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      Altered BAF occupancy and transcription factor dynamics in PBAF-deficient melanoma

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          SUMMARY

          ARID2 is the most recurrently mutated SWI/SNF complex member in melanoma; however, its tumor-suppressive mechanisms in the context of the chromatin landscape remain to be elucidated. Here, we model ARID2 deficiency in melanoma cells, which results in defective PBAF complex assembly with a concomitant genomic redistribution of the BAF complex. Upon ARID2 depletion, a subset of PBAF and shared BAF-PBAF-occupied regions displays diminished chromatin accessibility and associated gene expression, while BAF-occupied enhancers gain chromatin accessibility and expression of genes linked to the process of invasion. As a function of altered accessibility, the genomic occupancy of melanoma-relevant transcription factors is affected and significantly correlates with the observed transcriptional changes. We further demonstrate that ARID2-deficient cells acquire the ability to colonize distal organs in multiple animal models. Taken together, our results reveal a role for ARID2 in mediating BAF and PBAF subcomplex chromatin dynamics with consequences for melanoma metastasis.

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          In brief

          The tumor-suppressive functions of the SWI/SNF subunit ARID2 remain ill-defined in the context of melanoma. Carcamo et al. demonstrate that, upon ARID2 depletion, the PBAF complex fails to assemble, altering BAF genomic occupancy with consequences on chromatin accessibility, transcription factor binding, and transcriptional changes that promote metastasis.

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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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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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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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                Author and article information

                Journal
                101573691
                39703
                Cell Rep
                Cell Rep
                Cell reports
                2211-1247
                8 April 2022
                05 April 2022
                16 April 2022
                : 39
                : 1
                : 110637
                Affiliations
                [1 ]Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [2 ]Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [3 ]Division of Hematology and Oncology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [4 ]Department of Otolaryngology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [5 ]Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [6 ]Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [7 ]Tisch Cancer Institute Bioinformatics for Next Generation Sequencing (BiNGS) Shared Resource Facility, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
                [8 ]Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA
                [9 ]Department of Pathology and Laura & Isaac Perlmutter Cancer Center, New York, NY 10016, USA
                [10 ]Applied Bioinformatics Laboratories, NYU School of Medicine, New York, NY 10016, USA
                [11 ]Present address: Department of Cell Biology, Department of Medicine-Oncology, Cancer Dormancy and Tumor Microenvironment Institute, Gruss-Lipper Biophotonics Center, Albert Einstein Cancer Center, Ruth L. and David S. Gottesman Institute for Stem Cell Research and Regenerative Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA
                [12 ]These authors contributed equally
                [13 ]Lead contact
                Author notes

                AUTHOR CONTRIBUTIONS

                Conceptualization, S.C., D.H., and E.B.; investigation, S.C., D.H., C.B.N., E.G., D.F., A.A., A.D., J.I., and D.S.; formal analysis, S.C., D.H., C.B.N., and T.C.M.; writing – original draft, S.C. and E.B; writing – review & editing, S.C., D.H., C.B.N., E.G., D.F., J.A.A.-G., T.C.M., E.C.D., and E.B.; visualization, S.C. and D.H.; resources, expertise, and methods, I.A., J.A.A.-G., R.P., A.T., and E.C.D.; data curation, S.C., C.B.N., S.N., and D.H.; supervision, E.C.D., D.H., and E.B.; funding acquisition, R.P., J.A.A.-G., E.C.D., and E.B.

                Article
                NIHMS1795992
                10.1016/j.celrep.2022.110637
                9013128
                35385731
                afca22d3-2dac-4b4a-a31c-abb3b3263505

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                Cell biology
                Cell biology

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