Hi,

When we are running miR qPCR we usually include at least 3 controls in case one or more of them are unstable.

Commonly used small RNA controls are RNU44, RNU48, U47, snoRNA202, snoRNA234, snoRNA251.

I would try adding at least one of those to your analysis and see how you get on.

Hope that helps.

Hi,

Thanks for that! Will definitely consider that.

Using the small nuclear RNAs (U6 etc) are as suitable as using 18S for mRNA expression normalization as small nuclear RNAs are not in the same fraction as miRNAs. You should opt to use actual miRNAs that are expressed in your tissue type. I found that in my heart samples, U6 and RNU1a were unstable compared to candidate  miRNAs.

Thandiwe,

If you're going to look at the genes listed by Benjamin as candidate reference genes, you may want to consider evaluating the stability of those genes algorithmically.

There are a couple good methods for this - GeNorm and Normfinder. GeNorm used to have a free add-on for Excel, but is now only available as past of the qbase+ software. However, Normfinder is free for academic use http://moma.dk/normfinder-software. These are useful if you decide to do a qPCR to evaluate multiple candidate reference genes at once, as these algorithms will try to determine the combination of reference genes with the best stability in your sample set.

http://moma.dk/normfinder-software

Both Can and Aaron make valid points. 

I should of course have mentioned that the best way to pick endogenous controls is empirically using one of the software packages as Aaron suggests. 

The genes I recommended are often used and we have found then to be stable for many experiments but of course that will not hold true all the time.

Good luck and I hope you find something that works for you. 

Try RPL13AB

All the best.

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