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      The RNA-binding protein SFPQ preserves long-intron splicing and regulates circRNA biogenesis in mammals

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          Abstract

          Circular RNAs (circRNAs) represent an abundant and conserved entity of non-coding RNAs; however, the principles of biogenesis are currently not fully understood. Here, we identify two factors, splicing factor proline/glutamine rich (SFPQ) and non-POU domain-containing octamer-binding protein (NONO), to be enriched around circRNA loci. We observe a subclass of circRNAs, coined DALI circRNAs, with distal inverted Alu elements and long flanking introns to be highly deregulated upon SFPQ knockdown. Moreover, SFPQ depletion leads to increased intron retention with concomitant induction of cryptic splicing, premature transcription termination, and polyadenylation, particularly prevalent for long introns. Aberrant splicing in the upstream and downstream regions of circRNA producing exons are critical for shaping the circRNAome, and specifically, we identify missplicing in the immediate upstream region to be a conserved driver of circRNA biogenesis. Collectively, our data show that SFPQ plays an important role in maintaining intron integrity by ensuring accurate splicing of long introns, and disclose novel features governing Alu-independent circRNA production.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                21 January 2021
                2021
                : 10
                : e63088
                Affiliations
                [1]Department of Molecular Biology and Genetics, Aarhus University AarhusDenmark
                Centre de Regulació Genòmica (CRG) Spain
                Columbia University United States
                Centre de Regulació Genòmica (CRG) Spain
                Centre de Regulació Genòmica (CRG) Spain
                Author information
                https://orcid.org/0000-0003-1527-527X
                https://orcid.org/0000-0002-1879-4238
                https://orcid.org/0000-0003-3442-8577
                https://orcid.org/0000-0002-7573-9657
                Article
                63088
                10.7554/eLife.63088
                7819710
                33476259
                b0ea03c6-60db-4758-ba60-9c649daa1472
                © 2021, Stagsted et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 14 September 2020
                : 05 January 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100009708, Novo Nordisk Fonden;
                Award ID: NNF16OC0019874
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Chromosomes and Gene Expression
                Custom metadata
                Transcriptome and eCLIP analyses in mouse and human reveal splicing factor proline/glutamine rich (SFPQ) as a conserved and critical guardian of long-intron integrity, splicing, and circular RNA (circRNA) production.

                Life sciences
                sfpq,alternative splicing,circular rna,premature termination,human,mouse
                Life sciences
                sfpq, alternative splicing, circular rna, premature termination, human, mouse

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