Project description:5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are modified versions of cytosine in DNA with roles in regulating gene expression. Using whole genomic DNA from mouse cerebellum, we have benchmarked 5mC and 5hmC detection by Oxford Nanopore Technologies sequencing against other standard techniques. In addition, we assessed the ability of duplex base-calling to study strand asymmetric modification. Nanopore detection of 5mC and 5hmC is accurate relative to compared techniques and opens new means of studying these modifications. Strand asymmetric modification is widespread across the genome but reduced at imprinting control regions and CTCF binding sites in mouse cerebellum. This study demonstrates the unique ability of nanopore sequencing to improve the resolution and detail of cytosine modification mapping.
Project description:The field of epitranscriptomics has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here we show that using Oxford Nanopore Technologies, N6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Our results open new avenues to investigate the universe of RNA modifications with single nucleotide resolution, in individual RNA molecules.
Project description:Sequencing was performed to assess the ability of Nanopore direct cDNA and native RNA sequencing to characterise human transcriptomes. Total RNA was extracted from either HAP1 or HEK293 cells, and the polyA+ fraction isolated using oligodT dynabeads. Libraries were prepared using Oxford Nanopore Technologies (ONT) kits according to manufacturers instructions. Samples were then sequenced on ONT R9.4 flow cells to generate fast5 raw reads in the ONT MinKNOW software. Fast5 reads were then base-called using the ONT Albacore software to generate Fastq reads.
Project description:N6-methyladenosine (m6A) has been one of the most abundant and well-known modifications in mRNA since its discovery in 1970s. Recent studies have demonstrated that m6A gets involved in various biological processes such as alternative splicing and RNA degradation, playing an important role in all kinds of diseases. To better understand the role of m6A, transcriptome-wide m6A profiling data is indispensable. In these years, the Oxford Nanopore Technology Direct RNA Sequencing (DRS) platform has shown promise in RNA modification detection based on current disruptions measured in transcripts. However, decoding current intensity data into modification profiles remains a challenging task. Here, we introduce m6A Transcriptome-wide Mapper (m6ATM), a novel Python-based computational pipeline that applies deep neural networks to predict m6A sites at single-base resolution using DRS data. The m6ATM model architecture incorporates a WaveNet encoder and a dual-stream multiple instance learning model to extract features from specific target sites and characterize the m6A epitranscriptome. For validation, m6ATM achieved an accuracy of 80 to 98% across in-vitro transcription datasets containing varying m6A modification ratios and outperformed other tools in benchmarking with human cell-line data. Moreover, we demonstrated the versatility of m6ATM in providing reliable stoichiometric information and used it to pinpoint PEG10 as a potential m6A target transcript in liver cancer cells. In conclusion, we showed that m6ATM is a high-performance m6A detection tool and our results paved the way for epitranscriptomic precision medicine.
Project description:N6-methyladenosine (m6A) has been one of the most abundant and well-known modifications in mRNA since its discovery in 1970s. Recent studies have demonstrated that m6A gets involved in various biological processes such as alternative splicing and RNA degradation, playing an important role in all kinds of diseases. To better understand the role of m6A, transcriptome-wide m6A profiling data is indispensable. In these years, the Oxford Nanopore Technology Direct RNA Sequencing (DRS) platform has shown promise in RNA modification detection based on current disruptions measured in transcripts. However, decoding current intensity data into modification profiles remains a challenging task. Here, we introduce m6A Transcriptome-wide Mapper (m6ATM), a novel Python-based computational pipeline that applies deep neural networks to predict m6A sites at single-base resolution using DRS data. The m6ATM model architecture incorporates a WaveNet encoder and a dual-stream multiple instance learning model to extract features from specific target sites and characterize the m6A epitranscriptome. For validation, m6ATM achieved an accuracy of 80 to 98% across in-vitro transcription datasets containing varying m6A modification ratios and outperformed other tools in benchmarking with human cell-line data. Moreover, we demonstrated the versatility of m6ATM in providing reliable stoichiometric information and used it to pinpoint PEG10 as a potential m6A target transcript in liver cancer cells. In conclusion, we showed that m6ATM is a high-performance m6A detection tool and our results paved the way for epitranscriptomic precision medicine.
Project description:Whole-genome bisulfite sequencing (WGBS) is currently the gold standard for DNA methylation (5-methylcytosine, 5mC) profiling, however the destructive nature of sodium bisulfite results in DNA fragmentation and subsequent biases in sequencing data. Such issues have led to the development of bisulfite-free methods for 5mC detection. Nanopore sequencing is a long read non-destructive approach that directly analyzes DNA and RNA fragments in real time. Recently, computational tools have been developed that enable base-resolution detection of 5mC from Oxford Nanopore sequencing data. In this chapter we provide a detailed protocol for preparation, sequencing, read assembly and analysis of genome-wide 5mC using Nanopore sequencing technologies.
Project description:We present scNanoATAC-seq (Single-cell Assay for Transposase Accessible Chromatin by Oxford Nanopore Technologies Sequencing), an effective method for simultaneous detection of chromatin accessibility and genetic variation. Long fragments (about 4-5Kb) of single-cell ATAC-seq library were enriched and sequenced by Oxford Nanopore Technologies platform. Ends of long ATAC-seq fragments are regarded as chromatin accessibility signal in downstream analysis.