CGB - Universidad Mayor

13 diciembre 2019

Identification of Modules With Similar Gene Regulation and Metabolic Functions Based on Co-expression Data.

DOI : 10.3389/fmolb.2019.00139


Biological systems respond to environmental perturbations and to a large

diversity of compounds through gene interactions, and these genetic factors

comprise complex networks. In particular, a wide variety of gene co-expression

networks have been constructed in recent years thanks to the dramatic increase

of experimental information obtained with techniques, such as microarrays and

RNA sequencing. These networks allow the identification of groups of

co-expressed genes that can function in the same process and, in turn, these

networks may be related to biological functions of industrial, medical and

academic interest. In this study, gene co-expression networks for 17 bacterial

organisms from the COLOMBOS database were analyzed via weighted gene

co-expression network analysis and clustered into modules of genes with similar

expression patterns for each species. These networks were analyzed to determine

relevant modules through a hypergeometric approach based on a set of

transcription factors and enzymes for each genome. The richest modules were

characterized using PFAM families and KEGG metabolic maps. Additionally, we

conducted a Gene Ontology analysis for enrichment of biological functions.

Finally, we identified modules that shared similarity through all the studied

organisms by using comparative genomics.

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