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      Feminization of Male Mouse Liver by Persistent Growth Hormone Stimulation: Activation of Sex-Biased Transcriptional Networks and Dynamic Changes in Chromatin States

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          ABSTRACT

          Sex-dependent pituitary growth hormone (GH) secretory profiles—pulsatile in males and persistent in females—regulate the sex-biased, STAT5-dependent expression of hundreds of genes in mouse liver, imparting sex differences in hepatic drug/lipid metabolism and disease risk. Here, we examine transcriptional and epigenetic changes induced by continuous GH infusion (cGH) in male mice, which rapidly feminizes the temporal profile of liver STAT5 activity. cGH repressed 86% of male-biased genes and induced 68% of female-biased genes within 4 days; however, several highly female-specific genes showed weak or no feminization, even after 14 days of cGH treatment. Female-biased genes already in an active chromatin state in male liver generally showed early cGH responses; genes in an inactive chromatin state often responded late. Early cGH-responsive genes included those encoding two GH/STAT5-regulated transcriptional repressors: male-biased BCL6, which was repressed, and female-specific CUX2, which was induced. Male-biased genes activated by STAT5 and/or repressed by CUX2 were enriched for early cGH repression. Female-biased BCL6 targets were enriched for early cGH derepression. Changes in sex-specific chromatin accessibility and histone modifications accompanied these cGH-induced sex-biased gene expression changes. Thus, the temporal, sex-biased gene responses to persistent GH stimulation are dictated by GH/STAT5-regulated transcription factors arranged in a hierarchical network and by the dynamics of changes in sex-biased epigenetic states.

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.

              Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
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                Author and article information

                Journal
                Mol Cell Biol
                Mol. Cell. Biol
                mcb
                mcb
                MCB
                Molecular and Cellular Biology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0270-7306
                1098-5549
                10 July 2017
                12 September 2017
                1 October 2017
                12 September 2017
                : 37
                : 19
                : e00301-17
                Affiliations
                Department of Biology and Bioinformatics Program, Boston University, Boston, Massachusetts, USA
                Author notes
                Address correspondence to David J. Waxman, djw@ 123456bu.edu .
                [*]

                Present address: Alexander Suvorov, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Massachusetts, USA.

                Citation Lau-Corona D, Suvorov A, Waxman DJ. 2017. Feminization of male mouse liver by persistent growth hormone stimulation: activation of sex-biased transcriptional networks and dynamic changes in chromatin states. Mol Cell Biol 37:e00301-17. https://doi.org/10.1128/MCB.00301-17.

                Author information
                http://orcid.org/0000-0001-7982-9206
                Article
                00301-17
                10.1128/MCB.00301-17
                5599723
                28694329
                dfa877f2-9754-48c0-8f3e-419ee08388e4
                Copyright © 2017 Lau-Corona et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 31 May 2017
                : 27 June 2017
                : 3 July 2017
                Page count
                supplementary-material: 2, Figures: 10, Tables: 2, Equations: 0, References: 73, Pages: 23, Words: 14425
                Funding
                Funded by: HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) https://doi.org/10.13039/100000062
                Award ID: DK33765
                Award Recipient : David J. Waxman
                Categories
                Research Article
                Spotlight
                Custom metadata
                October 2017

                Molecular biology
                dnase hypersensitivity,sexual dimorphism,hepatocellular carcinoma,cytochrome p450,liver zonation,hypophysectomy,trim24,h3-k27me3,dhs

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