My question is regarding rt-pcr: I am trying to quantify the mRNA levels of a particular gene of my interest in the G1, S and G2/M phase of the cell cycle. However as i have read a housekeeping gene requirement for relative quantification, and found that all the three generally used house keeping genes..tubulin,/actin/ribosomal rna are changing in the different phases of the cell cycle....what should i do in order to quantify my genes expression?
Is it acceptable if I take equal amounts of initial RNA of each phase >> convert to cDNA>> spike each sample with the same amount of an exogenous dna (purified plasmid) that contains a gene not present in my particular organism of study>> perform pcr using sybr green and quantify using DDCt method using the equation:
DCt = Ct (gene of interest) - Ct (exogenous plastmid gene)
DDCt = [ DCt](S PHASE) - [ DCt](G1 PHASE) & [ DCt](G2/M PHASE) - [ DCt](G1 PHASE)
Your suggested approach seems to be ok. But be careful with DDCt method - it only works, when amplification efficiencies of both target and control PCR are approximately equal. Should you need more precise results, determine efficacy of your PCRs and calculate your results according to M. Pfaffl (Nucleic Acids Res. 2001 May 1; 29(9): e45.)
In my experience, 18S or GAPDH mRNA are good normalizers for cell cycle genes. I used them in a number of experiments in HeLa cells, and they seemed to be quite constantly expressed over time. However, the use of an exogenous spike in (as you suggest) could further help your quantification.
Once I compared the expression of different "house keeping" genes through out the cell cycle in NIH3T3 cells. Cells were first synchronized in G0 by 24 hours of serum starvation. Then I added serum and collected RNA at various time points. Ppia and B2M genes seemed to be best, since its expression didn't vary that much in the various time points (within 1.5 fold change). All the others (B-Actin, Hprt, GusB, Pgk1) varied too much (up to 3.5 fold). Anyway, I think your DNA spike approach seems reasonable too for your quantification, but if you want to include an endogenous reference gene, I would recommend Ppia. It's been working fine for my experiments.
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