Project description:Long-read nanopore sequencing has emerged as a potent tool for studying RNA modifications. However, the detection of N4-acetylcytidine (ac4C) based on nanopore sequencing remains largely unexplored. Here, we introduce ac4Cnet, a deep learning frame utilizing Oxford Nanopore direct RNA sequencing to accurately identify ac4C sites. Our methodology involves training ac4Cnet capable of distinguishing ac4C from unmodified cytidine and 5-methylcytosine (m5C), as well as estimating the modification rate at each ac4C site. We demonstrate the robustness of our approach through validations on independent in vitro datasets and a human cell line, highlighting its versatility and potential for advancing the study of ac4C modifications.
Project description:Transfer RNAs are the fundamental adapter molecules of protein synthesis and the most abundant and heterogeneous class of noncoding RNA molecules in cells. The study of tRNA repertoires remains challenging, complicated by the presence of dozens of post transcriptional modifications. Nanopore sequencing is an emerging technology with promise for both tRNA sequencing and the detection of RNA modifications; however, such studies have been limited by the throughput and accuracy of direct RNA sequencing methods. Moreover, detection of the complete set of tRNA modifications by nanopore sequencing remains challenging. Here we show that recent updates to nanopore direct RNA sequencing chemistry (RNA004) combined with our own optimizations to tRNA sequencing protocols and analysis workflows enable high throughput coverage of tRNA molecules and characterization of nanopore signals produced by 43 distinct RNA modifications. We share best practices and protocols for nanopore sequencing of tRNA and further report successful detection of low abundance mitochondrial and viral tRNAs, providing proof of concept for use of nanopore sequencing to study tRNA populations in the context of infection and organelle biology. This work provides a roadmap to guide future efforts towards de novo detection of RNA modifications across multiple organisms using nanopore sequencing.
Project description:We applied direct RNA long read sequencing for characterization of transcripts from constructs inserted into HEK293T mammalian cells with different promoters. Direct RNA sequencing was performed on an Oxford Nanopore GridION device using the Direct Sequencing Kit (SQK-RNA004, date accessed 15 May 2024), MinION RNA flow cell (FLO-MIN00RA), and data pre-processing was performed with MinKNOW (v24.06.10).
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:We cultured MCF10a-Snail-ER cells and induced EMT initiation with tamoxifen. A matched sequencing of their PolyA RNA was performed, using Illumina and direct RNA Oxford Nanopore sequencing technologies. Both generated datasets supported the development of hybrid bioinformatics tools.