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      Regulation of CHD2 expression by the Chaserr long noncoding RNA gene is essential for viability

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          Abstract

          Chromodomain helicase DNA binding protein 2 ( Chd2) is a chromatin remodeller implicated in neurological disease. Here we show that Chaserr, a highly conserved long noncoding RNA transcribed from a region near the transcription start site of Chd2 and on the same strand, acts in concert with the CHD2 protein to maintain proper Chd2 expression levels. Loss of Chaserr in mice leads to early postnatal lethality in homozygous mice, and severe growth retardation in heterozygotes. Mechanistically, loss of Chaserr leads to substantially increased Chd2 mRNA and protein levels, which in turn lead to transcriptional interference by inhibiting promoters found downstream of highly expressed genes. We further show that Chaserr production represses Chd2 expression solely in cis, and that the phenotypic consequences of Chaserr loss are rescued when Chd2 is perturbed as well. Targeting Chaserr is thus a potential strategy for increasing CHD2 levels in haploinsufficient individuals.

          Abstract

          The conserved long noncoding RNA Chaserr is transcribed upstream of the chromatin remodeler Chd2. Here, using mouse genetics and high throughput assays, the authors show that Chaserr inhibits expression of Chd2 in cis and is required for postnatal mouse development.

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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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              BEDTools: a flexible suite of utilities for comparing genomic features

              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 web-based 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 Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                igor.ulitsky@weizmann.ac.il
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 November 2019
                8 November 2019
                2019
                : 10
                : 5092
                Affiliations
                [1 ]ISNI 0000 0004 0604 7563, GRID grid.13992.30, Department of Biological Regulation, , Weizmann Institute of Science, ; Rehovot, Israel
                [2 ]ISNI 0000 0004 1937 0511, GRID grid.7489.2, National Institute for Biotechnology in the Negev and Department of Microbiology, Immunology and Genetics, , Ben-Gurion University of the Negev, ; Beer-Sheva, Israel
                [3 ]ISNI 0000 0004 0604 7563, GRID grid.13992.30, Department of Molecular Cell Biology, , Weizmann Institute of Science, ; Rehovot, Israel
                [4 ]ISNI 0000 0004 0604 7563, GRID grid.13992.30, Department of Veterinary Resources, , Weizmann Institute of Science, ; Rehovot, Israel
                Author information
                http://orcid.org/0000-0003-0555-6561
                Article
                13075
                10.1038/s41467-019-13075-8
                6841665
                31704914
                ae3d96d5-37e2-4967-9aab-488d0f48d80e
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 February 2019
                : 18 October 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: lincSAFARI
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003977, Israel Science Foundation (ISF);
                Award ID: 1984/14
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100005386, Council for Higher Education of Israel | Israeli Centers for Research Excellence (I-CORE);
                Award ID: 1796/12
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                gene regulation,chromatin remodelling,long non-coding rnas
                Uncategorized
                gene regulation, chromatin remodelling, long non-coding rnas

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