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      A nucleosome switch primes Hepatitis B Virus infection

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          Summary:

          Chronic hepatitis B virus (HBV) infection is an incurable global health threat responsible for causing liver disease and hepatocellular carcinoma. During the genesis of infection, HBV establishes an independent minichromosome consisting of the viral covalently closed circular DNA (cccDNA) genome and host histones. The viral X gene must be expressed immediately upon infection to induce degradation of the host silencing factor, Smc5/6. However, the relationship between cccDNA chromatinization and X gene transcription remains poorly understood. Establishing a reconstituted viral minichromosome platform, we found that nucleosome occupancy in cccDNA drives X transcription. We corroborated these findings in cells and further showed that the chromatin destabilizing molecule CBL137 inhibits X transcription and HBV infection in hepatocytes. Our results shed light on a long-standing paradox and represent a potential new therapeutic avenue for the treatment of chronic HBV infection.

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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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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
                Role: ConceptualizationRole: MethodologyRole: InvestigationRole: VisualizationRole: Writing – Original DraftRole: Writing – Review & EditingRole: Project AdministrationRole: Funding acquisition
                Role: MethodologyRole: InvestigationRole: VisualizationRole: Writing – Review & EditingRole: Funding acquisition
                Role: MethodologyRole: InvestigationRole: Writing – Review & Editing
                Role: MethodologyRole: InvestigationRole: Writing – Review & Editing
                Role: InvestigationRole: VisualizationRole: Writing – Review & Editing
                Role: MethodologyRole: InvestigationRole: Writing – Review & Editing
                Role: InvestigationRole: Writing – Review & Editing
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: MethodologyRole: InvestigationRole: Writing – Review & EditingRole: SupervisionRole: Project AdministrationRole: Funding acquisition
                Role: ConceptualizationRole: Writing – Review & EditingRole: SupervisionRole: Project AdministrationRole: Funding acquisition
                Role: ConceptualizationRole: Writing – Original DraftRole: Writing – Review & EditingRole: SupervisionRole: Project AdministrationRole: Funding acquisition
                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                12 June 2024
                : 2023.03.03.531011
                Affiliations
                [1 ]Tri-Institutional PhD Program in Chemical Biology; New York, NY 10065, USA
                [2 ]Chemical Biology Program, Memorial Sloan Kettering Cancer Center; New York, NY 10065, USA
                [3 ]Laboratory of Genome Architecture and Dynamics, The Rockefeller University; New York, NY 10065, USA
                [4 ]Division of Gastroenterology & Hepatology, Department of Medicine, Weill Cornell Medicine; New York, NY 10065, USA
                [5 ]Department of Pharmacology, Weill Cornell Medicine; New York, NY 10065, USA
                [6 ]Epigenetics Research Innovation Lab, Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center; New York, NY 10065, USA
                [7 ]Department of Physiology and Biophysics, Weill Cornell Medicine; New York, NY 10065, USA
                [8 ]These authors contributed equally
                [9 ]Lead Contact
                Author notes
                Author information
                http://orcid.org/0000-0002-0635-8906
                http://orcid.org/0000-0002-6607-4016
                http://orcid.org/0000-0001-9711-575X
                http://orcid.org/0000-0001-8152-7127
                http://orcid.org/0000-0002-6085-7423
                http://orcid.org/0000-0001-6798-9384
                http://orcid.org/0000-0002-2484-6161
                http://orcid.org/0000-0002-6820-5083
                http://orcid.org/0000-0003-2670-8704
                http://orcid.org/0000-0002-5417-5995
                http://orcid.org/0000-0003-1696-0025
                Article
                10.1101/2023.03.03.531011
                11195122
                38915612
                c35c2a0e-f3cc-4d7b-9d0c-1672363e1424

                This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.

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                hepatitis b virus,chromatin,nucleosome stability,epigenetics,transcription

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