Epigenetics and methylation analysis
Epigenetics, the study of heritable phenotypic changes that do not involve alteration of the nucleotide sequence, plays a key role in gene expression and has been associated with many diseases, including cancer. As PCR removes base modifications, their detection via traditional sequencing technologies requires the use of special library preparation steps (e.g. bisulfite conversion) which damage nucleic acids, resulting in very short sequencing reads. With nanopore sequencing, PCR is not required, enabling DNA and RNA modifications to be preserved and directly sequenced — with no additional library prep steps. Long-range epigenetic changes, structural variants, and single nucleotide polymorphisms can be identified and phased in a single dataset.
- Detect base modifications alongside nucleotide sequence as standard
- Use whole genome or amplification-free targeted sequencing approaches
- Streamline your workflow — rapid 10-minute library prep and no bisulfite conversion required
Directly detect DNA and RNA methylation with high reproducibility and low bias
Using nanopore sequencing, researchers have directly identified DNA and RNA base modifications at single-nucleotide resolution, including 5mC, 5hmC, 6mA, and BrdU in DNA, and m6A in RNA, with detection of further natural or synthetic epigenetic modifications possible through training basecalling algorithms.
One of the most widespread genomic modifications is 5-methylcytosine (5mC), which most frequently occurs at CpG dinucleotides in the human genome. Benchmarking genome-wide nanopore 5mC detection against whole-genome, short-read bisulfite sequencing, the traditional method of 5mC detection, has shown nanopore sequencing to enable gold-standard 5mC calling (Figure 1). Nanopore technology calls a higher number of CpG positions in the human genome, requires less sequencing data, and shows more even genomic coverage; analysis runtime is also significantly shorter.
Benefits of nanopore technology over traditional bisulfite sequencing for methylation analysis:
- More even genomic coverage with lower GC bias
- Higher number of CpG positions called at lower read depth
- Simplified haplotype phasing of methylated bases using long reads
- Greater experimental reproducibility
- Considerably faster data analysis
Target important genomic regions without PCR for cost-effective characterisation of methylation patterns
Reduced-representation bisulfite sequencing (RRBS) is frequently used to perform methylation analysis without the need for whole-genome sequencing; however, the method is expensive and time consuming. Reduced-Representation Methylation Sequencing (RRMS) with Oxford Nanopore enables cost-effective, genome-wide characterisation of methylation patterns across regions of interest. RRMS utilises adaptive sampling: a real-time, flexible, and precise method to enrich for regions of interest by depleting off-target regions during a sequencing run, without requiring special library preparation steps.
With adaptive sampling, Oxford Nanopore offers a flexible, PCR-free method of targeted methylation detection — whether in a single target, a panel of genes, or across multiple, large regions of interest.
Into the unknown: the epigenetics of repetitive DNA
Long nanopore sequencing reads and direct epigenetic modification detection enable the characterisation of methylation in repeat-rich regions, making it possible to characterise the epigenetics of large repetitive arrays in the human genome — previously unexplored with traditional short-read sequencing. Find out how Gershman et al. used PCR-free nanopore sequencing to discover long-range, allele-specific DNA methylation patterns across higher order repeats at chromosome centromeres in the human genome.
MeOW: genome-wide identification of differentially methylated regions using Oxford Nanopore long-read sequencing data
With direct nanopore sequencing, it is possible to characterise differentially methylated regions (DMRs) that may contribute to disease or act as biomarkers. Discover how Miranda Galey and her team developed a method to identify DMRs in clinical research samples, showing potential utility to rapidly identify disease-causing variants missed by traditional technologies.
How do I prepare and sequence samples for methylation detection?
Amplification-free library preparation is required in order to maintain base modifications. For DNA sequencing, we recommend the Ligation Sequencing Kit. For RNA modification analysis, the Direct RNA Sequencing Kit is required. Nanopore sequencing is the only currently available technology that allows direct sequencing of native RNA, with no requirement for amplification or reverse transcription.
PromethION is suitable for high-throughput epigenetic studies of larger genomes, such as human and many plant genomes, whilst MinION and GridION devices are ideal for epigenetic analysis of microbial genomes or eukaryotic transcriptomes and targeted genomic regions.
How do I analyse base modifications?
For gold-standard 5mC methylation calling in the human genome, we recommend the algorithm Remora, which is integrated into MinKNOW — the software onboard nanopore sequencing devices. Remora models run alongside basecalling, and provide superior performance to that of existing modification calling tools. Remora models for the detection of both 5mC and 5hmC are available.
Available in EPI2ME, the pre-configured, end-to-end data analysis workflow wf-human-variation enables the analysis of SVs, SNVs, and methylation. EPI2ME workflows suit all levels of bioinformatics expertise and can be run from an intuitive graphical interface, or from the command line. For more advanced usage, such as if you wish to train your own models to detect further epigenetic modifications of interest, you can access the Remora repository on GitHub.
The Genome in a Bottle consortium’s Ashkenazi Trio samples were sequenced on two PromethION Flow Cells with the Ligation Sequencing Kit and analysed using the wf-human-variation workflow. Try out the analysis tools with this nanopore dataset, which can be found here.
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