RNA isolation, RT-PCR, qPCR and endpoint PCR

These sections have the least flexibility of all the methods as there are widely accepted standards for reporting qPCR data that you have to follow; MIQE Sounds constraining but actually it just means you don’t need to make decisions, you just follow the rules!

Even if you are not using quantitative PCR or RT-PCR techniques, a lot of the MIQE guidelines still apply as good practice.

The lists below are for easy reference. Many of the phrasings here are directly from the article above, edited for brevity. If you are serious about your RNA analyses and want to be taken seriously (big tip; you do!) you should read the article linked above before you do any more qPCR!

downloadable checklist here


  • “Reference genes/transcripts” are prefered to “housekeeping”
  • qPCR and RT-qPCR are used for quantitative approaches (i.e. don’t use RT to mean “real-time”;RT means reverse transcriptase)
  • Quantification is a word. quantitation isn’t!
  • C subscript q is the term used for the threshold point of detection – not any of the other versions used by different light cycler manufacturers

Experimental design

Usual rules; as with all other experiments – define;

  • the experimental groups/control groups,
  • sample size,
  • independent sample
  • Number of replicates (biological and technical)


In practical writing terms – each of the subsections below can be dealt with as a paragraph following this order.

Making your writing bite sized can help make sure you cover all the details you need.


Describe all the steps from cells/tissue to RNA/DNA!

As with every other methods section; make sure you include manufacturer information for all of the following reagents. Here and onward.

  • Description of source material, mass, dissection etc, including things like post-mortem time
  • Describe time in storage before processing and how stored (if frozen; how and how quickly, if fixed; how?)
  • Describe processing procedures – name of kit or reagents and any modifications
  • Details of DNase or RNAse treatment
  • Contamination and nucleic acid quantification approach (instrument and method)
  • Purity (A260/280)
  • Yield
  • RNA integrity method/instrument – electrophoresis traces, RIN of 3’/5′ transcripts

Reverse Transcription

Describe the complete reaction conditions!

  • Amount of RNA and reaction volume
  • Oligonucleotide used for priming (oligo dt/ random hexamers etc)
  • Reverse transcriptase and concentration
  • Temperature and time
  • Storage conditions of cDNA

qPCR target information and Oligonucleotides

  • Gene symbol and accession number
  • location of amplicon and amplicon length
  • Include which splice isoforms are amplified
  • In silicon specificity screen (BLAST etc)
  • Primer sequences (and probe sequences if used) – references if required
  • Location and identity of any modifications
  • Purification method

If you have multiple oligo, this one of the occasions where it can be helpful to use a table! Make sure all the details go into the table though!

qPCR protocol

  • Complete reaction conditions
  • Reaction volume + amount of cDNA or DNA
  • Primers, Mg2+, dNTP concentrations (+probe), + additives (DMSO, SYBR Green) Polymerase identity and concentration, Buffer/kit identity and manufacturer + chemical composition
  • Information about plates, tubes, etc
  • Complete thermocycling parameters

Viva tip – anytime you have used a kit for an experiment you should be able to explain what is in that kit and what is happening at each stage. Kits are great but you should understand your science!

Assay Validation

  • Method for Cq determination
  • Specificity; gel, sequence, melt curve (*see below), digest
  • Results for no template controls
  • Calibration curve with slope and y intercept – PCR efficiency calculated from slope + r2 (*see below)
  • Outlier identification and disposition
  • Justification of number and choice of reference genes
  • Number and concordance of biological replicates
  • Number and stage of technical replicates (i.e. reverse transcription or qPCR repeats)
  • Repeatability and reproducibility
  • Power analysis
  • Statistical methods for significance determination, software
  • Cq or raw data submission

*melt curves and efficiency curves are critical to evaluating your data – I have had many students say to me that they don’t have these data as the primers were validated by a company. That’s not good enough to publish and you should set yourself higher standards.

Get these data from the cDNA you have made from your tissue/cells! Differences in impurities, integrity, RT approach, and cycling conditions will all affect your primer’s efficiency!

These data accompany every publication, usually in the supplemental figures*

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