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Whole Genome Enzymatic Methylation Sequencing (EM-seq)

Whole Genome Enzymatic Methylation Sequencing (EM-seq)

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Whole Genome Bisulfite Sequencing (WGBS) is the gold standard of DNA methylome analysis, but causes DNA fragmentation and damaging, and overestimated global methylation(1).

The Enzymatic Methylation-seq (EM-Seq®, New England Biolabs, USA) workflow maximizes DNA recovery of low-input samples and constructs libraries that accurately represent sample composition. By utilizing a highly effective enzymatic conversion method, EM-Seq minimizes damages to DNA and produces high quality libraries(2).


Additionally, these advantages all contribute to EM-seq having more usable sequencing data when comparing the same number of reads for EM-seq and WGBS, which ultimately increases the effective coverage of the libraries across the genome and reduces sequencing costs.

Superior performance with EM-Seq

To demonstrate the efficient and unbiased performance of the EM-seq, comparison experiment using 10 ng plasma cell-free DNA (cfDNA) was performed between EM-seq and WGBS with the same analysis. For WGBS, Zymo Research EZ DNA Methylation-Lightning Kit for bisulfite conversion, followed by Swift® Accel-NGS Methyl-Seq Kit was used for library construction. Libraries were sequenced on an Illumina NovaSeq6000 platform.

  • EM-seq libraries achieve higher PCR yields with fewer PCR cycles (Figure A), indicating that less DNA is lost during enzymatic conversion and library preparation, as compared to WGBS.
  • Reduced PCR cycles, in turn, translates into more complex libraries and fewer PCR duplicates during sequencing (Figure B).
  • EM-seq libraries also have larger insert sizes than WGBS (Figure C), which further supports the fact that DNA remains intact.
  • Moreover, using unmethylated lambda DNA as internal reference, EM-seq has a higher conversion efficiency (Figure D).
  • In conclusion, EM-seq provides the non-bisulfite conversion method that comprehensively addresses the limitations of bisulfite sequencing and represents a new approach for more complete methylome analysis; thus, offering a new, more accurate alternative for studying disease states(3-4).


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  1. Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data. Genome Biol (2018)
  2. EM-seq: Detection of DNA Methylation at Single Base Resolution from Picograms of DNA. (2020)
  3. cfNOMe — A single assay for comprehensive epigenetic analyses of cell-free DNA. Genome Medicine (2020)
  4. Efficient and accurate determination of genome-wide DNA methylation patterns in Arabidopsis thaliana with enzymatic methyl sequencing. Epigenetics & Chromatin (2020)