Isoform and pathway-specific regulation of post-transcriptional RNA processing in human cells.

Steady-state levels of RNA transcripts are controlled by their rates of synthesis and degradation. Here we used nascent RNA Bru-seq and BruChase-seq to profile RNA dynamics across 16 human cell lines as part of ENCODE4 Deeply Profiled Cell Lines collection. We show that RNA turnover dynamics differ widely between transcripts of different genes and between different classes of RNA. Gene set enrichment analysis (GSEA) revealed that transcripts encoding proteins belonging to the same pathway often show similar turnover dynamics. Furthermore, transcript isoforms show distinct dynamics suggesting that RNA turnover is important in regulating mRNA isoform choice. Finally, splicing across newly made transcripts appears to be cooperative with either all or none type splicing. These data sets generated as part of ENCODE4 illustrate the intricate and coordinated regulation of RNA dynamics in controlling gene expression to allow for the precise coordination of cellular functions.

Characterizing nascent transcription patterns of PROMPTs, eRNAs, and readthrough transcripts in the ENCODE4 deeply profiled cell lines.

Arising as co-products of canonical gene expression, transcription-associated lincRNAs, such as promoter upstream transcripts (PROMPTs), enhancer RNAs (eRNAs), and readthrough (RT) transcripts, are often regarded as byproducts of transcription, although they may be important for the expression of nearby genes. We identified regions of nascent expression of these lincRNA in 16 human cell lines using Bru-seq techniques, and found distinctly regulated patterns of PROMPT, eRNA, and RT transcription using the diverse biochemical approaches in the ENCODE4 deeply profiled cell lines collection. Transcription of these lincRNAs was influenced by sequence-specific features and the local or 3D chromatin landscape. However, these sequence and chromatin features do not describe the full spectrum of lincRNA expression variability we identify, highlighting the complexity of their regulation. This may suggest that transcription-associated lincRNAs are not merely byproducts, but rather that the transcript itself, or the act of its transcription, is important for genomic function.

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity.

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3' end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of 200,000 full-length transcripts, 40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3' processing are deployed across human tissues, with nearly half of multi-transcript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.

Pleiotropic Roles of Non-Coding RNAs in TGF-ß-Mediated Epithelial-Mesenchymal Transition and Their Functions in Tumor Progression.

Epithelial-mesenchymal transition (EMT) is a spatially- and temporally-regulated process involved in physiological and pathological transformations, such as embryonic development and tumor progression. While the role of TGF-ß as an EMT-inducer has been extensively documented, the molecular mechanisms regulating this transition and their implications in tumor metastasis are still subjects of intensive debates and investigations. TGF-ß regulates EMT through both transcriptional and post-transcriptional mechanisms, and recent advances underline the critical roles of non-coding RNAs in these processes. Although microRNAs and lncRNAs have been clearly identified as effectors of TGF-ß-mediated EMT, the contributions of other atypical non-coding RNA species, such as piRNAs, snRNAs, snoRNAs, circRNAs, and even housekeeping tRNAs, have only been suggested and remain largely elusive. This review discusses the current literature including the most recent reports emphasizing the regulatory functions of non-coding RNA in TGF-ß-mediated EMT, provides original experimental evidence, and advocates in general for a broader approach in the quest of new regulatory RNAs.

SPOt: A novel and streamlined microarray platform for observing cellular tRNA levels.

Recent studies have placed transfer RNA (tRNA), a housekeeping molecule, in the heart of fundamental cellular processes such as embryonic development and tumor progression. Such discoveries were contingent on the concomitant development of methods able to deliver high-quality tRNA profiles. The present study describes the proof of concept obtained in Escherichia coli (E. coli) for an original tRNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). This approach comprises three steps. First, E. coli cultures are spiked with radioactive orthophosphate; second, labeled total RNAs are trizol-extracted; third, RNA samples are hybridized on in-house printed microarrays and spot signals, the proxy for tRNA levels, are quantified by phosphorimaging. Features such as reproducibility and specificity were assessed using several tRNA subpopulations. Dynamic range and sensitivity were evaluated by overexpressing specific tRNA species. SPOt does not require any amplification or post-extraction labeling and can be adapted to any organism. It is modular and easily streamlined with popular techniques such as polysome fractionation to profile tRNAs interacting with ribosomes and actively engaged in translation. The biological relevance of these data is discussed in regards to codon usage, tRNA gene copy number, and position on the genome.

The Enzymatic Paradox of Yeast Arginyl-tRNA Synthetase: Exclusive Arginine Transfer Controlled by a Flexible Mechanism of tRNA Recognition.

Identity determinants are essential for the accurate recognition of transfer RNAs by aminoacyl-tRNA synthetases. To date, arginine determinants in the yeast Saccharomyces cerevisiae have been identified exclusively in vitro and only on a limited number of tRNA Arginine isoacceptors. In the current study, we favor a full cellular approach and expand the investigation of arginine determinants to all four tRNA Arg isoacceptors. More precisely, this work scrutinizes the relevance of the tRNA nucleotides at position 20, 35 and 36 in the yeast arginylation reaction. We built 21 mutants by site-directed mutagenesis and tested their functionality in YAL5, a previously engineered yeast knockout deficient for the expression of tRNA Arg CCG. Arginylation levels were also monitored using Northern blot. Our data collected in vivo correlate with previous observations. C35 is the prominent arginine determinant followed by G36 or U36 (G/U36). In addition, although there is no major arginine determinant in the D loop, the recognition of tRNA Arg ICG relies to some extent on the nucleotide at position 20. This work refines the existing model for tRNA Arg recognition. Our observations indicate that yeast Arginyl-tRNA synthetase (yArgRS) relies on distinct mechanisms to aminoacylate the four isoacceptors. Finally, according to our refined model, yArgRS is able to accommodate tRNA Arg scaffolds presenting N34, C/G35 and G/A/U36 anticodons while maintaining specificity. We discuss the mechanistic and potential physiological implications of these findings.