Whenever a PCR is done, we have to use housekeeping genes like GAPDH, to self normalise the values to account for different starting cDNA/DNA. Now there are many different genes like GAPDH, ubiquitin, actin etc.

Now when dealing with cells, I can understand that due to their immortal nature and frankly shocking number of generations undergone by them, the expression of the housekeeping gene may change.

Assuming that I am not dealing with cells and instead with animal tissues, does it matter which house keeping gene I select? Or in other words is GAPDH going to give me the same consistency between samples as something like 18s Ribsomal RNA or am I missing something specific?


2 Answers 2


Yes, it does matter. Gene expression varies a lot thoughout tissues and living conditions, so you need to test a variety of genes and choose the ones with the smallest variation in the expression between sample and control.

If you don't find any, you have to test other genes for this purpose. This is important, as this can severly affect the outcome of your experiment, since you normalize to the housekeeping genes. If these are not constant, it will cause problems. Have a look into the references, this helped me a lot.


  1. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.
  2. The normalization of gene expression data in melanoma: investigating the use of glyceraldehyde 3-phosphate dehydrogenase and 18S ribosomal RNA as internal reference genes for quantitative real-time PCR.
  3. Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references.

You need to watch out though. Some very used genes could be very uninformative as housekeeping genes in qPCR. ACTB and GAPDH have tons of pseudogenes (analogous genes not yielding proteins) that can interfere with the PCR. You can read more in this article (1).

To make it even worse, the PCR amplification fragments can be of the exact same length as the ACTB amplicon, making it impossible to differentiate.

In addition, you have to consider the specific cell type/application/treatment, because some mRNAs could be very constant through treatment A on cell type 1, but vary with treatment B or on cell type 2.

I think the best would be to use multiple housekeeping (3-5) and see how they behave relative to one another. You could also use the mean of these housekeeping.

(1) Sun, Yuan, et al. "Pseudogenes as weaknesses of ACTB (Actb) and GAPDH (Gapdh) used as reference genes in reverse transcription and polymerase chain reactions." PloS one 7.8 (2012): e41659.


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