression dynamics produced by a computational model of the developmental network. We observe a dramatic decrease in the total number of transcription factor binding sites through the course of evolution. Despite a decrease in average sequence binding energies through time, the regulatory sequences tend towards organisations containing increased high affinity transcription factor binding sites. Additionally, the binding energies of separate sequence segments demonstrate ubiquitous mutual correlations through time. Fewer than 10% of initial TFBSs are maintained throughout the entire simulation, deemed 'core' sites. These sites have increased functional importance as assessed under wild-type conditions and their binding energy distributions are highly conserved. Furthermore, TFBSs within close proximity of core sites exhibit increased longevity, reflecting functional regulatory interactions with core sites.

conclusionIn response to elevated mutational pressure, evolution tends to sample regulatory sequence organisations with fewer, albeit on average, stronger functional transcription factor binding sites. These organisations are also shaped by the regulatory interactions among core binding sites with sites in their local vicinity.

Indexed as

Computer SimulationEvolution, MolecularMutationRegulatory Sequences, Nucleic AcidAnimalsBinding SitesDrosophila melanogasterDrosophila ProteinsProtein BindingSelection, GeneticTranscription FactorsDrosophila ProteinsTranscription FactorsDrosophila developmentEvolutionGap gene regulatory networkRegulatory sequenceThermodynamic expression model

Identifiers

PMID28251865
PMCPMC5333172

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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.