MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation

Qu, Jianghan; Zhou, Meng; Song, Qiang; Hong, Elizabeth E.; Smith, Andrew D.

doi:10.1093/bioinformatics/btt459

Cited by 44 publications

(54 citation statements)

References 12 publications

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“…A guide to use of OxyBS is available: https://github.com/ Christensen-Lab-Dartmouth/OxyBS. A similar method has been developed to simultaneously estimate 5hmC, 5mC from BS-seq, oxBS-seq and TAB-seq experiments (Qu et al, 2013). Key features of our OxyBS software are its implementation in R and its compatibility with the popular Illumina Infinium arrays.…”

Section: Methodsmentioning

confidence: 99%

OxyBS: estimation of 5-methylcytosine and 5-hydroxymethylcytosine from tandem-treated oxidative bisulfite and bisulfite DNA

2016

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Summary: The use of sodium bisulfite (BS) treatment followed by hybridization to an Illumina Infinium BeadChip (HumanMethylation450 and MethylationEPIC) is a common method for interrogating 5-methylcytosine (5mC) at single nucleotide resolution. However, standard treatment of DNA with BS does not allow disambiguation of 5mC from an additional cytosine modification, 5-hydroxymethylcytosine (5hmC). Recently, it has been demonstrated that paired BS and oxidative bisulfite (oxBS) treatment on the same sample followed by hybridization to an Infinium microarray permits the differentiation of 5hmC from 5mC. Nevertheless, estimation of 5hmC and 5mC from tandem-treated arrays has been shown to produce irregular estimates of cytosine modifications. Results: We present a novel method using maximum likelihood estimation to accurately estimate the parameters of unmethylated cytosine (5C), 5mC and 5hmC from Infinium microarray data given the signal intensities from the oxBS and BS replicates. Availability and Implementation: OxyBS is an R package available on CRAN.

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Section: Methodsmentioning

confidence: 99%

OxyBS: estimation of 5-methylcytosine and 5-hydroxymethylcytosine from tandem-treated oxidative bisulfite and bisulfite DNA

2016

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“…To estimate the percentage of methylation and hydroxymethylation at each cytosine and to understand their distribution in the genome we used the maximum likelihood methylation levels (MLML) method described by Qu et al (22). This approach combines information from MethylC-Seq and oxBS-Seq to arrive at maximum likelihood estimates for the 5mC and 5hmC levels per cytosine.…”

Section: Significancementioning

confidence: 99%

5-hydroxymethylcytosine accumulation in postmitotic neurons results in functional demethylation of expressed genes

Mellén

Ayata

Heintz

2017

Proc. Natl. Acad. Sci. U.S.A.

137

140

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5-hydroxymethylcytosine (5hmC) occurs at maximal levels in postmitotic neurons, where its accumulation is cell-specific and correlated with gene expression. Here we demonstrate that the distribution of 5hmC in CG and non-CG dinucleotides is distinct and that it reflects the binding specificity and genome occupancy of methylcytosine binding protein 2 (MeCP2). In expressed gene bodies, accumulation of 5hmCG acts in opposition to 5mCG, resulting in “functional” demethylation and diminished MeCP2 binding, thus facilitating transcription. Non-CG hydroxymethylation occurs predominantly in CA dinucleotides (5hmCA) and it accumulates in regions flanking active enhancers. In these domains, oxidation of 5mCA to 5hmCA does not alter MeCP2 binding or expression of adjacent genes. We conclude that the role of 5-hydroxymethylcytosine in postmitotic neurons is to functionally demethylate expressed gene bodies while retaining the role of MeCP2 in chromatin organization.

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“…These estimates are computed directly or via expectation maximization. 60 It outputs an indicator of the number of conflicts, which is an estimate of methylation or hydroxymethylation levels falling outside of the confidence interval computed from the input coverage and level. This value is 0, 1, or 2 in our case, since we have two inputs per run (WGBS and oxWGBS).…”

Section: Creation Of An Expanded-alphabet Genome Sequencementioning

confidence: 99%

Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet

Viner

Johnson

Walker

et al. 2016

Preprint

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Introduction. Many transcription factors initiate transcription only in specific sequence contexts, providing the means for sequence specificity of transcriptional control. A four-letter DNA alphabet only partially describes the possible diversity of nucleobases a transcription factor might encounter. For instance, cytosine is often present in a covalently modified form: 5-methylcytosine (5mC). 5mC can be successively oxidized to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC). Just as transcription factors distinguish one unmodified nucleobase from another, some have been shown to distinguish unmodified bases from these covalently modified bases. Modification-sensitive transcription factors provide a mechanism by which widespread changes in DNA methylation and hydroxymethylation can dramatically shift active gene expression programs.Methods. To understand the effect of modified nucleobases on gene regulation, we developed methods to discover motifs and identify transcription factor binding sites in DNA with covalent modifications. Our models expand the standard A/C/G/T alphabet, adding m (5mC) h (5hmC), f (5fC), and c (5caC). We additionally add symbols to encode guanine complementary to these modified cytosine nucleobases, as well as symbols to represent states of ambiguous modification. We adapted the well-established position weight matrix model of transcription factor binding affinity to an expanded alphabet. We developed a program, Cytomod, to create a modified sequence. We also enhanced the MEME Suite to be able to handle custom alphabets. These versions permit users to specify new alphabets, anticipating future alphabet expansions.Results. We created an expanded-alphabet sequence using whole-genome maps of 5mC and 5hmC in naive ex vivo mouse T cells. Using this sequence and ChIP-seq data from Mouse ENCODE and others, we identified modification-sensitive cis-regulatory modules. We elucidated various known methylation binding preferences, including the preference of ZFP57 and C/EBPβ for methylated motifs and the preference of c-Myc for unmethylated E-box motifs. We demonstrated that our method is robust to parameter perturbations, with transcription factors' sensitivities for methylated and hydroxymethylated DNA broadly conserved across a range of modified base calling thresholds. Hypothesis testing across different threshold values was used to determine cutoffs most suitable for further analyses. Using these known binding preferences to tune model parameters enables discovery of novel modified motifs.Discussion. Hypothesis testing of motif central enrichment provides a natural means of differentially assessing modified versus unmodified binding affinity, without most of the limitations of a de novo analysis. This approach can be readily extended to other DNA modifications, provided genome-wide single-base resolution data is available. As more high-resolution epigenomic data becomes available, we expect this method to continue to yield insights into altered tra...

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MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation

Cited by 44 publications

References 12 publications

OxyBS: estimation of 5-methylcytosine and 5-hydroxymethylcytosine from tandem-treated oxidative bisulfite and bisulfite DNA

OxyBS: estimation of 5-methylcytosine and 5-hydroxymethylcytosine from tandem-treated oxidative bisulfite and bisulfite DNA

5-hydroxymethylcytosine accumulation in postmitotic neurons results in functional demethylation of expressed genes

Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet

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