Exploring Evidence of Non-coding RNA Translation With Trips-Viz and GWIPS-Viz Browsers

Detection of translation in so-called non-coding RNA provides an opportunity for identification of novel bioactive peptides and microproteins. The main methods used for these purposes are ribosome profiling and mass spectrometry. A number of publicly available datasets already exist for a substantial number of different cell types grown under various conditions, and public data mining is an attractive strategy for identification of translation in non-coding RNAs. Since the analysis of publicly available data requires intensive data processing, several data resources have been created recently for exploring processed publicly available data, such as OpenProt, GWIPS-viz, and Trips-Viz. In this work we provide a detailed demonstration of how to use the latter two tools for exploring experimental evidence for translation of RNAs hitherto classified as non-coding. For this purpose, we use a set of transcripts with substantially different patterns of ribosome footprint distributions. We discuss how certain features of these patterns can be used as evidence for or against genuine translation. During our analysis we concluded that the MTLN mRNA, previously misannotated as lncRNA LINC000116, likely encodes only a short proteoform expressed from shorter RNA transcript variants.

Automated summary

The detection of translation in non-coding RNAs provides an opportunity for identifying novel bioactive peptides and microproteins, with ribosome profiling and mass spectrometry being the main methods used. Public data mining is an attractive strategy for this purpose, but it requires intensive data processing. Researchers in this study used tools like OpenProt, GWIPS-viz, and Trips-Viz to explore the translation in non-coding RNAs, and found evidence suggesting that the MTLN mRNA, previously misannotated, likely encodes only a short proteoform.