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      methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles

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          Abstract

          DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation, cellular specification and cancer development. Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statistically significant regions of differential methylation and stratify tumor subtypes. methylKit is available at http://code.google.com/p/methylkit.

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          Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning.

          Shawn Cokus, Suhua Feng, Xiaoyu Zhang … (2008)
          Cytosine DNA methylation is important in regulating gene expression and in silencing transposons and other repetitive sequences. Recent genomic studies in Arabidopsis thaliana have revealed that many endogenous genes are methylated either within their promoters or within their transcribed regions, and that gene methylation is highly correlated with transcription levels. However, plants have different types of methylation controlled by different genetic pathways, and detailed information on the methylation status of each cytosine in any given genome is lacking. To this end, we generated a map at single-base-pair resolution of methylated cytosines for Arabidopsis, by combining bisulphite treatment of genomic DNA with ultra-high-throughput sequencing using the Illumina 1G Genome Analyser and Solexa sequencing technology. This approach, termed BS-Seq, unlike previous microarray-based methods, allows one to sensitively measure cytosine methylation on a genome-wide scale within specific sequence contexts. Here we describe methylation on previously inaccessible components of the genome and analyse the DNA methylation sequence composition and distribution. We also describe the effect of various DNA methylation mutants on genome-wide methylation patterns, and demonstrate that our newly developed library construction and computational methods can be applied to large genomes such as that of mouse.
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            Role for DNA methylation in genomic imprinting.

            E Li, C. Beard, R Jaenisch (1993)
            The paternal and maternal genomes are not equivalent and both are required for mammalian development. The difference between the parental genomes is believed to be due to gamete-specific differential modification, a process known as genomic imprinting. The study of transgene methylation has shown that methylation patterns can be inherited in a parent-of-origin-specific manner, suggesting that DNA methylation may play a role in genomic imprinting. The functional significance of DNA methylation in genomic imprinting was strengthened by the recent finding that CpG islands (or sites) in three imprinted genes, H19, insulin-like growth factor 2 (Igf-2), and Igf-2 receptor (Igf-2r), are differentially methylated depending on their parental origin. We have examined the expression of these three imprinted genes in mutant mice that are deficient in DNA methyltransferase activity. We report here that expression of all three genes was affected in mutant embryos: the normally silent paternal allele of the H19 gene was activated, whereas the normally active paternal allele of the Igf-2 gene and the active maternal allele of the Igf-2r gene were repressed. Our results demonstrate that a normal level of DNA methylation is required for controlling differential expression of the paternal and maternal alleles of imprinted genes.
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              Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome.

              Miao Yu, Gary C. Hon, Keith E. Szulwach … (2012)
              The study of 5-hydroxylmethylcytosines (5hmC) has been hampered by the lack of a method to map it at single-base resolution on a genome-wide scale. Affinity purification-based methods cannot precisely locate 5hmC nor accurately determine its relative abundance at each modified site. We here present a genome-wide approach, Tet-assisted bisulfite sequencing (TAB-Seq), that when combined with traditional bisulfite sequencing can be used for mapping 5hmC at base resolution and quantifying the relative abundance of 5hmC as well as 5mC. Application of this method to embryonic stem cells not only confirms widespread distribution of 5hmC in the mammalian genome but also reveals sequence bias and strand asymmetry at 5hmC sites. We observe high levels of 5hmC and reciprocally low levels of 5mC near but not on transcription factor-binding sites. Additionally, the relative abundance of 5hmC varies significantly among distinct functional sequence elements, suggesting different mechanisms for 5hmC deposition and maintenance. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Altuna Akalin
                Matthias Kormaksson
                Sheng Li
                Francine E Garrett-Bakelman
                Maria E Figueroa
                Ari Melnick
                Christopher E Mason
                Journal
                Journal ID (nlm-ta): Genome Biol
                Journal ID (iso-abbrev): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central
                ISSN (Print): 1465-6906
                ISSN (Electronic): 1465-6914
                Publication date (Print): 2012
                Publication date (Electronic): 3 October 2012
                Volume: 13
                Issue: 10
                Page: R87
                Affiliations
                [1 ]Department of Physiology and Biophysics, 1305 York Ave., Weill Cornell Medical College, New York, NY 10065, USA
                [2 ]The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, 1305 York Ave., Weill Cornell Medical College, New York, NY 10065, USA
                [3 ]Department of Public Health, Weill Cornell Medical College, 1300 York Ave., New York, NY 10065, USA
                [4 ]Department of Medicine, Division of Hematology/Oncology, 1300 York Ave., Weill Cornell Medical College, New York, NY 10065, USA
                [5 ]Department of Pathology, University of Michigan, 109 Zina Pitcher Place, Ann Arbor, MI 48109, USA
                [6 ]Department of Pharmacology, 1300 York Ave., Weill Cornell Medical College, New York, NY 10065, USA
                Article
                Publisher ID: gb-2012-13-10-r87
                DOI: 10.1186/gb-2012-13-10-r87
                PMC ID: 3491415
                PubMed ID: 23034086
                SO-VID: 2fb82f3d-4d3e-4158-84f4-714ed83960e9
                Copyright © Copyright ©2012 Akalin et al.; licensee BioMed Central Ltd.
                License:

                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
                Date received : 30 April 2012
                Date revision received : 12 June 2012
                Date accepted : 3 October 2012
                Categories
                Subject: Software

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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