RNALocate: a resource for RNA subcellular localizations

Abstract

Increasing evidence has revealed that RNA subcellular localization is a very important feature for deeply understanding RNA's biological functions after being transported into intra- or extra-cellular regions. RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. The current version of RNALocate documents more than 37 700 manually curated RNA subcellular localization entries with experimental evidence, involving more than 21 800 RNAs with 42 subcellular localizations in 65 species, mainly including Homo sapiens, Mus musculus and Saccharomyces cerevisiae etc. Besides, RNA homology, sequence and interaction data have also been integrated into RNALocate. Users can access these data through online search, browse, blast and visualization tools. In conclusion, RNALocate will be of help in elucidating the entirety of RNA subcellular localization, and developing new prediction methods. The database is available at http://www.rna-society.org/rnalocate/.

Characterization of the nuclear and cytosolic transcriptomes in human brain tissue reveals new insights into the subcellular distribution of RNA transcripts

“…Examples of snoRNA with extreme nucleus bias include SNORD114-12 and SNORD113-8 ( Figure 1C). Overall, the PCA and distribution of the different transcripts are in agreement with previous findings and indicate that our analysis readily identifies transcripts with a previously demonstrated cytosolic or nuclear localization 33 .…”

“…It is becoming increasingly evident that subcellular localization of lncRNAs is strongly associated with their function. In light of this, ongoing efforts such as the LncATLAS and RNALocate are aiming to establish a complete map for subcellular localization of lncRNAs in various tissue types 3,29 . So far, these databases rely on data from cell lines and lack knowledge about the subcellular localization of lncRNA in tissues and during development.…”

“…However, transcriptome analysis using RNA sequencing has primarily been performed on total or polyA+ RNA from whole cells, overlooking the spatial dimension of gene expression at the subcellular level. Nevertheless, an increasing number of reports are pointing to the importance of investigating the subcellular repertoire of RNA molecules and understanding the mechanisms that govern their distribution inside the cell [1][2][3][4] . Subcellular RNA localization is widespread and conserved from bacteria to mammals, and it is becoming evident that this process plays crucial roles in regulating gene expression 5,6 .…”

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

“…Novel datasets were obtained to build our enrichment categories, consisting of Gene Ontology [25], miRTarBase 8.0 [15], KEGG [26], miRandola 2017 [22], miRPathDB 2.0 [16], TissueAtlas [17], MNDR v2.0 [19], NPInter 4.0 [27], RNALocate v2.0 [21], TAM 2.0 [13], and TransmiR v2.0 [20]. Other pre-existing datasets have been updated, including HMDD v3.0 [18] and miRBase v22.1 [28].…”

“…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.…”