Abstract 820: Enzymatic Methyl-Seq: methylome analysis of challenging DNA samples

Abstract

Abstract DNA isolated from blood draws (cell-free DNA (cfDNA)) or from archival material like formalin fixed paraffin embedded (FFPE) tissues have advanced the field of cancer genetics. DNA methylation (5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC)) is a key epigenetic factor that plays an important role in cellular processes and it’s misregulation results in diseased states like cancer. Advances in the field of sample preparation from biological matrices and genomics have enabled cancer biomarker identification based on methylation profiling. Bisulfite sequencing is the standard method to detect methylation and has been employed for both targeted and whole genome methylation analysis. However, the chemical based bisulfite conversion of cytosines to uracils also results in DNA damage which subsequently results in shorter DNA insert sizes as well as introducing bias into the data. Robust biomarker detection relies primarily on the ability to profile methylation accurately. Analysis of DNA methylation from cfDNA and FFPE DNA is challenging as the DNA is typically of low quality and quantity. To overcome the drawbacks of bisulfite sequencing, we developed an enzyme based methylation detection technology, called NEBNext Enzymatic Methyl-Seq (EM-Seq). DNA damage is minimized enabling longer insert sizes, lower duplication rates and minimal GC bias resulting in more accurate quantification of methylation in the sample DNA. Using EM-Seq, we profiled cfDNA and FFPE DNA from multiple tissue types. Results for these challenging DNA types showed that the EM-Seq libraries had longer inserts, lower duplication rates, higher percentages of mapped reads and less GC bias compared to WGBS libraries. These libraries also identified a higher number of CpG’s and the estimated global methylation levels were in good agreement with the absolute levels quantified using LC/MS. In conclusion, EM-Seq libraries have superior sequencing metrics resulting in robust methylation profiling for these types of challenging DNA samples. Citation Format: Louise Williams, V K Chaithanya Ponnaluri, Brittany S. Sexton, Lana Saleh, Katherine Marks, Mala Samaranayake, Laurence Ettwiller, Shengxi Guan, Heidi E. Church, Nan Dai, Esta Tamanaha, Erbay Yigit, Bradley Langhorst, Zhiyi Sun, Thomas C. Evans, Romualdas Vaisvila, Eileen Dimalanta, Theodore B. Davis. Enzymatic Methyl-Seq: methylome analysis of challenging DNA samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 820.