Whole Genome Enzymatic Methylation Sequencing

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).

 

Copyright © 2021. GENESEEQ Technology Inc. All rights reserved.

 

References

  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)