Evidence map›Paper›PMID 30823869›Full record

ArticleBMC evolutionary biology2019

In silico simulations of occurrence of transcription factor binding sites in bacterial genomes.

Jan Mrázek, Anna C Karls

Open access · goldAbstract read
In one paragraph

Article in BMC evolutionary biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
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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 at 1 institution in 1 country.

Jan MrázekDepartment of Microbiology, University of Georgia, Athens, GA, USA. mrazek@uga.edu.
Anna C KarlsDepartment of Microbiology, University of Georgia, Athens, GA, USA.
University of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInteractions between transcription factors and their specific binding sites are a key component of regulation of gene expression. Until recently, it was generally assumed that most bacterial transcription factor binding sites are located at or near promoters. However, several recent works utilizing high-throughput technology to detect transcription factor binding sites in bacterial genomes found a large number of binding sites in unexpected locations, particularly inside genes, as opposed to known or expected promoter regions. While some of these intragenic binding sites likely have regulatory functions, an alternative scenario is that many of these binding sites arise by chance in the absence of selective constraints. The latter possibility was supported by in silico simulations for σ

resultsIn this work, we extend these simulations to more than forty transcription factors from E. coli and other bacteria. The results suggest that binding sites for all analyzed transcription factors are likely to arise throughout the genome by random genetic drift and many transcription factor binding sites found in genomes may not have specific regulatory functions. In addition, when comparing observed and expected patterns of occurrence of binding sites in genomes, we observed distinct differences among different transcription factors.

conclusionsWe speculate that transcription factor binding sites randomly occurring throughout the genome could be beneficial in promoting emergence of new regulatory interactions and thus facilitating evolution of gene regulatory networks.

Indexed as

Binding SitesEvolution, MolecularGenome, BacterialComputer SimulationEscherichia coliGene Regulatory NetworksPromoter Regions, GeneticProtein BindingTranscription FactorsTranscription, GeneticTranscription FactorsEvolutionGene regulatory networksPosition-specific score matrixProtein-DNA interactionsRandom sequence

Identifiers

PMID30823869
PMCPMC6397444
OpenAlexW2923454569

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.