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Using a Whole Genome Co- expression Network to Inform the Functional Characterisation of Predicted Genomic Elements from Mycobacterium tuberculosis Transcriptomic Data

Stiens, Jennifer; Yi Tan, Yen; Joyce, Rosanna; Arnvig, Kristine B.; Kendall, Sharon L.; Nobeli, Irene

Authors

Jennifer Stiens

Yen Yi Tan

Rosanna Joyce

Kristine B. Arnvig

Sharon L. Kendall

Irene Nobeli



Contributors

Sharon Kendall
Supervisor

Abstract

A 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 dataset 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.

Citation

Stiens, J., Yi Tan, Y., Joyce, R., Arnvig, K. B., Kendall, S. L., & Nobeli, I. (in press). Using a Whole Genome Co- expression Network to Inform the Functional Characterisation of Predicted Genomic Elements from Mycobacterium tuberculosis Transcriptomic Data. Molecular Microbiology, https://doi.org/10.1111/mmi.15055

Journal Article Type Article
Acceptance Date Mar 10, 2023
Online Publication Date Dec 29, 2023
Deposit Date Jun 29, 2022
Publicly Available Date Jan 10, 2024
Print ISSN 0950-382X
Publisher Wiley
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1111/mmi.15055
Keywords Mycobacterium tuberculosis; WGCNA; transcriptomic; non-coding RNA

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