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NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

Shirdel EA, Xie W, Mak TW, Jurisica I - PLoS ONE (2011)

Bottom Line: Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling.We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.

ABSTRACT

Background: MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP).

Results: mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs.

Conclusions: Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

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Related in: MedlinePlus

Expression of universe and intra-pathway microRNAs.Universe microRNAs are expressed in a broader panel of tissues than intra-pathway microRNAs [96].
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pone-0017429-g008: Expression of universe and intra-pathway microRNAs.Universe microRNAs are expressed in a broader panel of tissues than intra-pathway microRNAs [96].

Mentions: This may be either because universe microRNAs have been discovered earlier purely by chance and thus were more studied, or they may truly be more universal and thus were easier to discover under many conditions. To provide additional evidence to answer this question, we considered expression of microRNAs across a panel of tissues from Landgraf et al. [85]. Figure 8 shows a heatmap comparing universe and intra-pathway microRNA expression across tissues, confirming that universe microRNAs are more widely expressed than intra-pathway microRNAs. Thus, it is more likely that universe microRNAs are more broadly affecting varying cell types, and through their misexpression, universe microRNAs have the opportunity to create a more global change quickly by affecting genes in many different pathways. To further understand their role in human disease thus warrants further research.


NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

Shirdel EA, Xie W, Mak TW, Jurisica I - PLoS ONE (2011)

Expression of universe and intra-pathway microRNAs.Universe microRNAs are expressed in a broader panel of tissues than intra-pathway microRNAs [96].
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3045450&req=5

pone-0017429-g008: Expression of universe and intra-pathway microRNAs.Universe microRNAs are expressed in a broader panel of tissues than intra-pathway microRNAs [96].
Mentions: This may be either because universe microRNAs have been discovered earlier purely by chance and thus were more studied, or they may truly be more universal and thus were easier to discover under many conditions. To provide additional evidence to answer this question, we considered expression of microRNAs across a panel of tissues from Landgraf et al. [85]. Figure 8 shows a heatmap comparing universe and intra-pathway microRNA expression across tissues, confirming that universe microRNAs are more widely expressed than intra-pathway microRNAs. Thus, it is more likely that universe microRNAs are more broadly affecting varying cell types, and through their misexpression, universe microRNAs have the opportunity to create a more global change quickly by affecting genes in many different pathways. To further understand their role in human disease thus warrants further research.

Bottom Line: Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling.We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.

ABSTRACT

Background: MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP).

Results: mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs.

Conclusions: Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

Show MeSH
Related in: MedlinePlus