Using a whole genome co‐expression network to inform the functional characterisation of predicted genomic elements from Mycobacterium tuberculosis transcriptomic data

Author:

Stiens Jennifer1,Tan Yen Yi1,Joyce Rosanna1,Arnvig Kristine B.2,Kendall Sharon L.3ORCID,Nobeli Irene1ORCID

Affiliation:

1. Institute of Structural and Molecular Biology, Biological Sciences Birkbeck, University of London London UK

2. Division of Biosciences, Institute of Structural and Molecular Biology University College London London UK

3. Royal Veterinary College, Centre for Emerging, Endemic and Exotic Diseases, Pathobiology and Population Sciences Hatfield UK

Abstract

AbstractA whole genome co‐expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA‐sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein‐coding genes. These unannotated expressed transcripts were among the best‐connected members of the module sub‐networks, making up more than half of the ‘hub’ elements in modules that include protein‐coding genes known to be part of regulatory systems involved in stress response and host adaptation. This data set provides a valuable resource for investigating the role of non‐coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.

Publisher

Wiley

Subject

Molecular Biology,Microbiology

Reference101 articles.

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2. Non-coding RNA and its potential role in Mycobacterium tuberculosis pathogenesis

3. Sequence-Based Analysis Uncovers an Abundance of Non-Coding RNA in the Total Transcriptome of Mycobacterium tuberculosis

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