Expanding the horizons of microRNA bioinformatics

Abstract

MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult for researchers to find and analyze microRNA-related experimental data and define further research projects. We are addressing this problem by providing two new bioinformatics data sets that contain experimentally verified functional information for mammalian microRNAs involved in cardiovascular-relevant, and other, processes. To date, our resource provides over 4400 Gene Ontology annotations associated with over 500 microRNAs from human, mouse, and rat and over 2400 experimentally validated microRNA:target interactions. We illustrate how this resource can be used to create microRNA-focused interaction networks with a biological context using the known biological role of microRNAs and the mRNAs they regulate, enabling discovery of associations between gene products, biological pathways and, ultimately, diseases. This data will be crucial in advancing the field of microRNA bioinformatics and will establish consistent data sets for reproducible functional analysis of microRNAs across all biological research areas.

Non-coding RNA regulatory networks

“…All of these manually curated resources are essential sources of information, whereas both text-mining and predictions may retrieve a huge number of false positives that can be filtered only if gold standards of true interactors, strongly supported from experiments, exist. Recently, members of the Gene Ontology (GO) Consortium have been capturing experimentally validated microRNA interactions [71]. Specific guidelines have been developed to ensure consistent annotation of the experimental data [72] and the majority of these annotations include the GO term 'mRNA binding' (or child terms) with information about the target RNA (as an Ensembl gene ID) included in the 'annotation extension' field [73].…”

miRinGO: Prediction of biological processes indirectly targeted by human microRNAs

“…Using miRinGO, we can include potential target genes even if there is no physical interaction between miRNA and the regulated genes. In order to validate this method, we used a dataset of miRNAs and their known targeted GO terms [27]. Although this dataset is considered a significant step towards having a gold standard to validate different miRNA pathway or GO analysis tools, it is still limited to a fraction of human miRNAs and focused more on cardiovascular-related processes.…”

“…To validate our method, we used a 'gold standard' dataset of miRNAs and their experimentally validated functions (GO terms) [27] Supplementary Table S1.…”

Gene Ontology: A Resource for Analysis and Interpretation of Alzheimer’s Disease Data

“…Historically, GO was used specifically for annotation of proteins. Recently, the GO Consortium has extended the range of gene products that are annotated; rather than only annotating proteins some members of the GO Consortium are now annotating protein complexes (43) and microRNAs (26,44,45). To curate these entities, it has been necessary to create new identifiers (43,46) and develop strict guidelines to ensure that a consistent annotation approach is applied.…”

“…Furthermore, in these cases the annotation extension will be used to capture the identifier of the targeted mRNA. The resulting interaction data are not only available in the GO annotation files, but also within the EBI-GOA-miRNA dataset from the PSICQUIC web server (45).…”