Splicing of Nascent RNA Coincides with Intron Exit from RNA Polymerase II.
TL;DR: Two single-molecule nascent RNA sequencing methods are presented that directly determine the progress of splicing catalysis as a function of Pol II position and it is proposed that matched rates streamline the gene expression pathway, while allowing regulation through kinetic competition.
About: This article is published in Cell.The article was published on 2016-04-07 and is currently open access. It has received 195 citations till now. The article focuses on the topics: RNA splicing & Intron.
Citations
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TL;DR: Circular RNAs represent a large class of RNA molecules that are tightly regulated, and it is becoming increasingly clear that they likely impact many biological processes.
Abstract: The first circular RNA (circRNA) was identified more than 40 years ago, but it was only recently appreciated that circRNAs are common outputs of many eukaryotic protein-coding genes. Some circRNAs accumulate to higher levels than their associated linear mRNAs, especially in the nervous system, and have clear regulatory functions that result in organismal phenotypes. The pre-mRNA splicing machinery generates circRNAs via backsplicing reactions, which are often facilitated by intronic repeat sequences that base pair to one another and bring the intervening splice sites into close proximity. When spliceosomal components are limiting, circRNAs can become the preferred gene output, and backsplicing reactions are further controlled by exon skipping events and the combinatorial action of RNA binding proteins. This allows circRNAs to be expressed in a tissue- and stage-specific manner. Once generated, circRNAs are highly stable transcripts that often accumulate in the cytoplasm. The functions of most circRNAs remain unknown, but some can regulate the activities of microRNAs or be translated to produce proteins. Circular RNAs can further interface with the immune system as well as control gene expression events in the nucleus, including alternative splicing decisions. Circular RNAs thus represent a large class of RNA molecules that are tightly regulated, and it is becoming increasingly clear that they likely impact many biological processes. This article is categorized under: RNA Processing > Splicing Mechanisms RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution RNA Evolution and Genomics > Computational Analyses of RNA.
317 citations
TL;DR: The intricacies of the CTD code is discussed and how the newly characterized physicochemical properties ofThe CTD expand the function of theCTD beyond the code.
Abstract: The carboxy-terminal domain (CTD) extends from the largest subunit of RNA polymerase II (Pol II) as a long, repetitive and largely unstructured polypeptide chain. Throughout the transcription process, the CTD is dynamically modified by post-translational modifications, many of which facilitate or hinder the recruitment of key regulatory factors of Pol II that collectively constitute the 'CTD code'. Recent studies have revealed how the physicochemical properties of the CTD promote phase separation in the presence of other low-complexity domains. Here, we discuss the intricacies of the CTD code and how the newly characterized physicochemical properties of the CTD expand the function of the CTD beyond the code.
303 citations
TL;DR: Techniques that allow the temporal coordination of co-transcriptional splicing to occur on similar timescales are discussed, including spliceosome assembly, transcription elongation and other co- transcriptional events that allow for spatially constrained splicing.
Abstract: Several macromolecular machines collaborate to produce eukaryotic messenger RNA. RNA polymerase II (Pol II) translocates along genes that are up to millions of base pairs in length and generates a flexible RNA copy of the DNA template. This nascent RNA harbours introns that are removed by the spliceosome, which is a megadalton ribonucleoprotein complex that positions the distant ends of the intron into its catalytic centre. Emerging evidence that the catalytic spliceosome is physically close to Pol II in vivo implies that transcription and splicing occur on similar timescales and that the transcription and splicing machineries may be spatially constrained. In this Review, we discuss aspects of spliceosome assembly, transcription elongation and other co-transcriptional events that allow the temporal coordination of co-transcriptional splicing.
252 citations
TL;DR: It is described how circRNAs impact gene expression of their host gene locus by affecting transcriptional initiation and elongation or splicing, and how they partake in controlling the function of other molecules, for example by interacting with microRNAs and proteins.
Abstract: Protein-coding and noncoding genes in eukaryotes are typically expressed as linear messenger RNAs, with exons arranged colinearly to their genomic order. Recent advances in sequencing and in mapping RNA reads to reference genomes have revealed that thousands of genes express also covalently closed circular RNAs. Many of these circRNAs are stable and contain exons, but are not translated into proteins. Here, we review the emerging understanding that both, circRNAs produced by co- and posttranscriptional head-to-tail "backsplicing" of a downstream splice donor to a more upstream splice acceptor, as well as circRNAs generated from intronic lariats during colinear splicing, may exhibit physiologically relevant regulatory functions in eukaryotes. We describe how circRNAs impact gene expression of their host gene locus by affecting transcriptional initiation and elongation or splicing, and how they partake in controlling the function of other molecules, for example by interacting with microRNAs and proteins. We conclude with an outlook how circRNA dysregulation affects disease, and how the stability of circRNAs might be exploited in biomedical applications.
250 citations
Cites background from "Splicing of Nascent RNA Coincides w..."
...At the same time, yet other studies document that transcriptional pausing is not observed when RNAP II transcribed past a normal 3′ splice site during linear splicing [102] raising the question whether the speed of elongation is indeed a physiological determinant in the antagonism between linear splicing and backsplicing....
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TL;DR: The current understanding of the relationship between transcriptional elongation through a chromatin template and co-transcriptional splicing including alternative splicing decisions that affect the expression of most human genes is summarized.
223 citations
Cites background or methods from "Splicing of Nascent RNA Coincides w..."
...Seminal work in budding yeast using anti-pol II ChIP-seq strongly suggests that at a splicing-dependent transcriptional pause occurs at 3′ splice sites [20,63]; however, these pause sites have yet to be confirmed by nascent RNA sequencing [58]....
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...017 transcripts enriched by either high salt urea washing of chromatin [21,58] or anti-pol II immunoprecipitation [59]....
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...Recently, long-range sequencing of nascent transcripts from their 3′ ends revealed that in yeasts, co-transcriptional splicing can be completed by the time pol II has extended only 25–30 bases beyond the 3′ splice site [58]....
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References
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TL;DR: SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Abstract: Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Availability: http://samtools.sourceforge.net
Contact: [email protected]
45,957 citations
TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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TL;DR: The command-line tool cutadapt is developed, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features.
Abstract: When small RNA is sequenced on current sequencing machines, the resulting reads are usually longer than the RNA and therefore contain parts of the 3' adapter. That adapter must be found and removed error-tolerantly from each read before read mapping. Previous solutions are either hard to use or do not offer required features, in particular support for color space data. As an easy to use alternative, we developed the command-line tool cutadapt, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features. Cutadapt, including its MIT-licensed source code, is available for download at http://code.google.com/p/cutadapt/
20,255 citations
TL;DR: A new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format, which allows the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks.
Abstract: Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing webbased methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools
18,858 citations
TL;DR: TopHat2 is described, which incorporates many significant enhancements to TopHat, and combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.
Abstract: TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
11,380 citations