ABSTRACT
MOTIVATION: Long-read RNA sequencing enables the mapping of RNA modifications, structures, and protein-interaction sites at the resolution of individual transcript isoforms. To understand the functions of these RNA features, it is critical to analyze them in the context of transcriptomic and genomic annotations, such as open reading frames and splice junctions. RESULTS: We have developed R2Dtool, a bioinformatics tool that integrates transcript-mapped information with transcript and genome annotations, allowing for the isoform-resolved analytics and graphical representation of RNA features in their genomic context. We illustrate R2Dtool's capability to integrate and expedite RNA feature analysis using epitranscriptomics data. R2Dtool facilitates the comprehensive analysis and interpretation of alternative transcript isoforms. AVAILABILITY AND IMPLEMENTATION: R2Dtool is freely available under the MIT license at github.com/comprna/R2Dtool.
Subject(s)
Sequence Analysis, RNA , Software , Sequence Analysis, RNA/methods , Computational Biology/methods , RNA Isoforms/genetics , Humans , RNA/chemistry , Transcriptome/geneticsABSTRACT
Maps of the RNA modification 5-methylcytosine (m5C) often diverge markedly not only because of differences in detection methods, data depand analysis pipelines but also biological factors. We re-analysed bisulfite RNA sequencing datasets from five human cell lines and seven tissues using a coherent m5C site calling pipeline. With the resulting union list of 6,393 m5C sites, we studied site distribution, enzymology, interaction with RNA-binding proteins and molecular function. We confirmed tRNA:m5C methyltransferases NSUN2 and NSUN6 as the main mRNA m5C "writers," but further showed that the rRNA:m5C methyltransferase NSUN5 can also modify mRNA. Each enzyme recognises mRNA features that strongly resemble their canonical substrates. By analysing proximity between mRNA m5C sites and footprints of RNA-binding proteins, we identified new candidates for functional interactions, including the RNA helicases DDX3X, involved in mRNA translation, and UPF1, an mRNA decay factor. We found that lack of NSUN2 in HeLa cells affected both steady-state levels of, and UPF1-binding to, target mRNAs. Our studies emphasise the emerging diversity of m5C writers and readers and their effect on mRNA function.
Subject(s)
5-Methylcytosine , Methyltransferases , Protein Biosynthesis , RNA, Messenger , Humans , 5-Methylcytosine/metabolism , RNA, Messenger/metabolism , RNA, Messenger/genetics , Methyltransferases/metabolism , Methyltransferases/genetics , HeLa Cells , RNA-Binding Proteins/metabolism , RNA-Binding Proteins/genetics , Substrate Specificity , Methylation , RNA Stability/genetics , tRNA MethyltransferasesABSTRACT
Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.