The first aim of this thesis is to examine relationships between microRNAs targeting gene networks, combining knowledge from microRNA prediction databases into our microRNA Data Integration Portal (mirDIP). Modeling the microRNA:transcript interactome – referred to as the micronome – to build microRNA interaction networks of signalling pathways, we find genes within signalling pathways to be co-targeted by common microRNAs suggesting an unexpected level of transcriptional control. We identify 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, to be more studied and more involved in cancer signalling than their intrapathway counterparts. The second aim was to undertake a more focused view, analyzing the characteristics of microRNAs within the micronome itself beginning with a focus on the under-examined microRNA terminal loop across the micronome to determine if this region of the microRNA structure might contribute to microRNA functioning. We have identified 2 main classes of microRNAs based on loop structure – perfect and occluded, which show biological relevance. We found regulatory motifs within microRNA terminal loops and found a large number of Frequently Occurring Words (FOWs) significantly overrepresented across the micronome. Set analysis of in vitro secreted microRNAs, microRNA expression across a panel of normal tissues, and microRNAs shown to be secreted in lung cancer shows that specific microRNA loop motifs within these groups are significantly overreperesented – suggesting that microRNA terminal loops harbour sequences bearing microRNA processing and localization signals.

The first aim of this thesis is to examine relationships between microRNAs targeting gene networks, combining knowledge from microRNA prediction databases into our microRNA Data Integration Portal (mirDIP). Modeling the microRNA:transcript interactome – referred to as the micronome – to build microRNA interaction networks of signalling pathways, we find genes within signalling pathways to be co-targeted by common microRNAs suggesting an unexpected level of transcriptional control. We identify 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, to be more studied and more involved in cancer signalling than their intrapathway counterparts. The second aim was to undertake a more focused view, analyzing the characteristics of microRNAs within the micronome itself beginning with a focus on the under-examined microRNA terminal loop across the micronome to determine if this region of the microRNA structure might contribute to microRNA functioning. We have identified 2 main classes of microRNAs based on loop structure – perfect and occluded, which show biological relevance. We found regulatory motifs within microRNA terminal loops and found a large number of Frequently Occurring Words (FOWs) significantly overrepresented across the micronome. Set analysis of in vitro secreted microRNAs, microRNA expression across a panel of normal tissues, and microRNAs shown to be secreted in lung cancer shows that specific microRNA loop motifs within these groups are significantly overreperesented – suggesting that microRNA terminal loops harbour sequences bearing microRNA processing and localization signals.