Design and sampling plan optimization for RT-qPCR experiments in plants: a case study in blueberry
Author
Die, Jose V.
Román, Belén
Flores, Fernando
Rowland, Lisa J.
Publisher
FrontiersDate
2016Subject
RTReverse transcription
RTase
Reverse transcriptase
qPCR
Quantitative real-time PCR
RT-qPCR
Reverse transcription–qPCR
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Show full item recordAbstract
The qPCR assay has become a routine technology in plant biotechnology and agricultural research. It
is unlikely to be technically improved, but there are still challenges which center around minimizing
the variability in results and transparency when reporting technical data in support of the conclusions
of a study. There are a number of aspects of the pre- and post-assay workflow that contribute to
variability of results. Here, through the study of the introduction of error in qPCR measurements at
different stages of the workflow, we describe the most important causes of technical variability in a
case study using blueberry. In this study, we found that the stage for which increasing the number of
replicates would be the most beneficial depends on the tissue used. For example, we would
recommend the use of more RT replicates when working with leaf tissue, while the use of more
sampling (RNA extraction) replicates would be recommended when working with stems or fruits to
obtain the most optimal results. The use of more qPCR replicates provides the least benefit as it is the
most reproducible step. By knowing the distribution of error over an entire experiment and the costs
at each step, we have developed a script to identify the optimal sampling plan within the limits of a
given budget. These findings should help plant scientists improve the design of qPCR experiments and refine their laboratory practices in order to conduct qPCR assays in a more reliable-manner to
produce more consistent and reproducible data.