Mapping DNA methylation with high-throughput nanopore sequencing

Rand, Arthur C; Jain, Miten; Eizenga, Jordan M.; Musselman-Brown, Audrey; Olsen, Hugh E.; Akeson, Mark; Paten, Benedict

doi:10.1038/nmeth.4189

Cited by 432 publications

(369 citation statements)

References 24 publications

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“…Unfortunately, these algorithms are typically trained to predict exclusively four bases (A, C, G, T), and thus cannot directly identify DNA-or RNA-modified nucleotides. There have nonetheless been recent reports describing computational models capable of detecting modified DNA bases, by training models from biological control data and by observing conspicuous alterations of ionic current at specific positions (Stoiber et al 2016;McIntyre et al 2017;Rand et al 2017;Simpson et al 2017). With respect to DRS, these strategies have recently been applied to characterize the epitranscriptome, namely the identification of m 6 A (Garalde et al 2016) and conserved 16S ribosomal RNA base modifications and a 7-methylguanosine modification associated with antibiotic resistance .…”

Section: Future Approaches: Direct Rna Sequencingmentioning

confidence: 99%

The RNA modification landscape in human disease

Jonkhout

Tran

Smith

et al. 2017

RNA

490

420

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RNA modifications have been historically considered as fine-tuning chemo-structural features of infrastructural RNAs, such as rRNAs, tRNAs, and snoRNAs. This view has changed dramatically in recent years, to a large extent as a result of systematic efforts to map and quantify various RNA modifications in a transcriptome-wide manner, revealing that RNA modifications are reversible, dynamically regulated, far more widespread than originally thought, and involved in major biological processes, including cell differentiation, sex determination, and stress responses. Here we summarize the state of knowledge and provide a catalog of RNA modifications and their links to neurological disorders, cancers, and other diseases. With the advent of direct RNA-sequencing technologies, we expect that this catalog will help prioritize those RNA modifications for transcriptome-wide maps.

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Section: Future Approaches: Direct Rna Sequencingmentioning

confidence: 99%

The RNA modification landscape in human disease

Jonkhout

Tran

Smith

et al. 2017

RNA

490

420

View full text Add to dashboard Cite

show abstract

“…106 Novel high-throughput nanopore sequencing variants, as well as diversity in technological platforms and in required sequencing depth, have also stimulated contributions to the recent literature. 107,108 Increasingly, sophisticated bioinformatic methods are required for downstream analyses as researchers attempt to interpret multi-locus methylation information from multiple samples, for example, methods such as model-based clustering described by Houseman et al, 109 tailored for data obtained with methylation-specific microarrays. Multivariate statistical methods, particularly for both supervised and unsupervised clustering, principal component analysis, regression and visualization tools, such as heatmaps, have proved vital to interpretation of outcomes for these complex data, 110 which are generated by combinations of epigenetic changes and molecular events.…”

Section: Targeted Analysis Methods and Toolsmentioning

confidence: 99%

Recent advances in computational epigenetics

Ruskin¹,

Barat²

2017

AGG

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“…Nanopore sequencing uses pores through which nucleic acid strands are Bpulled^and the ionic pattern reveals the nucleotide sequence, including modifications (Jain et al 2017;Shendure et al 2017). These technologies are still in the developmental phase but show great promise (Rand et al 2017). With continued technical development, they may be employed to aging research making direct analysis of DNA modification patterns from un-manipulated DNA possible.…”

Section: Alternatives To Conversion-based Sequencingmentioning

confidence: 99%

Analysis of DNA modifications in aging research

et al. 2018

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As geroscience research extends into the role of epigenetics in aging and age-related disease, researchers are being confronted with unfamiliar molecular techniques and data analysis methods that can be difficult to integrate into their work. In this review, we focus on the analysis of DNA modifications, namely cytosine methylation and hydroxymethylation, through nextgeneration sequencing methods. While older techniques for modification analysis performed relative quantitation across regions of the genome or examined average genome levels, these analyses lack the desired specificity, rigor, and genomic coverage to firmly establish the nature of genomic methylation patterns and their response to aging. With recent methodological advances, such as whole genome bisulfite sequencing (WGBS), bisulfite oligonucleotide capture sequencing (BOCS), and bisulfite amplicon sequencing (BSAS), cytosine modifications can now be readily analyzed with base-specific, absolute quantitation at both cytosine-guanine dinucleotide (CG) and non-CG sites throughout the genome or within specific regions of interest by next-generation sequencing. Additional advances, such as oxidative bisulfite conversion to differentiate methylation from hydroxymethylation and analysis of limited input/single-cells, have great promise for continuing to expand epigenomic capabilities. This review provides a background on DNA modifications, the current state-of-theart for sequencing methods, bioinformatics tools for converting these large data sets into biological insights, and perspectives on future directions for the field.

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Mapping DNA methylation with high-throughput nanopore sequencing

Cited by 432 publications

References 24 publications

The RNA modification landscape in human disease

The RNA modification landscape in human disease

Recent advances in computational epigenetics

Analysis of DNA modifications in aging research

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