Biology subjects

Woodward, K.

Publications and source records attributed to Woodward, K..

3 recordsLinked to original sources

bioRxiv2026

dirCLIP profiles variant-specific RNA-protein interactions via nanopore long-read sequencing

RNA binding proteins (RBPs) control gene expression through their activities in essentially all processing steps of coding and noncoding RNAs and are dysregulated in disease. With >95% of human multi-exon genes undergoing alternative splicing, the inability to assign RBP sites to distinct RNA variants fundamentally limits our understanding of RNA regulation. We present dirCLIP, a method combining UV crosslinking and immunoprecipitation (CLIP) with amplification-free direct nanopore long-read sequencing preserving full-length transcripts. dirCLIP employs two complementary strategies: direct RNA sequencing detecting amino acid adduct-induced perturbations in current signals and direct cDNA sequencing capturing binding sites as mutations. Benchmarking dirCLIP with SRSF3 demonstrated >75% concordance with short-read-based data, revealed isoform-selective RNA binding and enabled detection of co-occurring binding sites in single RNA molecules. Application to the noncanonical RBP HMGA1 uncovered new AT-hook mediated RNA variant-specific interactions. dirCLIP fundamentally transforms our ability to interrogate RNA regulation of distinct isoforms and transcript variants with direct implications to disease mechanisms and development of RNA therapeutics.

molecular biology↗

bioRxiv2024

High-Accuracy RNA Integrity Definition for Unbiased Transcriptome Comparisons with INDEGRA

RNA sample integrity variability introduces biases and obscures natural RNA degradation, posing a significant challenge in transcriptomics. To address this, we developed the Direct Transcriptome Integrity (DTI) measure, a universal and robust RNA integrity metric based on nanopore sequencing. By accurately modeling RNA fragmentation, DTI provides a reliable assessment of sample quality. Integrated into the INDEGRA package (freely available at https://github.com/Arnaroo/INDEGRA), we provide tools to correct false discoveries and enable precise differential expression and RNA degradation analyses, even for challenging sample types. INDEGRA software can be used to accurately measure RNA DTI stability metric, isolate biological component of RNA degradation from technical biases, compare biological RNA stability transcriptome-wide and suppress false degradation-induced differential gene expression hits to allow broad comparisons across samples of different quality DTI offers a straightforward and accurate method for assessing RNA degradation, characterizing both overall sample integrity and transcript-specific degradation rates using direct RNA sequencing (DRS) data. Calculated through INDEGRA, DTI reveals inter- and intra-transcript variability in degradation, while INDEGRA separates RNA degradation from mapping inaccuracies, and connects degradation profiles to RNA fragmentation rates. By leveraging INDEGRA, researchers can minimize false differential transcript abundance findings caused by variations in overall sample integrity, while preserving genuine transcript-specific differences in stability and degradation. INDEGRA supports integration with widely used differential transcript abundance tools like DESeq2, limma-voom, and edgeR, enabling seamless analysis pipelines. INDEGRA enhances the accuracy and reliability of RNA quantification in high-throughput data and simplifies comparisons across diverse transcriptomic datasets, including those derived from different tissues, species, or experimental protocols.

bioinformatics↗

bioRxiv2022

Identification of m6A and m5C RNA modifications at single-molecule resolution from Nanopore sequencing

The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUIs capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.

bioinformatics↗