Quantitative Real Time PCR

Changes in specific gene expression patterns often reflect adaptations in cellular functions to certain biological stimuli. These transcriptional changes can be assessed and quantitated using real time PCR (qPCR). This is an incredibly sensitive technique, and the quality of your results is directly correlated with the stringency in your workflow. Typically, the real time (qPCR) workflow involves extracting high quality RNA (RNA isolation 140 kb pdf file) from whole tissue or cultured cells, followed by bioanalysis (using the Agilent 2100 Bionanalyzer) of the quality and quantity of your RNA. This RNA is then normalized (quantity) for reverse transcription (106 kb pdf file) and equal amounts of cDNA are used in the qPCR reaction using the ABI ViiA7 (384, 96 well and TLDA format) or the ABI QuantStudio 7 (384 well format). There are two predominant methods of experimental qPCR quantitation: absolute and comparative. With absolute quantitation, copy-number information is obtained by comparing data with standard curves generated with plasmids of the target gene. With comparative (or ΔΔCt) quantitation, levels of expression of your gene of interest are quantitated relative to those of a housekeeping (reference) gene (100 kb pdf gene). Reactions can be set up using pre-validated fluorescent probes or with SYBR green dye in the master mix. Any primer sets used in combination with SYBR green must be validated first to optimize concentration, efficiency and R² values, using end-point PCR (with the ABI Veriti) and by running standard curves in your qPCR instrument of choice. Analysis software is available (ABI Expression Suite) for all real time PCR experiments. See below for detailed information on the qPCR workflow.

Many factors must be taken into consideration for a successful gene expression study, even long before any sample processing occurs. For example, in order to minimize experimental variability, efforts must be taken in carefully selecting proper control groups, ensuring that an adequate number of technical and biological replicates are incorporated into the study, that experimental conditions and tissue/cell isolation are all strictly recorded and reproduced with each animal/cell line, etc. Here are some important factors to consider when you design your study:

  • What are the different treatments or disease groups you will have? How many animals/conditions/treatments will you have to do to “power” the study effectively (make it statistically significant)? How many and what are the target genes in your study and what are the housekeeping genes (reference) you wish to use? Do you know that their expression does not change in your experimental model (i.e. Housekeeper Ct values should be within 0.5 across different treatment/control groups) so as to not introduce variability into your study
  • What group constitutes your control group? Is it a proper control for your experimental condition (i.e. sham treated or untreated, t=0, normal/wild-type background)
  • Have you incorporated both biological and technical replicates into your study? Each sample (from a culture well, plate, flask or individual animal/organ/biopsy) should be run in triplicate and there should a minimum of three representative (individual) wells/plates/flasks/animals/etc. from each treatment or control group
  • Keep a stringent record of experimental conditions so you can ensure reproducibility: duration of treatment, formulation of any drug treatments, dosages, age and sex of animal, genetic background, cell culture conditions, media, growth phase and/or cell density at time of treatment, etc.
  • Treatment of cells/tissue at time of RNA isolation: duration or sample harvesting, time from harvesting tissue to snap freezing (if frozen) or processing (if fresh), method that sample is harvested, time that tissue is handled after freezing to isolation, method that RNA is isolated (see below for greater details on considerations for RNA isolation)

Now that you have designed your experiments carefully, there are many details to think about when setting up your actual qPCR experiment. Here is a breakdown of the qPCR workflow and things to think about at each step:

qPCR workflow:

  1. RNA isolation (140 kb pdf file)
  2. Bioanalysis
  3. Reverse transcription (126 kb pdf file)
  4. Designing and validating primers (677 kb pdf file)
  5. qPCR setup and run with QuantStudio 7 software (1 MB pdf file)
  6. qPCR data analysis (4.5 MB pdf file)