Abstract
Understanding the role of DNA methylation often requires accurate assessment and comparison of these modifications in a genome-wide fashion. Sequencing-based DNA methylation profiling provides an unprecedented opportunity to map and compare complete DNA CpG methylomes. These include whole genome bisulfite sequencing (WGBS), Reduced-Representation Bisulfite-Sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. An investigator needs a method that is flexible with the quantity of input DNA, provides the appropriate balance among genomic CpG coverage, resolution, quantitative accuracy, and cost, and comes with robust bioinformatics software for analyzing the data. In this chapter, we describe four protocols that combine state-of-the-art experimental strategies with state-of-the-art computational algorithms to achieve this goal. We first introduce two experimental methods that are complementary to each other. MeDIP-seq, or methylation-dependent immunoprecipitation followed by sequencing, uses an anti-methylcytidine antibody to enrich for methylated DNA fragments, and uses massively parallel sequencing to reveal identity of enriched DNA. MRE-seq, or methylation-sensitive restriction enzyme digestion followed by sequencing, relies on a collection of restriction enzymes that recognize CpG containing sequence motifs, but only cut when the CpG is unmethylated. Digested DNA fragments enrich for unmethylated CpGs at their ends, and these CpGs are revealed by massively parallel sequencing. The two computational methods both implement advanced statistical algorithms that integrate MeDIP-seq and MRE-seq data. M&M is a statistical framework to detect differentially methylated regions between two samples. methylCRF is a machine learning framework that predicts CpG methylation levels at single CpG resolution, thus raising the resolution and coverage of MeDIP-seq and MRE-seq to a comparable level of WGBS, but only incurring a cost of less than 5% of WGBS. Together these methods form an effective, robust, and affordable platform for the investigation of genome-wide DNA methylation.
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Acknowledgments
We thank Joseph F. Costello, Ravi Nagarajan, Chibo Hong for developing the experimental protocols described in this chapter. We thank Michael Stevens for developing methylCRF. We thank Nan Lin, Yan Zhou, Boxue Zhang for developing M&M. We thank members of the Wang laboratory for testing and improving various parts of the methods. This work was supported by NIH grant U01ES017154 (T.W.), R01HG007354 (T.W.), NIDA’s R25 program DA027995 (B.Z.), and American Cancer Society grant RSG-14-049-01-DMC (T.W.).
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Xing, X., Zhang, B., Li, D., Wang, T. (2018). Comprehensive Whole DNA Methylome Analysis by Integrating MeDIP-seq and MRE-seq. In: Tost, J. (eds) DNA Methylation Protocols. Methods in Molecular Biology, vol 1708. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7481-8_12
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DOI: https://doi.org/10.1007/978-1-4939-7481-8_12
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