Reduction of Systematic Bias in Transcriptome Data

Transportation of samples is essential for large-scale biobank projects. However, RNA degradation during pre-analytical operations prior to transportation can cause systematic bias in transcriptome data, which may prevent subsequent biomarker identification. Therefore, to collect high-quality biobank samples for expression analysis, specimens must be transported under stable conditions.

In this study, researchers from Iwate Medical University, Japan examined the effectiveness of RNA-stabilizing reagents to prevent RNA degradation during pre-analytical operations with an emphasis on RNA from peripheral blood mononuclear cells (PBMCs) to establish a protocol for reducing systematic bias. To this end, they obtained PBMCs from 11 healthy volunteers and analyzed the purity, yield, and integrity of extracted RNA after performing pre-analytical operations for freezing PBMCs at -80°C. They randomly chose 7 samples from 11 samples individually, and systematic bias in expression levels was examined by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), RNA sequencing (RNA-Seq) experiments and data analysis. Their data demonstrated that omission of stabilizing reagents significantly lowered RNA integrity, suggesting substantial degradation of RNA molecules due to pre-analytical freezing. qRT-PCR experiments for 19 selected transcripts revealed systematic bias in the expression levels of five transcripts. RNA-Seq for 25,223 transcripts also suggested that about 40% of transcripts were systematically biased. These results indicated that appropriate reduction in systematic bias is essential in protocols for collection of RNA from PBMCs for large-scale biobank projects.

rna-seq

On the basis of the results of this study, the researchers established a protocol to reduce systematic bias in the expression levels of RNA transcripts isolated from PBMCs. They believe that these data provide a novel methodology for collection of high-quality RNA from PBMCs for biobank researchers.

Ohmomo H, Hachiya T, Shiwa Y, Furukawa R, Ono K, et al. (2014) Reduction of Systematic Bias in Transcriptome Data from Human Peripheral Blood Mononuclear Cells for Transportation and Biobanking. PLoS ONE 9(8): e104283. [article]