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

By Coby Viner, James Johnson, Nicolas Walker, Hui Shi, Marcela Sjöberg, David J. Adams, Anne C. Ferguson-Smith, Timothy L Bailey, Michael M. Hoffman

Posted 15 Mar 2016
bioRxiv DOI: 10.1101/043794

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 transcription factor binding affinities across a variety of modifications.

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