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      Poison cassette exon splicing of SRSF6 regulates nuclear speckle dispersal and the response to hypoxia

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          Abstract

          Hypoxia induces massive changes in alternative splicing (AS) to adapt cells to the lack of oxygen. Here, we identify the splicing factor SRSF6 as a key factor in the AS response to hypoxia. The SRSF6 level is strongly reduced in acute hypoxia, which serves a dual purpose: it allows for exon skipping and triggers the dispersal of nuclear speckles. Our data suggest that cells use dispersal of nuclear speckles to reprogram their gene expression during hypoxic adaptation and that SRSF6 plays an important role in cohesion of nuclear speckles. Down-regulation of SRSF6 is achieved through inclusion of a poison cassette exon (PCE) promoted by SRSF4. Removing the PCE 3′ splice site using CRISPR/Cas9 abolishes SRSF6 reduction in hypoxia. Aberrantly high SRSF6 levels in hypoxia attenuate hypoxia-mediated AS and impair dispersal of nuclear speckles. As a consequence, proliferation and genomic instability are increased, while the stress response is suppressed. The SRSF4–PCE–SRSF6 hypoxia axis is active in different cancer types, and high SRSF6 expression in hypoxic tumors correlates with a poor prognosis. We propose that the ultra-conserved PCE of SRSF6 acts as a tumor suppressor and that its inclusion in hypoxia is crucial to reduce SRSF6 levels. This may prevent tumor cells from entering the metastatic route of hypoxia adaptation.

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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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            Fiji: an open-source platform for biological-image analysis.

            Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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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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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                25 January 2023
                09 January 2023
                09 January 2023
                : 51
                : 2
                : 870-890
                Affiliations
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Cardiovascular Regeneration, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Buchmann Institute for Molecular Life Sciences (BMLS) , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Buchmann Institute for Molecular Life Sciences (BMLS) , Frankfurt am Main, Germany
                Buchmann Institute for Molecular Life Sciences (BMLS) , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Buchmann Institute for Molecular Life Sciences (BMLS) , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Biochemistry II, Goethe University , Frankfurt am Main, Germany
                Functional Proteomics, Institute of Cardiovascular Physiology, Goethe University , Frankfurt am Main, Germany
                Institute of Cardiovascular Regeneration, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Institute of Cardiovascular Regeneration, Goethe University , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Buchmann Institute for Molecular Life Sciences (BMLS) , Frankfurt am Main, Germany
                Institute of Molecular Biosciences, Goethe University , Frankfurt am Main, Germany
                Author notes
                To whom correspondence should be addressed. Email: mueller-mcnicoll@ 123456bio.uni-frankfurt.de
                Correspondence may also be addressed to Kathi Zarnack. Email: kathi.zarnack@ 123456bmls.de
                Author information
                https://orcid.org/0000-0003-3174-2042
                https://orcid.org/0000-0002-1045-2436
                https://orcid.org/0000-0003-3527-3378
                https://orcid.org/0000-0002-7174-8310
                Article
                gkac1225
                10.1093/nar/gkac1225
                9881134
                36620874
                b3adbb52-d795-4ac0-a81b-175299181073
                © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 10 December 2022
                : 06 December 2022
                : 10 March 2022
                Page count
                Pages: 21
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: TRR267-Z02
                Award ID: CEF-MC
                Award ID: ECCPS
                Award ID: CPI
                Award ID: TRR267-A03
                Award ID: SFB902-B13
                Award ID: TRR267-A01
                Award ID: SFB902-B13
                Categories
                AcademicSubjects/SCI00010
                RNA and RNA-protein complexes

                Genetics
                Genetics

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