Biology subjects

Leins, J.

Publications and source records attributed to Leins, J..

2 recordsLinked to original sources

bioRxiv2025

Extended poly(A) tails are a shared feature of herpesvirus mRNAs

Poly(A) tails are present on most cellular and viral mRNAs, providing a platform for poly(A)-binding proteins that stimulate translation and regulate the deadenylation and stability of transcripts in the cytoplasm. Here we leverage nanopore direct RNA sequencing to analyse the distribution of poly(A) tail lengths on cellular and viral mRNAs across Herpesviridae and other DNA and RNA virus infections. We find that herpesvirus mRNA poly(A) tails are consistently longer than those on cellular and other viral transcripts, presenting a previously unrecognized yet widespread mechanism to advantage herpesviral gene expression. This contrasts with the templated poly(A) tails on coronavirus RNAs and those on cytoplasmically transcribed poxviral mRNAs, which are more similar in length to those on host mRNAs. Herpesviral noncoding RNAs display differential poly(A) tailing patterns which do not correlate with nuclear localisation while individual herpesviral mRNAs also show variation in the extent to which their poly(A) tail lengths change during the virus lifecycle, suggestive of additional uncharacterised layers of poly(A) tail length regulation. Importantly, while we detect non-adenosine nucleotides within herpesviral poly(A) tails, which are known to oppose deadenylase activity, this "mixed tailing" is not at sufficient frequency to explain the widespread extended tails of herpesvirus mRNAs.

microbiology↗

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↗