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      Statistical methods for detecting differentially methylated loci and regions

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          Abstract

          DNA methylation, the reversible addition of methyl groups at CpG dinucleotides, represents an important regulatory layer associated with gene expression. Changed methylation status has been noted across diverse pathological states, including cancer. The rapid development and uptake of microarrays and large scale DNA sequencing has prompted an explosion of data analytic methods for processing and discovering changes in DNA methylation across varied data types. In this mini-review, we present a compact and accessible discussion of many of the salient challenges, such as experimental design, statistical methods for differential methylation detection, critical considerations such as cell type composition and the potential confounding that can arise from batch effects. From a statistical perspective, our main interests include the use of empirical Bayes or hierarchical models, which have proved immensely powerful in genomics, and the procedures by which false discovery control is achieved.

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          Most cited references32

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          Epigenetic programming by maternal behavior.

          Here we report that increased pup licking and grooming (LG) and arched-back nursing (ABN) by rat mothers altered the offspring epigenome at a glucocorticoid receptor (GR) gene promoter in the hippocampus. Offspring of mothers that showed high levels of LG and ABN were found to have differences in DNA methylation, as compared to offspring of 'low-LG-ABN' mothers. These differences emerged over the first week of life, were reversed with cross-fostering, persisted into adulthood and were associated with altered histone acetylation and transcription factor (NGFI-A) binding to the GR promoter. Central infusion of a histone deacetylase inhibitor removed the group differences in histone acetylation, DNA methylation, NGFI-A binding, GR expression and hypothalamic-pituitary-adrenal (HPA) responses to stress, suggesting a causal relation among epigenomic state, GR expression and the maternal effect on stress responses in the offspring. Thus we show that an epigenomic state of a gene can be established through behavioral programming, and it is potentially reversible.
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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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              Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution.

              5-Methylcytosine can be converted to 5-hydroxymethylcytosine (5hmC) in mammalian DNA by the ten-eleven translocation (TET) enzymes. We introduce oxidative bisulfite sequencing (oxBS-Seq), the first method for quantitative mapping of 5hmC in genomic DNA at single-nucleotide resolution. Selective chemical oxidation of 5hmC to 5-formylcytosine (5fC) enables bisulfite conversion of 5fC to uracil. We demonstrate the utility of oxBS-Seq to map and quantify 5hmC at CpG islands (CGIs) in mouse embryonic stem (ES) cells and identify 800 5hmC-containing CGIs that have on average 3.3% hydroxymethylation. High levels of 5hmC were found in CGIs associated with transcriptional regulators and in long interspersed nuclear elements, suggesting that these regions might undergo epigenetic reprogramming in ES cells. Our results open new questions on 5hmC dynamics and sequence-specific targeting by TETs.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                16 September 2014
                2014
                : 5
                : 324
                Affiliations
                [1] 1Institute of Molecular Life Sciences, University of Zurich Zurich, Switzerland
                [2] 2SIB Swiss Institute of Bioinformatics, University of Zurich Zurich, Switzerland
                Author notes

                Edited by: Shihua Zhang, Chinese Academy of Science, China

                Reviewed by: Helder I. Nakaya, Emory University, USA; Xinghua Shi, University of North Carolina at Charlotte, USA; Wenyuan Li, University of Southern California, USA

                *Correspondence: Mark D. Robinson, Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland e-mail: mark.robinson@ 123456imls.uzh.ch

                This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Genetics.

                Article
                10.3389/fgene.2014.00324
                4165320
                25278959
                cca50025-5ee6-402e-a728-2c540db9ff67
                Copyright © 2014 Robinson, Kahraman, Law, Lindsay, Nowicka, Weber and Zhou.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 July 2014
                : 29 August 2014
                Page count
                Figures: 0, Tables: 2, Equations: 0, References: 66, Pages: 7, Words: 5753
                Categories
                Genetics
                Mini Review Article

                Genetics
                differential methylation,bisulphite sequencing,cell type composition,beta-binomial
                Genetics
                differential methylation, bisulphite sequencing, cell type composition, beta-binomial

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