DNA methylation researchers face a tough choice: expensive whole-genome bisulfite sequencing (WGBS), or limited insights from arrays, reduced representation bisulfite sequencing (RRBS), and targeted panels. Bisulfite conversion also damages DNA, resulting in potential biases that can complicate data analysis.
CUTANA™ meCUT&RUN solves this challenge by selectively enriching methylated DNA, delivering high-quality, genome-wide insights at a fraction of the sequencing required for WGBS.
Why Choose meCUT&RUN:
Many 5-methylcytosine mapping strategies, like whole-genome bisulfite sequencing (WGBS), require >800 M reads, intensive bioinformatics processing, and high overall costs, making them impractical for many research labs. However, targeted strategies also raise concerns. Reduced representation bisulfite sequencing (RRBS), microarrays, and hybridization panels only cover a small percentage of CpG sites and are often biased for CpG islands. Furthermore, the use of bisulfite conversion introduces potential bias and damages DNA, resulting in high input requirements.
Enter CUTANA™ meCUT&RUN: Genome-wide DNA methylation insights for a fraction of the cost!
Figure 1: The CUTANA™ meCUT&RUN workflow can be divided into 3 easy steps. In Step 1, a modified CUT&RUN workflow is performed to enrich methylated DNA. Only 10,000-500,000 cells per reaction is needed. In Step 2, methylated DNA is prepared for sequencing using a standard library prep strategy. For base-pair resolution DNA methylation sequencing (optional), prepare DNA using EM-seq. Step 3 is next-generation sequencing and data analysis. Note that for traditional library prep, only 15-20 M total reads are needed; for base-pair resolution using EM-seq (meCUT&RUN-EM), we recommend 30-50 M total reads.
We paired meCUT&RUN with Enzymatic Methyl-seq (EM-seq) to enable base-pair resolution comparisons with RRBS and Whole-Genome EM-seq (Figure 2). The results:
CUTANA™ meCUT&RUN generates DNA methylation profiles similar to whole genome EM-seq at greatly reduced sequencing depth, while also providing improved 5-methylcytosine coverage compared to RRBS.
Figure 2: meCUT&RUN was paired with EM-seq (meCUT&RUN-EM; 30 M reads) to thoroughly evaluate it’s performance against targeted bisulfite-conversion assays (RRBS; data from ENCODE, 57 M reads) and whole-genome, enzymatic-based approaches (EM-seq; 300 M reads) in K562 cells.
meCUT&RUN is a robust approach for capturing genome-wide DNA methylation, even at low sequencing depths. Figure 3 shows the number of methylated CpGs (5mCs) detected by meCUT&RUN at varying sequencing depths, normalized to the total number of 5mCs captured by Whole-Genome EM-seq.
At 20-30 M unique reads, meCUT&RUN detects 80% of methylated CpGs, providing improved coverage vs. other targeted approaches, while also reducing sequencing costs.
Figure 3: CUTANA™ meCUT&RUN recovers 80% of methylated CpGs (5mCs) compared to whole-genome EM-seq in K562 cells, with just 20-30 M unique reads. Here, meCUT&RUN was paired with EM-seq for base-pair resolution 5mC analysis (meCUT&RUN-EM). Data were downsampled to 3 to 50 M uniquely aligned reads. The number of methylated CpG positions was calculated for each downsampled dataset and normalized to the number of 5mC position detected by EM-seq.
If you need an efficient, cost-effective, and genome-wide method for DNA methylation analysis, meCUT&RUN is for you!
meCUT&RUN assays are useful for a variety of biomedical research areas, including:
💊 Drug and biomarker discovery teams
🧫 Studies with human cell lines and tissues
🐁 Mouse models of cancer, metabolic disease, and development
🧠 Neuroscience research
Figure 4: Representative genome browser tracks for meCUT&RUN experiments using decreasing amounts of lightly cross-linked K562 cells (0.1 % formaldehyde, 1 min). At 8,000 cells, data are largely indistinguishable from assays using 250,000 cells.
We have everything you need to get started with CUTANA™ meCUT&RUN assays!
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