Differential DNA Methylation Analysis without a Reference Genome

Cell Rep. 2015 Dec 22;13(11):2621-2633. doi: 10.1016/j.celrep.2015.11.024. Epub 2015 Dec 8.

Abstract

Genome-wide DNA methylation mapping uncovers epigenetic changes associated with animal development, environmental adaptation, and species evolution. To address the lack of high-throughput methods for DNA methylation analysis in non-model organisms, we developed an integrated approach for studying DNA methylation differences independent of a reference genome. Experimentally, our method relies on an optimized 96-well protocol for reduced representation bisulfite sequencing (RRBS), which we have validated in nine species (human, mouse, rat, cow, dog, chicken, carp, sea bass, and zebrafish). Bioinformatically, we developed the RefFreeDMA software to deduce ad hoc genomes directly from RRBS reads and to pinpoint differentially methylated regions between samples or groups of individuals (http://RefFreeDMA.computational-epigenetics.org). The identified regions are interpreted using motif enrichment analysis and/or cross-mapping to annotated genomes. We validated our method by reference-free analysis of cell-type-specific DNA methylation in the blood of human, cow, and carp. In summary, we present a cost-effective method for epigenome analysis in ecology and evolution, which enables epigenome-wide association studies in natural populations and species without a reference genome.

Keywords: DNA methylation; RRBS; bisulfite sequencing; comparative genomics; computational epigenetics; cross-species comparison; differential methylation analysis; non-model organisms; reference genome independent analysis; vertebrate genomes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Blood Cells / metabolism
  • Carps
  • Cattle
  • Chromosome Mapping
  • CpG Islands
  • DNA / chemistry
  • DNA / metabolism*
  • DNA Methylation*
  • Genome*
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Leukocytes / metabolism
  • Sequence Analysis, DNA
  • Software

Substances

  • DNA