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      USP15 Deubiquitinase Safeguards Hematopoiesis and Genome Integrity in Hematopoietic Stem Cells and Leukemia Cells

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          Summary

          Altering ubiquitination by disruption of deubiquitinating enzymes (DUBs) affects hematopoietic stem cell (HSC) maintenance. However, comprehensive knowledge of DUB function during hematopoiesis in vivo is lacking. Here, we systematically inactivate DUBs in mouse hematopoietic progenitors using in vivo small hairpin RNA (shRNA) screens. We find that multiple DUBs may be individually required for hematopoiesis and identify ubiquitin-specific protease 15 (USP15) as essential for HSC maintenance in vitro and in transplantations and Usp15 knockout (KO) mice in vivo. USP15 is highly expressed in human hematopoietic tissues and leukemias. USP15 depletion in murine progenitors and leukemia cells impairs in vitro expansion and increases genotoxic stress. In leukemia cells, USP15 interacts with and stabilizes FUS (fused in sarcoma), a known DNA repair factor, directly linking USP15 to the DNA damage response (DDR). Our study underscores the importance of DUBs in preserving normal hematopoiesis and uncovers USP15 as a critical DUB in safeguarding genome integrity in HSCs and leukemia cells.

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          Highlights

          • In vivo shRNAs screens for deubiquitinases identify regulators of murine hematopoiesis

          • Usp15 deletion compromises HSC maintenance and reconstitution potential in vivo

          • USP15 loss affects genome integrity and growth of mHSPCs and human leukemia cells

          • In human leukemia cells, USP15 stabilizes its interactor, FUS, a DNA repair factor

          Abstract

          Van den Berk et al. use unbiased in vivo RNAi screens targeting deubiquitinases in mouse hematopoietic stem and progenitor cells. This study underscores the importance of deubiquitinases in hematopoietic stem cell function and reveals the role of USP15 in preserving genome integrity in normal and transformed hematopoietic cells.

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.

            The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. © 2012 AACR.
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              MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

              Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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                Author and article information

                Contributors
                Journal
                Cell Rep
                Cell Rep
                Cell Reports
                Cell Press
                2211-1247
                29 December 2020
                29 December 2020
                29 December 2020
                : 33
                : 13
                : 108533
                Affiliations
                [1 ]Division of Tumor Biology and Immunology, the Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, the Netherlands
                [2 ]Division of Molecular Genetics, the Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, the Netherlands
                [3 ]Max-Delbrück-Center for Molecular Medicine (MDC), Robert-Rössle-Str. 10, 13092 Berlin, Germany
                [4 ]Transgenic Core Facility, Mouse Clinic for Cancer and Aging (MCCA), the Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, the Netherlands
                [5 ]Division of Experimental Animal Pathology, the Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, the Netherlands
                [6 ]Proteomics Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Berlin Institute of Health, Robert Rössle Strasse 10, 13125 Berlin, Germany
                [7 ]ONCODE Institute, Utrecht, the Netherlands
                Author notes
                []Corresponding author gaetano.gargiulo@ 123456mdc-berlin.de
                [∗∗ ]Corresponding author elisabetta.citterio@ 123456gmail.com
                [8]

                These authors contributed equally

                [9]

                Senior author

                [10]

                Lead Contact

                Article
                S2211-1247(20)31522-9 108533
                10.1016/j.celrep.2020.108533
                7788286
                33378683
                18300b7c-d963-488d-97fa-bc23377eb31d
                © 2020 The Author(s)

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

                History
                : 29 January 2020
                : 28 July 2020
                : 25 November 2020
                Categories
                Article

                Cell biology
                hematopoietic stem cell,hsc,usp15,deubiquitinating enzymes,deubiquitinase,in vivo shrna screen,leukemia,dna damage response,genome integrity,fus,fused in sarcoma,rnai

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