Project description:Studies in epitranscriptomics indicates that RNA is modified by a variety of enzymes. Among these RNA modifications, A-to-I RNA editing occurs frequently in the mammalian transcriptome. These RNA editing sites can be detected directly from RNA-seq data by examining nucleotide changes from adenosine (A) to guanine (G), which substitutes for inosine (I). However, a careful investigation of such nucleotide changes must be conducted to distinguish sequencing errors and genomic mutations from the genuine editing sites. Building upon our recent introduction of an easy-to-use bioinformatics tool, RNAEditor, to detect RNA editing events from RNA-seq data, we examined the extent by which RNA editing events affects the binding of RNA-binding proteins (RBP). Through employing bioinformatic techniques, we uncover that RNA editing sites occur frequently in RBP-bound regions. Moreover, the presence of RNA editing sites are more frequent when RNA editing islands are examined, which are regions in which RNA editing sites are present in clusters. When the binding of one RBP, HuR, was quantified experimentally, its binding was reduced upon silencing of the RNA editing enzyme ADAR compared to the control—suggesting that the presence of RNA editing islands influences HuR binding to its target regions. These data indicate RNA editing as an important mediator of RBP-RNA interactions—a mechanism which likely constitutes an additional mode of post-transcription gene regulation in biological systems.
Project description:RNA-protein interactions determine the cellular fate of RNA and are central to regulating gene expression outcomes in health and disease. To date, no method exists to identify the proteins bound to specific regions in endogenous RNAs in an unbiased fashion. Here, we develop SHIFTR (Selective RNase-H-mediated interactome framing for target RNA regions), an efficient and scalable approach to identify proteins bound to selected RNA regions in live cells. Compared to state-of-the-art RNA antisense purification techniques, SHIFTR is superior in accuracy, captures close to zero background interactions and requires orders of magnitude lower input material. We establish SHIFTR workflows for targeting RNA biotypes of different length and abundance, including short and long non-coding RNAs, as well as mRNAs and demonstrate that SHIFTR is compatible with multiplexed RNA interactome release in a single experiment. Using SHIFTR, we comprehensively identify interactions of cis-regulatory elements located at the 5ʹ and 3ʹ-terminal regions of the authentic SARS-CoV-2 RNA genome in infected cells and accurately recover known and novel interactions linked to the function of these viral RNA elements. SHIFTR enables the systematic mapping of region-resolved RNA interactomes for any RNA in any cell type, which has the potential to revolutionize our understanding of the transcriptomes of pathogens and their hosts.
Project description:The dataset accompanying a publication describing the RNA degradosome components in Mycobacterium tuberculosis (Mtb). The RNA-bound proteome was determined by affinity purification of protein-RNA complexes from Mycobacterium bovis cells fed with 4-thiouridine and crosslinked via photoactivation at 365nm. Affinity purified RNA-protein complexes were subjected to LC-MS analysis
Project description:The goals of this study were to compare the transcriptome of six genotypes of wheat grown under the normal conditions by RNA-Seq and to study the root architecture in drought sensitive and tolerant genotypes.