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. 2021 Nov 22;18(4):20210029.
doi: 10.1515/jib-2021-0029.

Modular network inference between miRNA-mRNA expression profiles using weighted co-expression network analysis

Nisar Wani  1 , Debmalya Barh  2   3 , Khalid Raza  4
Affiliations

Modular network inference between miRNA-mRNA expression profiles using weighted co-expression network analysis

Nisar Wani et al. J Integr Bioinform. .

Abstract

Connecting transcriptional and post-transcriptional regulatory networks solves an important puzzle in the elucidation of gene regulatory mechanisms. To decipher the complexity of these connections, we build co-expression network modules for mRNA as well as miRNA expression profiles of breast cancer data. We construct gene and miRNA co-expression modules using the weighted gene co-expression network analysis (WGCNA) method and establish the significance of these modules (Genes/miRNAs) for cancer phenotype. This work also infers an interaction network between the genes of the turquoise module from mRNA expression data and hubs of the turquoise module from miRNA expression data. A pathway enrichment analysis using a miRsystem web tool for miRNA hubs and some of their targets, reveal their enrichment in several important pathways associated with the progression of cancer.

Keywords: gene expression; hubs; miRNA; module detection; module eigengene networks; network inference.

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Figures

Figure 1:
Figure 1:
Network construction and module detection workflow.
Figure 2:
Figure 2:
WGCNA based module association workflow.
Figure 3:
Figure 3:
Heatmap showing expression profiles: expression levels in miRNA modules (left) and expression levels in gene modules (right).
Figure 4:
Figure 4:
Gene significance of miRNA modules.
Figure 5:
Figure 5:
Gene significance of gene modules..
Figure 6:
Figure 6:
Interaction network between hub miRNAs and genes of turquoise modules.
See this image and copyright information in PMC

References

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