Alwie, Y. | bioRxiv Science

bioRxiv2025

Defining expansions and perturbations to the RNA polymerase III transcriptome and epitranscriptome by modified direct RNA nanopore sequencing

RNA polymerase III (Pol III) transcribes cytosolic transfer RNAs (tRNAs) and other non-coding RNAs (ncRNAs) essential to cellular function. However, many aspects of Pol III transcription and processing, including RNA modifications, remain poorly understood, mainly due to a lack of available sensitive and systematic methods for their analysis. Here, we present DRAP3R (Direct Read and Analysis of Polymerase III transcribed RNAs), a modified nanopore direct RNA sequencing approach and analysis framework that enables the specific and sensitive capture of nascent Pol III transcribed RNAs. Applying DRAP3R to distinct cell types, we identify previously unconfirmed tRNA genes and other novel Pol III transcribed RNAs, thus expanding the known Pol III transcriptome. Critically, DRAP3R also enables discrimination between co- and post-transcriptional RNA modifications such as pseudouridine ({Psi}) and N6-methyladenosine (m6A) at single-nucleotide resolution across all examined transcript types and reveals differential {Psi} installation patterns across tRNA isodecoders and other ncRNAs. Finally, applying DRAP3R to epithelial cells infected with Herpes Simplex Virus Type 1 reveals an extensive remodelling of both the Pol III transcriptome and epitranscriptome. Our findings thus establish DRAP3R as a powerful tool for systematically studying Pol III transcribed RNAs and their modifications in diverse cellular contexts.

systems biology↗

bioRxiv2024

Nanopore Guided Annotation of Transcriptome Architectures

High-resolution annotations of transcriptomes from all domains of life are essential for many sequencing-based RNA analyses, including Nanopore direct RNA sequencing (DRS), which would otherwise be hindered by misalignments and other analysis artefacts. DRS allows the capture and full-length sequencing of native RNAs, without recoding or amplification bias, and resulting data may be interrogated to define the identity and location of chemically modified ribonucleotides, as well as the length of poly(A) tails on individual RNA molecules. Existing software solutions for generating high-resolution transcriptome annotations are poorly suited to small gene dense organisms such as viruses due to the challenge of identifying distinct transcript isoforms where alternative splicing and overlapping RNAs are prevalent. To resolve this, we identified key characteristics of DRS datasets and developed a novel approach to transcriptome. We demonstrate, using a combination of synthetic and original datasets, that our novel approach yields a high level of precision and recall when reconstructing both gene sparse and gene dense transcriptomes from DRS datasets. We further apply this approach to generate a new high resolution transcriptome annotation of the neglected pathogen human adenovirus type F 41 for which we identify 77 distinct transcripts encoding at least 23 different proteins.

bioinformatics↗