Poster Presentation Australian Islet Study Group 2013

Comparing high-throughput qPCR technologies for microRNA diagnostics: Does size matter? (#17)

Ryan J Farr 1 , Mugdha V Joglekar 1 , Anandwardhan A Hardikar 1 , RAPID Study Group Investigators 1
  1. The University of Sydney, Camperdown, NSW, Australia

Small noncoding RNAs / microRNAs  have generated increasing interest and attention as biomarkers for prediction of cancer, obesity and even diabetes. Although several conventional real-time quantitative PCR (qPCR) approaches are available, the most common platform involves analysis using 96-well plates.  

Whilst the underlying biochemistry remains largely unchanged, qPCR can now be undertaken in various formats that showcase the growing field of nanoengineering. Reducing the volume needed for a qPCR reaction allows a significant increase in the number of assays that can be performed, while decreasing the reagents consumed and time required. Although this can be enticing for laboratories that routinely employ qPCR-based diagnostics in clinical research, these technologies must be able to reliably detect transcripts of interest, especially those present at very low copy numbers. When a sample containing a low number of transcripts is split into very small volumes, their likelihood of equal distribution across multiple reactions decreases.  Many manufacturers have attempted to overcome this by pre-amplifying the samples prior to qPCR, but is this optimal?

Here, we have compared conventional 96-well qPCR formats (5 and 20 µl reaction volumes) with three high-throughput technologies: TaqMan Low Density Array (TLDA, Applied Biosystems), OpenArray (Applied Biosystems) and Dynamic Array (Fluidigm). These technologies contain reaction volumes of 1 µl, 33 nl and 15 nl respectively. To investigate the capabilities of each system, we measured various microRNAs using RNA isolations from diabetic and non-diabetic serum (RAPID Study) as well as human pancreatic cells. Multiple replicates were chosen to compare the variability between cycle threshold (CT) values and the overall reproducibility of each platform. Furthermore, the ease of use is compared, including sample preparation, RNA input, use of pre-amplification, number of wells and software available for analysis. We believe that this analysis will assist researchers in making the transition to high-throughput technologies by providing a comprehensive review of the benefits/limitations of each platform.   

  1. We acknowledge the generous support of Australian Research Council (ARC) towards the Australian Future Fellowship offered to AAH. MVJ is a JDRF post-doctoral fellow and RJF is an APA recipient. Further details about RAPID Study are available on www.RAPIDstudy.info