Project description:Long-read RNA sequencing technologies offer unparalleled in- sights into transcriptomes by enabling full-length sequencing of RNA molecules, uncovering novel isoforms and alternative splicing events. While long-read sequencing platforms, such as Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), have historically been associated with higher error rates, recent advancements in both platforms have significantly en- hanced read accuracy, broadening their applicability for tran- scriptomic studies. With the rapid evolution of sequencing protocols and bioin- formatics tools, the trade-offs between sequencing throughput, read length, accuracy, and cost present significant challenges in selecting the optimal approach. Systematic benchmarking studies that compare these options are crucial to inform fu- ture research directions. However, many existing benchmark- ing datasets with matched data across multiple platforms have limitations, including: 1) a lack of realistic biological replicates, which may restrict the generalisability of differential analysis results to real-world scenarios, and 2) the use of earlier sequenc- ing kits, which may not reflect the latest advancements in se- quencing technology, limiting their relevance for future studies that typically use newer sequencing protocols. Here we present LongBench, a comprehensive benchmarking dataset designed to fill these critical gaps. Derived from eight lung cancer cell lines with synthetic RNA spike-ins, LongBench includes bulk, single-cell, and single-nucleus RNA-seq data from three state-of-the-art long-read sequencing platforms — ONT PCR-cDNA, ONT direct RNA, PacBio Kinnex — alongside Il- lumina short-read data for robust cross-platform comparisons. The LongBench dataset is a valuable resource for benchmarking and improving sequencing protocols and bioinformatics tools. With the LongBench dataset we present a systematic evaluation of transcript capture, quantification, and differential expression analyses, examining the strengths and limitations of each se- quencing platform in various biological contexts, enabling re- searchers to make more informed decisions on platform and method selection.
Project description:The Long-read POG dataset comprises a cohort of 189 patient tumours and 41 matched normal samples sequenced using the Oxford Nanopore Technologies PromethION platform. This dataset from the Personalized Oncogenomics (POG) program and the Marathon of Hope Cancer Centres Network includes accompanying DNA and RNA short-read sequence data, analytics, and clinical information. We show the potential of long-read sequencing for resolving complex cancer-related structural variants, viral integrations, and extrachromosomal circular DNA. Long-range phasing of variants facilitates the discovery of allelically differentially methylated regions (aDMRs) and allele-specific expression, including recurrent aDMRs in the cancer genes RET and CDKN2A. Germline promoter methylation in MLH1 can be directly observed in Lynch syndrome. Promoter methylation in BRCA1 and RAD51C is a likely driver behind patterns of homologous recombination deficiency where no driver mutation was found. This dataset demonstrates applications for long-read sequencing in precision medicine, and is available as a resource for developing analytical approaches using this technology.