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.
Introduction
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.
View the methylation benchmarking poster
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
Figure 1: Benchmarking of 5mC calling in DNA was performed with genomic data from two replicates of human genome HG002 at 20x depth of coverage (ONT_1, ONT_2) and 40x coverage (ONT_3). All samples were analysed using the Remora algorithm within the Guppy basecaller, phased with clair3, and aggregation was performed with modbam2bed. Nanopore methylation data was compared to publicly available bisulfite datasets. View the poster for further data analysis information.
Nanopore read depth is more uniform than the bisulfite data (Fig. 1b), maps completely to the genome (Fig. 1c) and requires far less analysis time than bisulfite data (Fig. 1d). The nanopore data showed a higher percentage of successfully called CpGs (>90%) at 20x overall read depth (Fig. 1e). Nanopore 5mC calls correlate well with bisulfite (0.94) and are highly reproducible (0.95) (Fig. 1f). Ultra-Long HG002 data was also generated using the Ultra-Long DNA Sequencing Kit, producing a N50 of 80 kb and a mapped coverage of 35x of the human genome, enabling phasing and haplotype-resolved methylation analysis across 90% of the called CpGs and >80% of the CpGs in the human genome (Fig. 1g).
Figure 2. RRMS combines adaptive sampling with methylation calling of native DNA using Remora. Comparison with RRBS showed RRMS retains a higher proportion of data than RRBS, gives a higher proportion of on-target reads, and more even coverage in paired tumour/normal cell line clinical research samples.
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 or Cas9 targeted sequencing, Oxford Nanopore offers scalable, flexible, PCR-free methods of targeted methylation detection - whether in a single target, a panel of genes, or across multiple, large regions of interest.
Case study
Detecting methylation in repetitive regions of the human genome
‘we are just scratching the surface about unveiling epigenetic control of these [repetitive] regions’
Ariel GershmanWith the limited capacity of traditional short-read sequencing technologies to access repeat-rich regions, such areas of the human genome have remained underexplored. Ariel Gershman and colleagues at Johns Hopkins University, USA, have been using long nanopore reads to reveal the methylome of previously unexplored large repetitive arrays in the human genome. Analysis of higher order repeats (HORs) at chromosome centromeres, which provide binding sites for the centromere-associated histone variant CENPA, uncovered distinctive patterns of hypomethylation and hypermethylation. Her team demonstrated for the first time how long nanopore reads could reveal long-range, allele-specific DNA methylation patterns across HORs and other classes of satellite repeats. These analyses have the potential to advance our understanding of the role of methylation in chromosome segregation and its association with genetic disorders.
Case study
Chromosome-scale haplotyping and methylation analysis for parent-of-origin assignment
Vahid Akbari (BC Cancer – Genome Sciences Centre, Canada) presented his work at the NCM 2022 demonstrating chromosome-scale phasing and parent-of-origin detection without the need for parental sequencing information using long Nanopore sequencing reads and methylation calling. He predicted that in the future this method has the potential to be used to improve genealogy and diagnosis and management of genetic diseases where the phenotype is affected by the parental origin of the allele.
Sequencing workflow
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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Genome-wide detection of methylation in humans
For whole-genome detection of modified bases in humans, we recommend the following:
Analysing microbial base modifications or performing amplification-free target enrichment? Find out more about our MinION and GridION devices.
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