WEHI Wednesday Seminar hosted by Professor Marnie Blewitt

Professor Matt Ritchie

Division Head – Genetics and Gene Regulation division, WEHI

Comparative benchmarking of high-resolution spatial and long-read transcriptomic platforms with LongBench and SpatialBench

Davis Auditorium

Join via SLIDO enter code #WEHIWednesday

Including Q&A session

Long-read and spatial transcriptomic platforms have rapidly developed in recent years, yet rigorous cross-platform benchmarking remains limited in scope and biological grounding. I will present our recent collaborative efforts to create systematic data resources for evaluating these emerging technologies using well characterized reference samples with in-built ground truth.

LongBench is a multi-platform reference dataset spanning bulk, single-cell, and single-nucleus transcriptomics across eight human lung cancer cell lines with synthetic spike-in controls. It incorporates three state-of-the-art long-read protocols (Oxford Nanopore Technologies (ONT) PCR-cDNA, ONT direct RNA, and PacBio Kinnex) alongside Illumina short reads to allow systematic evaluation of transcript capture, quantification accuracy, differential expression, isoform usage, variant detection, and allele-specific analyses. Our results show high concordance in gene-level differential analyses across protocols, but reduced consistency for transcript-level and isoform analyses due to length and platform-dependent biases. Single-cell long-read data are highly concordant with bulk for high-confidence features, though single-nuclei data show reduced feature detection.

SpatialBench is a matched multi-platform data resource comprising Visium HD, Xenium and MERSCOPE data with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 (T-bet) knockout mouse spleen model. Loss of T-bet in B cells disrupts germinal centre (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. Across platforms, immune organization and Tbx21-associated programs were consistently recovered, indicating robustness of major biological signals. Platforms differed in biological resolution: Visium HD enabled transcriptome-scale GC characterization and, with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity.

Together, these resources provide a biologically defined framework for evaluating long-read and spatial technologies to guide method development and platform selection.

Professor Matt Ritchie is a bioinformatician who analyses high-throughput transcriptomic and methylation data and develops statistical methods implemented in open-source R/Bioconductor software. Through close collaboration with molecular biologists and clinician scientists, his work has revealed new insights into epigenetic processes, haematopoiesis, apoptosis, and mechanisms of treatment resistance in cancer.

All welcome!