miRCarta: a central repository for collecting miRNA candidates

Abstract

The continuous increase of available biological data as consequence of modern high-throughput technologies poses new challenges for analysis techniques and database applications. Especially for miRNAs, one class of small non-coding RNAs, many algorithms have been developed to predict new candidates from next-generation sequencing data. While the amount of publications describing novel miRNA candidates keeps steadily increasing, the current gold standard database for miRNAs - miRBase - has not been updated since June 2014. As a result, publications describing new miRNA candidates in the last three to five years might have a substantial overlap of candidates without noticing. With miRCarta we implemented a database to collect novel miRNA candidates and augment the information provided by miRBase. In the first stage, miRCarta is thought to be a highly sensitive collection of potential miRNA candidates with a high degree of analysis functionality, annotations and details on each miRNA. We added—besides the full content of the miRBase—12,857 human miRNA precursors to miRCarta. Users can match their own predictions to the entries of miRCarta to reduce potential redundancies in their studies. miRCarta provides the most comprehensive collection of human miRNAs and miRNA candidates to form a basis for further refinement and validation studies. The database is freely accessible at https://mircarta.cs.uni-saarland.de/.

miRSwitch: Detecting microRNA arm shift and switch events

“…From the table, single precursors can be selected and detailed information for these candidates are provided. These include links to external databases (miRBase [35] and miRCarta [15]), the sequence and structure, a pie chart on the arm distribution and detailed distribution per annotation group. All information can be displayed either as percentages or absolute values in the bar diagrams.…”

“…However, not all mature miRNAs might be available in miRBase. In addition, several studies pointed out the erroneous nature of many mature miRNAs in miRBase [15,41,42,30]. Another challenge is the underlying technology.…”

“…Another challenge is the underlying technology. It is well known that expression of miRNAs, similar to other non coding RNAs, mRNAs or proteins, varies depending on the experimental techniques and protocols [15,41,42,43]. Most of the data sets used in the reference map stem from Illumina Sequencing By Synthesis instruments, which may show e.g.…”

“…Previous work also demonstrates that arm shifts are specific for tissue types and the distribution of the dominant mature and the miR* sequence can change [13,14]. For several precursor hairpins, significant quantities of mature miRNAs from both arms are known [15] and both of them are biologically functional. The dominant arm represses translation by means of AGO1 and the miR* sequence by means of AGO2 [16].…”

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

“…All kinds of enrichment tools rely on high quality sets of miRNA categories that were either obtained by curation of scientific literature or collected from specific databases. For instance, curated miRNA annotations can be obtained from miRBase or miRCarta [14], miRNA-target interactions from miRTarBase [15], miRNA-pathway associations from miRPathDB [16], tissuespecific miRNAs from the human TissueAtlas [17], or miRNA-disease associations from HMDD [18] or MNDR [19], many of which were updated in the last two years. Further specialised annotations like miRNA and transcription factor interactions provided by TransmiR [20], miRNA sub-cellular localisations collected in RNALocate [21], or extra-cellular circulating miRNAs contained in miRandola [22] provide target categories for integrated enrichment analysis.…”