RT-PCR Internal Standard - (May/28/2009 )
I am currently having difficulty finding an internal control for my RT-PCR. I am looking at the expression of mutliple genes daily for a few weeks, and under these circumstances there appears to be no commonly used internal control that does not vary in expression over this long period of time. I figure in this case I have two options. 1) Use the three internal controls that I have tried so far, but the variation in these genes is large, and thus I doubt my results could ever be significant. Also, this option will add a lot more financial cost to my overall analysis since I would have to run three internal controls. 2) Lose the internal control and just do a copy # per a fixed amount of RNA (ng). I realize the 2nd option is not as rigorous, but it eliminates the problem with variation in the internal controls. So, I am wondeirng can anyone think of any other options for this situation? I am fairly new to RT-PCR so any suggestions or comments would be appreciated.
First you need keep in mind that NO such gene that does not vary in expression over experimental conditions or treatments. You have to do some test to pick up best control gene(s) for you.
What are the control genes you have tested?
Beside rRNA, GAPDH and β-actin, other useful internal standard candidates include:
hypoxanthine phosphoribosyl-transferase (HPRT), acidic ribosomal phosphoprotein P0 (36B4), β-2 microglobulin (β2MG), peptidylprolyl isomerase A(PPIA), histone H2A, TATA box binding protein, and tubulin.
Some less popular candidates include: albumin, ATP synthase 6, eukaryotic translation elongation factor 1γ, glucose 6-phosphate dehydrogenase, β-glucuronidase, phosphoglycerokinase, phospholipase A2, porphobilinogen deaminase (hydroxymethylbilane synthase), ribosome protein L-15/L-13/S26, RNA polymerase II, transferring receptor, ubiquitin C, and U2snRNA. The list can go on and on.
I will suggest try HPRT, 36B4, β2MG.
If you have expression profile generated by microarray or some other person you know have done it, you have another option. Get microarray data and find those genes that do not change. As long as they do not change expression level, they can serve as internal standard and they donít have to be house keeping genes.
I have had very good results using ribosomal protein L15. Mainly because RP are not regulated transcriptionally, but translationally... But that depends on your cells. You can also calculate absolute expression by using a standard curve. This is independent of reference genes.
What do you mean with copy # per fixed amount of RNA? Simply use the different CT values from same amounts of RNA? I don't recommend since your RT efficiency might vary. Better use an external standard (spike-RNA), and quantify your data like that.
Hope that helps,