Systematic cross-study assessment of RNA-Seq experimental workflows for plasma cell-free transcriptome profiling

Tuni, C.; Asole, G.; Monteagudo-Mesas, P.; Rusu, E. C.; Cabus, L.; Gonzalez, L.; Sanchez, L.; Neto, B.; Sanders, P.; Weber, M.; Lagarde, J.

doi:10.1101/2025.07.10.664092

bioRxiv · 10.1101/2025.07.10.664092

Systematic cross-study assessment of RNA-Seq experimental workflows for plasma cell-free transcriptome profiling

Tuni, C.·Asole, G.·Monteagudo-Mesas, P.·Rusu, E. C.·Cabus, L.·Gonzalez, L.·Sanchez, L.·Neto, B.·Sanders, P.·Weber, M.·Lagarde, J.

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Abstract

Plasma cell-free RNA (cfRNA) is a promising source of non-invasive biomarkers, but its clinical translation is hindered by technical challenges and a lack of protocol standardization, which compromises reproducibility and comparability across studies. There is a need for a systematic evaluation of existing cfRNA-Seq workflows to understand the drivers of technical variability. Here, we address this gap by performing a comprehensive cross-study analysis of 2,166 cfRNA-Seq samples from 15 published studies and an in-house generated dataset, applying a uniform bioinformatics pipeline to enable a controlled comparison of experimental workflows. Our analysis reveals that the donor phenotype typically explains a negligible fraction of the transcriptomic variation, whose main determinants are technical - principally protocol choice, genomic DNA contamination levels and library diversity. Remarkably, this technical noise is so profound that variation within plasma cfRNA samples exceeds that found across a wide range of human tissues. Finally, we demonstrate that critical pre-analytical factors are often confounded with patient phenotypes, jeopardizing the validity of biomarker discovery efforts. Our work serves as a comprehensive benchmark of current cfRNA-Seq methodologies and provides evidence-based guidelines to improve experimental design. By highlighting the dominance of controllable technical factors, we offer a path towards more robust and reproducible cfRNA research.

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Tuni, C., Asole, G., Monteagudo-Mesas, P., Rusu, E. C., Cabus, L., Gonzalez, L., Sanchez, L., Neto, B., Sanders, P., Weber, M., Lagarde, J.. 2025-07-14. Systematic cross-study assessment of RNA-Seq experimental workflows for plasma cell-free transcriptome profiling. https://doi.org/10.1101/2025.07.10.664092

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