Reference gene for normalisation - for different growth rates - (Aug/15/2013 )
I am just starting RT-qPCR to study the activity of the promoter of a gene present on a recombinant plasmid in E. coli.
This is known to be a stationary-phase promoter. Apart from this, I would also analyse the expression of rpoS - the stationary phase sigma factor and rpoD - the primary sigma factor, for comparison. Samples would be taken from different steady states from a chemostat, each corresponding to a particular growth rate. So, I expect rpoD transcripts to be high at growth rates near the maximum while rpoS and the target promoter should be expressed high at low growth rates (mimicking starvation; corresponding to stationary phase during batch).
My problem is that no matter which reference gene I choose for normalisation, I think it is impossible to expect its expression to be steady over different growth rates since growth rate is a parameter with such global effects on the transcriptome. What is your take on this ?
Also, the effects of growth rate on the plasmid copy number and hence available copies of the target gene for transcription must also be taken into account during normalisation. This is another issue I am thinking about. Would a plasmid-based gene be a better candidate as reference gene instead of a genome-based one like gapA. But then the other 2 genes rpoS and rpoD are genome-based.
Would anyone like to comment on these? Should I check multiple candidate reference genes from genome and plasmid ?
I think your last question is the key. Yes, you need to check multiple candidate reference genes from both the genome and plasmid. Don't assume a traditional reference gene will be suitable for your experiment - this needs to be confirmed. Also, it is usually better to normalize the expression of your genes-of-interest using more than one reference gene. So I suggest testing multiple candidates, and then use the 2-3 most stable genes as your reference genes.
thank you for your response!
we are going for 9 house keeping genes and selecting the best 4 genes as reference. This is to be done with each gene.