Choosing reference genes for qPCR normalisation

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Quantifying mRNA via cDNA levels as in a QRT-PCR hinges on the references you choose. If you pick only one reference gene and your pick is not constant across different conditions or samples, your results will be skewed. Pick several and check whether they satisfy the criteria for a good reference gene.

Contents

Normalisation against "housekeeping" genes, rRNA, total RNA?

There is an ongoing debate what is the best reference to normalise against. Many studies use a single :-( or a set of so called housekeeping genes, which despite their label are often not constant or comparable. Other studies have suggested the use of cell number, total rRNA [1] [2], or total RNA.

The ideal reference gene

A mRNA used as reference or standard of a QRT-PCR (and other experiments) should have the following properties:

  • expressed in all cells
  • constant copy number in all cells
  • medium copy number for more accuracy (or similar copy number to gene of interest)

Common reference genes

Common reference mRNAs linked to known mouse primer pairs:

  • β-actin (common cytoskeletal enzyme) [3], [4]
  • ribosomal proteins (e.g. RPLP0)
  • cyclophilin mRNA
  • MHC I (major histocompatibility complex I)

Common but not recommended references

  • glyceraldehyde-3-phosphate dehydrogenase GAPDH (common metabolic enzyme) [5], [6] - see QRT-PCR#Reference_mRNAs
  • ribosomal RNAs (28S or 18S) - see below

Reference genes across tissues

If you are comparing mRNA/cDNA levels from different tissue it is especially important that reference gene levels are close to constant across different tissues. Radonić et al compared 13 putative reference gene levels in 13 different human tissues [PMID 14706621]. The results are summarised below (bold most recommended, only recommended genes included):

  • genes with the smallest Ct range (most constant levels): G6PDH, RP2, HPRT, beta2M, PPIA
  • genes found in all tissues analysed: TBP, RP2, Act, Tub, PLA

Primer collections

Search primer repositories like RTPrimerDB (see also below) and check the literature before doing it from scratch.
Check out the Eccles Lab collection of human and mouse qPCR reference genes on OWW.

Stability

  • Ajeffs 06:55, 21 April 2007 (EDT): In addition to the given requirements of good (well, acceptable) specificity and efficiency of the reference gene primers, the next most important aspect of reference gene selection is stability. I don't care if the CT value of my reference genes (yes, genes, not gene) is close to the target genes/s or not - as long as the efficiency of all the primers is similar, and they are all working within their respective limits of detection i.e. linear range, then the stability of the reference genes between samples, treatments, etc. is the most crucial aspect of generating believable qPCR results.

Selection

  • Ajeffs 06:55, 21 April 2007 (EDT): Screen a handful of ref genes, select the most stable using genorm, bestkeeper etc, use at least 2 reference genes for subsequent reactions and normalisation. Inlcude your genorm M values when publishing qPCR data.

Use of 18S

  • Ajeffs 06:55, 21 April 2007 (EDT): 18S is generally a terrible choice for a reference gene thanks to the combination of (i) high abundance (creating a 1:100 dilution of template to run in parallel with neat template just for 18S is a complete drag); and (ii) having different degradation characteristics to mRNAs (it appears to be more resistant to degradation). However, if you can show that you have screened 5-10 reference genes, and 18S is still the best for your specific situation then so be it (but do try 28S if you or you PI is hung-up on 18S).
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