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      Cytosine methylation changes in enhancer regions of core pro-fibrotic genes characterize kidney fibrosis development

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          Abstract

          Background

          One in eleven people is affected by chronic kidney disease, a condition characterized by kidney fibrosis and progressive loss of kidney function. Epidemiological studies indicate that adverse intrauterine and postnatal environments have a long-lasting role in chronic kidney disease development. Epigenetic information represents a plausible carrier for mediating this programming effect. Here we demonstrate that genome-wide cytosine methylation patterns of healthy and chronic kidney disease tubule samples obtained from patients show significant differences.

          Results

          We identify differentially methylated regions and validate these in a large replication dataset. The differentially methylated regions are rarely observed on promoters, but mostly overlap with putative enhancer regions, and they are enriched in consensus binding sequences for important renal transcription factors. This indicates their importance in gene expression regulation. A core set of genes that are known to be related to kidney fibrosis, including genes encoding collagens, show cytosine methylation changes correlating with downstream transcript levels.

          Conclusions

          Our report raises the possibility that epigenetic dysregulation plays a role in chronic kidney disease development via influencing core pro-fibrotic pathways and can aid the development of novel biomarkers and future therapeutics.

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          Most cited references28

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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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            Principles and challenges of genomewide DNA methylation analysis.

            Methylation of cytosine bases in DNA provides a layer of epigenetic control in many eukaryotes that has important implications for normal biology and disease. Therefore, profiling DNA methylation across the genome is vital to understanding the influence of epigenetics. There has been a revolution in DNA methylation analysis technology over the past decade: analyses that previously were restricted to specific loci can now be performed on a genome-scale and entire methylomes can be characterized at single-base-pair resolution. However, there is such a diversity of DNA methylation profiling techniques that it can be challenging to select one. This Review discusses the different approaches and their relative merits and introduces considerations for data analysis.
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              Cancer genetics and epigenetics: two sides of the same coin?

              Epigenetic and genetic alterations have long been thought of as two separate mechanisms participating in carcinogenesis. A recent outcome of whole exome sequencing of thousands of human cancers has been the unexpected discovery of many inactivating mutations in genes that control the epigenome. These mutations have the potential to disrupt DNA methylation patterns, histone modifications, and nucleosome positioning and hence, gene expression. Genetic alteration of the epigenome therefore contributes to cancer just as epigenetic process can cause point mutations and disable DNA repair functions. This crosstalk between the genome and the epigenome offers new possibilities for therapy. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2013
                7 October 2013
                : 14
                : 10
                : R108
                Affiliations
                [1 ]Renal Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania United States,, 415 Curie Blvd, Philadelphia, PA 19104, USA
                [2 ]Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
                [3 ]Department of Pathology, Montefiore Medical Center, Bronx, NY 10461, USA
                [4 ]Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
                [5 ]Department of Oncology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
                [6 ]Case Western Reserve University, Cleveland, Ohio 44106, USA
                Article
                gb-2013-14-10-r108
                10.1186/gb-2013-14-10-r108
                4053753
                24098934
                b52dc085-2f26-4dde-9833-c68bd5b976af
                Copyright © 2013 Ko et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 April 2013
                : 7 October 2013
                Categories
                Research

                Genetics
                Genetics

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