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Understanding cooperativity of microRNAs via microRNA association networks.

Na YJ, Kim JH - BMC Genomics (2013)

Bottom Line: In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner.On the system level, we identified cooperatively regulating miRNAs in the miRNA association network.We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar.

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ABSTRACT

Background: MicroRNAs (miRNAs) are key components in post-transcriptional gene regulation in multicellular organisms. As they control cooperatively a large number of their target genes, they affect the complexity of gene regulation. One of the challenges to understand miRNA-mediated regulation is to identify co-regulating miRNAs that simultaneously regulate their target genes in a network perspective.

Results: We created miRNA association network by using miRNAs sharing target genes based on sequence complementarity and co-expression patterns of miRNA-target pairs. The degree of association between miRNAs can be assessed by the level of concordance between targets of miRNAs. Cooperatively regulating miRNAs have been identified by network topology-based approach. Cooperativity of miRNAs is evaluated by their shared transcription factors and functional coherence of target genes. Pathway enrichment analysis of target genes in the cooperatively regulating miRNAs revealed the mutually exclusive functional landscape of miRNA cooperativity. In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner. Sequence and structural similarity analysis within miRNA association network showed that pre-miRNA secondary structure may be involved in the expression of mature miRNA's function.

Conclusions: On the system level, we identified cooperatively regulating miRNAs in the miRNA association network. We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar. This study demonstrates the potential importance of the secondary structures of pre-miRNAs in both cooperativity and specificity of target genes.

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Heatmap of over-represented biological pathways of target genes of CMM. Color gradient represents statistical significance as the -log10 (p-value) in the hypergeometric test for enrichment analysis using (A) KEGG pathway and (B) BioCarta pathway. Red indicates significant associations while blue indicates insignificant associations.
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Figure 4: Heatmap of over-represented biological pathways of target genes of CMM. Color gradient represents statistical significance as the -log10 (p-value) in the hypergeometric test for enrichment analysis using (A) KEGG pathway and (B) BioCarta pathway. Red indicates significant associations while blue indicates insignificant associations.

Mentions: The biology of miRNA function will be dictated by the mRNA transcripts targeted by specific miRNAs [16]. Functional enrichment analysis of miRNA's target transcripts hence can be used as a proxy for evaluation of the functional coherence of CMMs. We performed functional enrichment analysis by using all KEGG and BioCarta pathways for each CMM. Heat maps in Figure 4(A) and 4(B) exhibit-log10 p-values obtained by hypergeometric tests between (horizontal axis) CMMs' target transcripts and (vertical axis) KEGG and BioCarta pathways. All pathways mapped to at least one CMM and all modules mapped to at least one pathway appear in the Heat maps. Those modules and pathways that have no mapping at all are omitted from each heat map. Ten (i.e., CMMs 1~9 and 12) and nine (i.e., CMMs 1~9) CMMs have at least one KEGG and BioCarta pathway mappings, respectively.


Understanding cooperativity of microRNAs via microRNA association networks.

Na YJ, Kim JH - BMC Genomics (2013)

Heatmap of over-represented biological pathways of target genes of CMM. Color gradient represents statistical significance as the -log10 (p-value) in the hypergeometric test for enrichment analysis using (A) KEGG pathway and (B) BioCarta pathway. Red indicates significant associations while blue indicates insignificant associations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3852507&req=5

Figure 4: Heatmap of over-represented biological pathways of target genes of CMM. Color gradient represents statistical significance as the -log10 (p-value) in the hypergeometric test for enrichment analysis using (A) KEGG pathway and (B) BioCarta pathway. Red indicates significant associations while blue indicates insignificant associations.
Mentions: The biology of miRNA function will be dictated by the mRNA transcripts targeted by specific miRNAs [16]. Functional enrichment analysis of miRNA's target transcripts hence can be used as a proxy for evaluation of the functional coherence of CMMs. We performed functional enrichment analysis by using all KEGG and BioCarta pathways for each CMM. Heat maps in Figure 4(A) and 4(B) exhibit-log10 p-values obtained by hypergeometric tests between (horizontal axis) CMMs' target transcripts and (vertical axis) KEGG and BioCarta pathways. All pathways mapped to at least one CMM and all modules mapped to at least one pathway appear in the Heat maps. Those modules and pathways that have no mapping at all are omitted from each heat map. Ten (i.e., CMMs 1~9 and 12) and nine (i.e., CMMs 1~9) CMMs have at least one KEGG and BioCarta pathway mappings, respectively.

Bottom Line: In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner.On the system level, we identified cooperatively regulating miRNAs in the miRNA association network.We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: MicroRNAs (miRNAs) are key components in post-transcriptional gene regulation in multicellular organisms. As they control cooperatively a large number of their target genes, they affect the complexity of gene regulation. One of the challenges to understand miRNA-mediated regulation is to identify co-regulating miRNAs that simultaneously regulate their target genes in a network perspective.

Results: We created miRNA association network by using miRNAs sharing target genes based on sequence complementarity and co-expression patterns of miRNA-target pairs. The degree of association between miRNAs can be assessed by the level of concordance between targets of miRNAs. Cooperatively regulating miRNAs have been identified by network topology-based approach. Cooperativity of miRNAs is evaluated by their shared transcription factors and functional coherence of target genes. Pathway enrichment analysis of target genes in the cooperatively regulating miRNAs revealed the mutually exclusive functional landscape of miRNA cooperativity. In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner. Sequence and structural similarity analysis within miRNA association network showed that pre-miRNA secondary structure may be involved in the expression of mature miRNA's function.

Conclusions: On the system level, we identified cooperatively regulating miRNAs in the miRNA association network. We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar. This study demonstrates the potential importance of the secondary structures of pre-miRNAs in both cooperativity and specificity of target genes.

Show MeSH