Detecting DNA cytosine methylation using nanopore sequencing

By Jared T. Simpson, R. Workman, P. Zuzarte, Matei David, L. Jonathan Dursi, Winston Timp. Nature Methods, 2017

976 citations recorded by the source corpus.

In nanopore sequencing devices, electrolytic current signals are sensitive to base modifications, such as 5-methylcytosine (5-mC). Here we quantified the strength of this effect for the Oxford Nanopore Technologies MinION sequencer. By using synthetically methylated DNA, we were able to train a hidden Markov model to distinguish 5-mC from unmethylated cytosine. We applied our method to sequence the methylome of human DNA, without requiring special steps for library preparation.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/fee779b286b71cebc2caa2f8d8a6ba58ea11ccf3

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Citations in the corpus

Assembly of long, error-prone reads using repeat graphs (2018, methodology): “Although the Nanopolish tool contributed to a reduction in the base-calling errors of the ONT assemblies 25 , the resulting error rate The NG50 of an assembly is the largest possible number L , such that all contigs of length L or longer cover at least 50% of the genome.”
DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing (2023, neutral): “15 – 18).”
From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy (2018, background): “In addition, Nanopolish has recently obtained a new functionality that allows it to detect and call methylated bases [42].”
Readfish enables targeted nanopore sequencing of gigabase-sized genomes (2020, methodology): “SNPs in NA12878 read data were called using Nanopolish in methylation aware mode 26 .”
The Third Revolution in Sequencing Technology. (2018, background): “Recently, it was shown that nanopore sequencing can also detect 5mC and 6 mA [65,66].”
Piercing the dark matter: bioinformatics of long-range sequencing and mapping (2018, background): “The process of assembling sequences of DNa into a scaffold. a scaffold is similar to a contig but may contain gaps, typically represented as Ns in the sequence. as more detailed maps of DNA methylation in pathogens and human disease 21,22 .”
De novo Identification of DNA Modifications Enabled by Genome-Guided Nanopore Signal Processing (2017, methodology): “Most current nanopore base calling and methylation detection algorithms 12, 13, 16-18 utilize picoamp (pA) values produced by normalization of the raw 16-bit data acquisition (DAC) values.”
Nanopore sequencing technology, bioinformatics and applications (2021, methodology): “Compared to PacBio, ONT performs better in detecting 5mC but has lower accuracy in detecting 6mA 68,75,81 .”
Nanopore sequencing and assembly of a human genome with ultra-long reads (2017, positive): “Otherwise, training for signalAlign and nanopolish was carried out as previously described 35,36 .”
Deep learning in bioinformatics: introduction, application, and perspective in big data era (2019, background): “ng sequence variants [198, 166], model the transcription factor binding afﬁnity landscape [25, 3, 166], improve DNA sequencing [87, 154] and peptide sequencing [156], analyze DNA sequence modiﬁcation [143], and model various post-transcription regulation events, such as alternative polyadenylation [”
Long-read human genome sequencing and its applications (2020, neutral): “Several computational tools have been developed to detect DNA and RNA modifications on the basis of these characteristic disruptions: Nanopolish 85,86 , signalAlign 127 , DeepSignal 153 , 154 , DeepMod 155 and Tombo 156 .”
RNA modifications detection by comparative Nanopore direct RNA sequencing (2019, neutral): “qRT-PCR primers: 7sk (22-73): Fwd 5′-GCGACATCTGTCACCC CATT-3′; Rev 5′-CAGCCAGATCAGCCGAATCA-3′.”