Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods

  1. Ting Wang1,2,9
  1. 1Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63108, USA;
  2. 2Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA;
  3. 3Department of Dermatology, University of California, San Francisco, San Francisco, California 94143, USA;
  4. 4Brain Tumor Research Center, Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California 94143, USA;
  5. 5Department of Medical Oncology, Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
  6. 6Departments of Pathology, Brigham and Women's Hospital, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts 02115, USA;
  7. 7BC Cancer Agency, Canada's Michael Smith Genome Sciences Centre Vancouver, British Columbia, V5Z 4S6, Canada;
  8. 8Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada

    Abstract

    Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. These include whole-genome bisulfite sequencing (WGBS, MethylC-seq, or BS-seq), reduced-representation bisulfite sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. These methods yield largely comparable results but differ significantly in extent of genomic CpG coverage, resolution, quantitative accuracy, and cost, at least while using current algorithms to interrogate the data. None of these existing methods provides single-CpG resolution, comprehensive genome-wide coverage, and cost feasibility for a typical laboratory. We introduce methylCRF, a novel conditional random fields–based algorithm that integrates methylated DNA immunoprecipitation (MeDIP-seq) and methylation-sensitive restriction enzyme (MRE-seq) sequencing data to predict DNA methylation levels at single-CpG resolution. Our method is a combined computational and experimental strategy to produce DNA methylomes of all 28 million CpGs in the human genome for a fraction (<10%) of the cost of whole-genome bisulfite sequencing methods. methylCRF was benchmarked for accuracy against Infinium arrays, RRBS, WGBS sequencing, and locus-specific bisulfite sequencing performed on the same human embryonic stem cell line. methylCRF transformation of MeDIP-seq/MRE-seq was equivalent to a biological replicate of WGBS in quantification, coverage, and resolution. We used conventional bisulfite conversion, PCR, cloning, and sequencing to validate loci where our predictions do not agree with whole-genome bisulfite data, and in 11 out of 12 cases, methylCRF predictions of methylation level agree better with validated results than does whole-genome bisulfite sequencing. Therefore, methylCRF transformation of MeDIP-seq/MRE-seq data provides an accurate, inexpensive, and widely accessible strategy to create full DNA methylomes.

    Footnotes

    • 9 Corresponding authors

      E-mail jcostello{at}cc.ucsf.edu

      E-mail twang{at}genetics.wustl.edu

    • [Supplemental material is available for this article.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.152231.112.

    • Received November 18, 2012.
    • Accepted June 13, 2013.

    This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.

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