Abstract

Abstract DNA methylation is an epigenetic regulator of gene expression with important functions in development and diseases such as cancer. Traditionally, sodium bisulfite conversion was used to distinguish 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) from cytosines. However, this method damages DNA and introduces significant sequencing bias. NEBNext® Enzymatic Methyl-seq (EM-seq™) is an enzymatic conversion approach that minimizes DNA damage therefore enabling longer insert sizes, lower duplication rates and a more accurate quantification of methylation in DNA samples with inputs ranging from 10 ng to 200 ng. An improved enzymatic conversion method, EM-seq v2, has a more streamlined workflow and an expanded DNA input range of 100 pg to 200 ng. Libraries made using NA12878 genomic DNA show improved yields, consistent global methylation and an even GC bias representation. The increased library yields subsequently reduces sequencing duplications and costs. Sequencing costs are an important consideration when performing whole genome methylome analysis as this often needs high sequencing depth to attain meaningful coverage to accurately call methylation. Reduced representation libraries, a commonly used method to investigate DNA methylation, relies on enrichment of CpGs within libraries digested using MspI. These CpGs are commonly found in regulatory regions. Although lacking comprehensive CpG coverage, for many researchers this method provides enough cost effective CpG methylation coverage for their studies. Reduced Representation EM-seq libraries (RREM-seq) and Reduced Representation Bisulfite libraries (RRBS) were made using 200 ng to 100 pg of NA12878 DNA. EM-seq adaptors were ligated to MspI digested DNA followed by conversion using either EM-seq v2 or sodium bisulfite. Libraries were PCR amplified and sequenced on an Illumina NovaSeq platform. RREM-seq resulted in higher yields and reproducible results regardless of input amounts compared to RRBS libraries. RREM-seq libraries also identified a higher number of CpGs with even coverage facilitating accurate methylation calling. RREM-seq libraries have superior sequencing metrics resulting in robust methylation profiling. Focusing on a subset of the genome generates higher coverage DNA methylation data at a lower DNA sequencing cost. Citation Format: Vaishnavi Panchapakesa, Chaithanya Ponnaluri, Daniel Evanich, Ariel Erijman, Bradley Langhorst, Louise Williams. Whole genome and reduced representation enzymatic methyl-seq enable cost effective methylomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7022.

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