My experiment is this: there are 2 very similar genes which are expressed in a mutually exclusive fashion but at essentially identical levels. I want to look at normal donor and primary samples and investigate the proportion of cells expressing each gene by qPCR. So I want to look at the expression ratio between gene 1 and gene 2 (usually 2:1) and see if this varies between samples, and also if any treatments affect this ratio. I make cDNA from each sample then use 2 sets of primers (specific for each gene). So both sets of primers will lead to amplification in each polyclonal sample but only one or other will prime in a clonal sample (eg cell line). Make sense?
Can I actually use qPCR to do this? Is it meaningful to compare the expression of 2 different genes within or across samples? Do I need to make calibration curves to confirm both PCRs are efficient? What do people think would be the best way to compare and express data?
thanks!
Hi Paul,
Could you not use a housekeeping gene as reference? And quantify both the genes of interests in all samples even though you know it is not expressed in some of them? Then do ddCT calculations.
Alternatively, but similarly, you could quantify the two genes on all samples, but use standard curve for quantification. This could simply be a pool of cDNA from all experiments that are serially diluted. Make sure that the highest concentration standard is diluted at least ten fold less than the samples though. You can assign arbitrary values to the standards, e.g. 1000 100 10 and 1 etc. Then you can relate the values you get for gene1 to valies for gene2. Or gene 1&2 to a housekeeping gene without doing the ddCT calculations...
Cheers,
Vegard
Hi Paul,
As Vegard suggested, normalize expression of gene 1 and 2 to housekeeping gene for each sample.
To present the data, I would use dot plot to show the normalized values of gene 1 and 2 for each sample on X and Y axis (instead of plotting ratios). In that way, hopefully the normal/disease/treated samples will show clustering and it is easier to pick up any trend/correlation for the two genes.
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