- Author
- Anneleen Decock (UGent) , Olivier De Wever (UGent) , Celine Everaert (UGent) , Hetty Helsmoortel (UGent) , An Hendrix (UGent) , Pieter Mestdagh (UGent) , Annelien Morlion (UGent) , Jo Vandesompele (UGent) , Ruben Van Paemel (UGent) , Francisco Avila Cobos (UGent) , Jasper Verwilt, Jasper Anckaert (UGent) , Jilke De Wilde (UGent) , Carolina Fierro, Philippe Decruyenaere (UGent) , Jill Deleu (UGent) , Bert Dhondt, Eva Hulstaert, Nele Nijs (UGent) , Justine Nuytens (UGent) , Annouck Philippron, Kathleen Schoofs (UGent) , Eveline Vanden Eynde (UGent) , Kimberly Verniers (UGent) , Nurten Yigit (UGent) , Thibaut D'huyvetter, Thomas Piofczyk, Olivier Thas (UGent) , Scott Kuersten, Tim R. Mercer, Gary P. Schroth, Katleen De Preter (UGent) and Tom Van Maerken (UGent)
- Organization
- Project
- Abstract
- Using blood-based extracellular RNA (circulating cell-free RNA; exRNA) as a clinical biomarker requires a validated procedure for sample collection and processing, and RNA quantification. So far, no study has systematically tested pre-analytical variables affecting transcriptome-wide analysis of exRNAs. We evaluate and compare ten blood collection tubes, three time intervals between blood draw and blood processing, and eight RNA purification methods using the supplier-specified minimal and maximal biofluid input volumes. The impact on deep transcriptome profiling of both small and messenger RNA from blood plasma or serum was separately assessed for each pre-analytical variable and for interactions among a selected pre-analytical variable set, resulting in 456 complete extracellular transcriptomes. The processing and analysis workflow was controlled using 189 synthetic spike-in RNA molecules. In blood collection tube comparisons, manufacturer-designated ‘preservation tubes’ did not stabilize exRNA well, resulting in variable RNA concentration and number of detected genes over time, together with increased replicate variability. We also document large differences in RNA purification method performance in terms of number of detected genes, replicate variability and observed transcriptome complexity, and demonstrate technical interactions between specific blood collection tubes, purification methods, and time intervals. Our results are comprehensively summarized in 11 analytical performance metrics that enable an informed selection of the best sample processing workflow for a given experiment. We provide robust quality control metrics for exRNA quantification methods with validated standard operating procedures (SOPs), and put forward recommendations for both users and manufacturers of RNA purification methods and blood collection tubes, all together essential groundwork for future exRNA-based precision medicine applications.
- License
- LicenseNotListed
- Other license
- https://ega-archive.org/datasets/EGAD00001009724
- Access
- restricted access
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HQQJFZSNTW6BKBSQ7HAH806M
@misc{01HQQJFZSNTW6BKBSQ7HAH806M,
abstract = {{Using blood-based extracellular RNA (circulating cell-free RNA; exRNA) as a clinical biomarker requires a validated procedure for sample collection and processing, and RNA quantification. So far, no study has systematically tested pre-analytical variables affecting transcriptome-wide analysis of exRNAs. We evaluate and compare ten blood collection tubes, three time intervals between blood draw and blood processing, and eight RNA purification methods using the supplier-specified minimal and maximal biofluid input volumes. The impact on deep transcriptome profiling of both small and messenger RNA from blood plasma or serum was separately assessed for each pre-analytical variable and for interactions among a selected pre-analytical variable set, resulting in 456 complete extracellular transcriptomes. The processing and analysis workflow was controlled using 189 synthetic spike-in RNA molecules. In blood collection tube comparisons, manufacturer-designated ‘preservation tubes’ did not stabilize exRNA well, resulting in variable RNA concentration and number of detected genes over time, together with increased replicate variability. We also document large differences in RNA purification method performance in terms of number of detected genes, replicate variability and observed transcriptome complexity, and demonstrate technical interactions between specific blood collection tubes, purification methods, and time intervals. Our results are comprehensively summarized in 11 analytical performance metrics that enable an informed selection of the best sample processing workflow for a given experiment. We provide robust quality control metrics for exRNA quantification methods with validated standard operating procedures (SOPs), and put forward recommendations for both users and manufacturers of RNA purification methods and blood collection tubes, all together essential groundwork for future exRNA-based precision medicine applications.}},
author = {{Decock, Anneleen and De Wever, Olivier and Everaert, Celine and Helsmoortel, Hetty and Hendrix, An and Mestdagh, Pieter and Morlion, Annelien and Vandesompele, Jo and Van Paemel, Ruben and Avila Cobos, Francisco and Verwilt, Jasper and Anckaert, Jasper and De Wilde, Jilke and Fierro, Carolina and Decruyenaere, Philippe and Deleu, Jill and Dhondt, Bert and Hulstaert, Eva and Nijs, Nele and Nuytens, Justine and Philippron, Annouck and Schoofs, Kathleen and Vanden Eynde, Eveline and Verniers, Kimberly and Yigit, Nurten and D'huyvetter, Thibaut and Piofczyk, Thomas and Thas, Olivier and Kuersten, Scott and Mercer, Tim R. and Schroth, Gary P. and De Preter, Katleen and Van Maerken, Tom}},
publisher = {{European Genome-Phenome Archive}},
title = {{The Extracellular RNA Quality Control (exRNAQC) study (phase 2)}},
year = {{2022}},
}