☆ 4.7 Article

RNA-seq analysis of virR and revR mutants of Clostridium perfringens

BMC GENOMICS (2016)

Journal

BMC GENOMICS

Volume 17, Issue -, Pages -

Publisher

BMC

DOI: 10.1186/s12864-016-2706-2

Keywords

RNA-seq; Gene transcription; Reciprocal gene expression; C. perfringens

Funding

Australian National Health and Medical Research Council [GNT1065985, GNT1082401]
Monash Postgraduate Scholarship

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Abstract

Background: Clostridium perfringens causes toxin-mediated diseases, including gas gangrene (clostridial myonecrosis) and food poisoning in humans. The production of the toxins implicated in gas gangrene, a-toxin and perfringolysin O, is regulated by the VirSR two-component regulatory system. In addition, RevR, an orphan response regulator, has been shown to affect virulence in the mouse myonecrosis model. RevR positively regulates the expression of genes that encode hydrolytic enzymes, including hyaluronidases and sialidases. Results: To further characterize the VirSR and RevR regulatory networks, comparative transcriptomic analysis was carried out with strand-specific RNA-seq on C. perfringens strain JIR325 and its isogenic virR and revR regulatory mutants. Using the edgeR analysis package, 206 genes in the virR mutant and 67 genes in the revR mutant were found to be differentially expressed. Comparative analysis revealed that VirR acts as a global negative regulator, whilst RevR acts as a global positive regulator. Therefore, about 95 % of the differentially expressed genes were up-regulated in the virR mutant, whereas 81 % of the differentially expressed genes were down-regulated in the revR mutant. Importantly, we identified 23 genes that were regulated by both VirR and RevR, 18 of these genes, which included the sporulation-specific spoIVA, sigG and sigF genes, were regulated positively and negatively by RevR and VirR, respectively. Furthermore, analysis of the mapped RNA-seq reads visualized as depth of coverage plots showed that there were 93 previously unannotated transcripts in intergenic regions. These transcripts potentially encode small RNA molecules. Conclusion: In conclusion, using strand-specific RNA-seq analysis, this study has identified differentially expressed chromosomal and pCP13 native plasmid-encoded genes, antisense transcripts, and transcripts within intergenic regions that are controlled by the VirSR or RevR regulatory systems.

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Addressing the mean-correlation relationship in co-expression analysis

Yi Wang, Stephanie C. Hicks, Kasper D. Hansen

Summary: Estimates of correlation between genes in co-expression analysis are commonly used to construct gene networks. However, the distribution of these correlations depends on the observed expression level, resulting in a higher correlation for highly expressed genes. This relationship is not observed in protein-protein interaction data, indicating that it is not biologically relevant. To address this issue, we propose a method called spatial quantile normalization (SpQN) that normalizes local distributions in a correlation matrix, removing the mean-correlation relationship and correcting expression bias in network reconstruction.

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