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      Distinct roles for CKM–Mediator in controlling Polycomb-dependent chromosomal interactions and priming genes for induction

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          Abstract

          Precise control of gene expression underpins normal development. This relies on mechanisms that enable communication between gene promoters and other regulatory elements. In embryonic stem cells (ESCs), the cyclin-dependent kinase module Mediator complex (CKM–Mediator) has been reported to physically link gene regulatory elements to enable gene expression and also prime genes for induction during differentiation. Here, we show that CKM–Mediator contributes little to three-dimensional genome organization in ESCs, but it has a specific and essential role in controlling interactions between inactive gene regulatory elements bound by Polycomb repressive complexes (PRCs). These interactions are established by the canonical PRC1 (cPRC1) complex but rely on CKM–Mediator, which facilitates binding of cPRC1 to its target sites. Importantly, through separation-of-function experiments, we reveal that this collaboration between CKM–Mediator and cPRC1 in creating long-range interactions does not function to prime genes for induction during differentiation. Instead, we discover that priming relies on an interaction-independent mechanism whereby the CKM supports core Mediator engagement with gene promoters during differentiation to enable gene activation.

          Abstract

          Here, Dimitrova et al. examine how CKM–Mediator and Polycomb shape 3D chromosome interactions in ESCs and discover that gene activation during differentiation is independent of pre-formed interactions but depends on recruitment of the core Mediator.

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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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            The Sequence Alignment/Map format and SAMtools

            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: rd@sanger.ac.uk
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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
                emilia.dimitrova@bioch.ox.ac.uk
                rob.klose@bioch.ox.ac.uk
                Journal
                Nat Struct Mol Biol
                Nat Struct Mol Biol
                Nature Structural & Molecular Biology
                Nature Publishing Group US (New York )
                1545-9993
                1545-9985
                11 October 2022
                11 October 2022
                2022
                : 29
                : 10
                : 1000-1010
                Affiliations
                [1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Biochemistry, , University of Oxford, ; Oxford, UK
                [2 ]GRID grid.430814.a, ISNI 0000 0001 0674 1393, Division of Gene Regulation, , Oncode Institute and The Netherlands Cancer Institute, ; Amsterdam, The Netherlands
                [3 ]GRID grid.7497.d, ISNI 0000 0004 0492 0584, Present Address: German Cancer Research Center (DKFZ), ; Heidelberg, Germany
                [4 ]GRID grid.419927.0, ISNI 0000 0000 9471 3191, Present Address: Hubrecht Institute KNAW, ; Utrecht, The Netherlands
                Author information
                http://orcid.org/0000-0001-5669-1240
                http://orcid.org/0000-0001-7094-8081
                http://orcid.org/0000-0002-6466-7280
                http://orcid.org/0000-0003-2883-1415
                http://orcid.org/0000-0002-8726-7888
                Article
                840
                10.1038/s41594-022-00840-5
                9568430
                36220895
                b304dd03-8cc6-4252-8c7b-304f901bdcc1
                © The Author(s) 2022

                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
                : 12 November 2021
                : 22 August 2022
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                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Molecular biology
                transcription,transcriptional regulatory elements,chromatin structure,chromatin,chromatin analysis

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