Gene expression differences between PAXgene and Tempus blood RNA tubes are highly reproducible between independent samples and biobanks.
BACKGROUND
Gene expression profiling from blood is sensitive to technology choices. For example, the main blood RNA collection systems-the PAXgene and Tempus tubes-differently influence RNA expression signatures. The aim of this study was to establish a common RNA isolation protocol for these two systems and investigate if it could reduce the differences in gene expression between them.


RESULTS
We collected identical blood samples on the PAXgene and Tempus systems and retrieved blood samples from two independent biobanks-NOWAC and HUNT3-which are based on PAXgene and Tempus, respectively. High-quality RNA was extracted from both sampling systems by using their original protocols and our common modified protocol, and were profiled on Illumina microarrays. Regardless of the protocol used, we found most of the measured transcripts to be differently affected by the two sampling systems. However, our modified protocol reduced the number of transcripts that were significantly differentially expressed between PAXgene and Tempus by approximately 50%. Expression differences between PAXgene and Tempus were highly reproducible both between protocols and between different independent sample sets (Pearson correlation 0.563-0.854 across 47323 probes). Moreover, the modified protocol increased the microRNA output of the system with lowest microRNA yield, the PAXgene system.


CONCLUSIONS
Most transcripts are affected by the choice of sampling system, but these effects are highly reproducible between independent samples. We propose that by running a control experiment with samples on both systems in parallel with biologically relevant samples, researchers may adjust for technical differences between the sampling systems.
Department of Laboratory Medicine, Children's and Women's Health, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway.
Anne Heidi
AH
Skogholt
Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway.
Einar
E
Ryeng
Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway.
Sten Even
SE
Erlandsen
Department of Laboratory Medicine, Children's and Women's Health, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway.
Frank
F
Skorpen
Department of Laboratory Medicine, Children's and Women's Health, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway.
Svanhild A
SA
Schønberg
Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway. pal.satrom@ntnu.no.|Department of Computer and Information Science, Faculty of Information Technology, Mathematics and Electrical Engineering, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway. pal.satrom@ntnu.no.|Bioinformatics Core Facility-BioCore, Faculty of Medicine, Norwegian University of Science and Technology-NTNU, 7491, Trondheim, Norway. pal.satrom@ntnu.no.
Pål
http://orcid.org/0000-0001-8142-7441
P
Sætrom
D001771:Blood Banks; D001800:Blood Specimen Collection / Q000295:instrumentation / Q000379:methods*; D020869:Gene Expression Profiling / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000295:instrumentation / Q000379:methods; D012313:RNA / Q000097:blood / Q000235:genetics*; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction
D035683:MicroRNAs; D012313:RNA
Blood samples; Microarray; RNA-isolation; Sampling systems; miRNA