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Elucidation of Operon Structures across Closely Related Bacterial Genomes

Overview of attention for article published in PLOS ONE, June 2014
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Title
Elucidation of Operon Structures across Closely Related Bacterial Genomes
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0100999
Pubmed ID
Authors

Chuan Zhou, Qin Ma, Guojun Li

Abstract

About half of the protein-coding genes in prokaryotic genomes are organized into operons to facilitate co-regulation during transcription. With the evolution of genomes, operon structures are undergoing changes which could coordinate diverse gene expression patterns in response to various stimuli during the life cycle of a bacterial cell. Here we developed a graph-based model to elucidate the diversity of operon structures across a set of closely related bacterial genomes. In the constructed graph, each node represents one orthologous gene group (OGG) and a pair of nodes will be connected if any two genes, from the corresponding two OGGs respectively, are located in the same operon as immediate neighbors in any of the considered genomes. Through identifying the connected components in the above graph, we found that genes in a connected component are likely to be functionally related and these identified components tend to form treelike topology, such as paths and stars, corresponding to different biological mechanisms in transcriptional regulation as follows. Specifically, (i) a path-structure component integrates genes encoding a protein complex, such as ribosome; and (ii) a star-structure component not only groups related genes together, but also reflects the key functional roles of the central node of this component, such as the ABC transporter with a transporter permease and substrate-binding proteins surrounding it. Most interestingly, the genes from organisms with highly diverse living environments, i.e., biomass degraders and animal pathogens of clostridia in our study, can be clearly classified into different topological groups on some connected components.

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The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 9%
New Zealand 1 4%
Iran, Islamic Republic of 1 4%
Unknown 19 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 39%
Researcher 6 26%
Student > Bachelor 2 9%
Other 2 9%
Student > Master 1 4%
Other 1 4%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 39%
Biochemistry, Genetics and Molecular Biology 6 26%
Unspecified 1 4%
Mathematics 1 4%
Immunology and Microbiology 1 4%
Other 2 9%
Unknown 3 13%