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Genetic Co-Occurrence Network across Sequenced Microbes

Overview of attention for article published in PLoS Computational Biology, December 2011
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Title
Genetic Co-Occurrence Network across Sequenced Microbes
Published in
PLoS Computational Biology, December 2011
DOI 10.1371/journal.pcbi.1002340
Pubmed ID
Authors

Pan-Jun Kim, Nathan D. Price

Abstract

The phenotype of any organism on earth is, in large part, the consequence of interplay between numerous gene products encoded in the genome, and such interplay between gene products affects the evolutionary fate of the genome itself through the resulting phenotype. In this regard, contemporary genomes can be used as molecular records that reveal associations of various genes working in their natural lifestyles. By analyzing thousands of orthologs across ∼600 bacterial species, we constructed a map of gene-gene co-occurrence across much of the sequenced biome. If genes preferentially co-occur in the same organisms, they were called herein correlogs; in the opposite case, called anti-correlogs. To quantify correlogy and anti-correlogy, we alleviated the contribution of indirect correlations between genes by adapting ideas developed for reverse engineering of transcriptional regulatory networks. Resultant correlogous associations are highly enriched for physically interacting proteins and for co-expressed transcripts, clearly differentiating a subgroup of functionally-obligatory protein interactions from conditional or transient interactions. Other biochemical and phylogenetic properties were also found to be reflected in correlogous and anti-correlogous relationships. Additionally, our study elucidates the global organization of the gene association map, in which various modules of correlogous genes are strikingly interconnected by anti-correlogous crosstalk between the modules. We then demonstrate the effectiveness of such associations along different domains of life and environmental microbial communities. These phylogenetic profiling approaches infer functional coupling of genes regardless of mechanistic details, and may be useful to guide exogenous gene import in synthetic biology.

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Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 5%
United Kingdom 3 2%
Hungary 1 <1%
Norway 1 <1%
Austria 1 <1%
Australia 1 <1%
Brazil 1 <1%
Sweden 1 <1%
Germany 1 <1%
Other 8 5%
Unknown 134 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 53 33%
Student > Ph. D. Student 36 23%
Student > Master 16 10%
Professor > Associate Professor 12 8%
Professor 10 6%
Other 18 11%
Unknown 15 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 81 51%
Biochemistry, Genetics and Molecular Biology 32 20%
Engineering 5 3%
Computer Science 4 3%
Immunology and Microbiology 4 3%
Other 13 8%
Unknown 21 13%