Detecting DNA cytosine methylation using nanopore sequencing

Simpson, Jared T.; Workman, Rachael E.; Zuzarte, Philip C.; David, Matei; Dursi, L. J.; Timp, Winston

doi:10.1038/nmeth.4184

Cited by 884 publications

(1,026 citation statements)

References 28 publications

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“…Base-calling can also be performed a posteriori with Albacore on a personal computer, a high performance computing server, or ONT's cloud-based analysis service known as Metrichor (https://metrichor.com). A third option is to use one of the multiple open-source base-calling algorithms, which use various machine-or deep-learning algorithms, including hidden Markov models Simpson et al 2017) and recurrent neural networks (Boža et al 2017;Stoiber and Brown 2017). 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.…”

Section: Future Approaches: Direct Rna Sequencingmentioning

confidence: 99%

The RNA modification landscape in human disease

Jonkhout

Tran

Smith

et al. 2017

RNA

470

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

470

420

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“…With continued technical development, they may be employed to aging research making direct analysis of DNA modification patterns from un-manipulated DNA possible. An exciting possibility of this single-molecule approach would be that individual cells could potentially be interrogated, without the need for extensive amplification (and the issues this can cause) but this still requires additional method development (Simpson et al 2017). …”

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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“…Cette méthode a permis récemment de réaliser le séquençage, directement sur site, d'espèces de bactéries sauvages [20,21], de détecter et d'identifier des virus in situ (virus de la dengue [22], parvovirus [23], virus Ebola [24]). Elle a été utilisée pour la détection d'éléments transposables [25], de méthylation de l'ADN [26], et de mutations précoces liées à la maladie d'Alzheimer [27]. Grâce à des algorithmes fondés sur le maximum de vraisemblance, elle a aussi révélé des isoformes de récepteurs dans des lymphocytes B [28].…”

Section: Séquençage De L'adn Par Nanopores Résultats Et Perspectivesunclassified

Séquençage de l’ADN par nanopores

Montel

2018

Med Sci (Paris)

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Après des années de développement, l’utilisation du nanopore comme sonde pour séquencer les molécules d’ADN est maintenant une possibilité viable et prometteuse. La détection d’une seule paire de bases lors du transport de l’ADN permet d’enregistrer de très longs fragments de polynucléotides, avec une parallélisation et des vitesses élevées. Dans cette revue, les méthodologies actuelles fondées sur la détection électrique et les nanopores biologiques seront présentées de même que les nouvelles méthodes utilisant des nanopores à l’état solide, ou la détection optique.

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Detecting DNA cytosine methylation using nanopore sequencing

Cited by 884 publications

References 28 publications

The RNA modification landscape in human disease

The RNA modification landscape in human disease

Analysis of DNA modifications in aging research

Séquençage de l’ADN par nanopores

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