Abstract
Subtle molecular differences indicate the heterogeneity present in a number of disease settings. Digital-PCR (dPCR) platforms achieve the necessary levels of sensitivity and accuracy over standard quantitative RT-PCR (qPCR) that promote their use for such situations, detecting low abundance transcript and subtle changes from gene expression. An underlying requisite is good quality RNA, principally dictated by appropriate tissue handling and RNA extraction. Here we consider the application of dPCR to measures of gene expression in pathological tissues with inherent necrosis, focusing on rheumatoid subcutaneous nodules. Variable RNA fragmentation is a feature of RNA from such tissues. Increased presence of transcript fragmentation is reflected in a proportionate decrease in Agilent DV200 metric and downstream, a reduction in endogenous control genes’ expression, measured by RT-dPCR. We show that normalisation of target gene expression to that for endogenous control genes sufficiently corrects for the variable level of fragmented RNA. Recovery of target gene values was achieved in samples comprising as much as 50 percent fragmented RNA, indicating the suitability and appropriate limitation of such data treatment when applied to samples obtained from inherently necrotic tissues.
Highlights
Subtle molecular differences indicate the heterogeneity present in a number of disease settings
Key factors in conducting research in human disease are both the availability and quality of appropriate tissue samples. This combination is often a fait accompli, with potential confounders associated with available human tissue, including characteristics of any inherent pathological processes, likely to influence the quality of the tissue and yield of accurate molecular results
This study examined the characteristics of human rheumatoid subcutaneous nodules, an inflammatory lesion with inherent necrosis, associated with granulomatous inflammation
Summary
Subtle molecular differences indicate the heterogeneity present in a number of disease settings. Digital PCR (dPCR) is becoming a valuable technique for the quantification of gene expression, providing increased sensitivity, reproducibility and linearity when compared to real-time quantitative PCR (qPCR) These advantages are relevant for low-abundant targets[1,2,3]. There is currently little information available concerning the rationale and efficacy of reference gene normalisation to correct for variable quality of input RNA in RT-dPCR. Such variation is more likely when sampling from disease-associated or tumour tissues that incorporate inherent necrosis or where significant areas are affected by mechanisms leading to cell death[4,5,6]. Fragmented RNA of at least 100 nucleotides in length contributes to the total www.nature.com/scientificreports/
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