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      Histone H3 lysine 4 acetylation and methylation dynamics define breast cancer subtypes

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          Abstract

          The onset and progression of breast cancer are linked to genetic and epigenetic changes that alter the normal programming of cells. Epigenetic modifications of DNA and histones contribute to chromatin structure that result in the activation or repression of gene expression. Several epigenetic pathways have been shown to be highly deregulated in cancer cells. Targeting specific histone modifications represents a viable strategy to prevent oncogenic transformation, tumor growth or metastasis. Methylation of histone H3 lysine 4 has been extensively studied and shown to mark genes for expression; however this residue can also be acetylated and the specific function of this alteration is less well known. To define the relative roles of histone H3 methylation (H3K4me3) and acetylation (H3K4ac) in breast cancer, we determined genomic regions enriched for both marks in normal-like (MCF10A), transformed (MCF7) and metastatic (MDA-MB-231) cells using a genome-wide ChIP-Seq approach. Our data revealed a genome-wide gain of H3K4ac associated with both early and late breast cancer cell phenotypes, while gain of H3K4me3 was predominantly associated with late stage cancer cells. Enrichment of H3K4ac was over-represented at promoters of genes associated with cancer-related phenotypic traits, such as estrogen response and epithelial-to-mesenchymal transition pathways. Our findings highlight an important role for H3K4ac in predicting epigenetic changes associated with early stages of transformation. In addition, our data provide a valuable resource for understanding epigenetic signatures that correlate with known breast cancer-associated oncogenic pathways.

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          Most cited references30

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          Identifying ChIP-seq enrichment using MACS.

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
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            BigWig and BigBed: enabling browsing of large distributed datasets

            Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
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              Manipulation of FASTQ data with Galaxy

              Summary: Here, we describe a tool suite that functions on all of the commonly known FASTQ format variants and provides a pipeline for manipulating next generation sequencing data taken from a sequencing machine all the way through the quality filtering steps. Availability and Implementation: This open-source toolset was implemented in Python and has been integrated into the online data analysis platform Galaxy (public web access: http://usegalaxy.org; download: http://getgalaxy.org). Two short movies that highlight the functionality of tools described in this manuscript as well as results from testing components of this tool suite against a set of previously published files are available at http://usegalaxy.org/u/dan/p/fastq Contact: james.taylor@emory.edu; anton@bx.psu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                2 February 2016
                15 January 2016
                : 7
                : 5
                : 5094-5109
                Affiliations
                1 Department of Biochemistry and University of Vermont Cancer Center, University of Vermont College of Medicine, Burlington, VT, USA
                Author notes
                Correspondence to: Gary S. Stein, gary.stein@ 123456uvm.edu
                Article
                6922
                10.18632/oncotarget.6922
                4868673
                26783963
                9901da26-b25c-4209-9df1-0bfd1355fc8d
                Copyright: © 2016 Messier et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 September 2015
                : 6 January 2016
                Categories
                Priority Research Paper

                Oncology & Radiotherapy
                epigenetics,breast cancer,estrogen receptor pathway,emt pathway,histone h3k4 modifications

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