Dear Johannes,

first of all i think it is a great idea trying to adapt you miRNA experiments to MIQE since this will improve your results as well as avoid contradicting results – which, in part, can be observed in miRNA research related to circulating miRNAs from body fluids.

I try to give some recommendations to address at least some of your points:

1.       Since you will be using primers from Exiqon (which I think is a very reliable way to measure mIRNAs) it is not necessary to do gradient PCR to optimize your primers for more specific products. You can check Specificity by using melting curves (since your system is based on SYBR green).

2.       RIN is a way (e.g. via bioanalyzer) to check the quality of your extracted RNA. I think this point is more important for small RNA seq or microarray systems since there are papers around which show that degraded RNA will not necessarily impact miRNA analysis with RT-qPCR (since degraded RNA does not neccesarily mean degraded mIRNA).

e.g. https://www.ncbi.nlm.nih.gov/pubmed/20378769

3.       Since you will measure miRNA signals from heart tissue, I don’t think that you will have problems with LOD (like this is the case in CSF or urine due to very low RNA content). Nonetheless it is important to do calibration curves to identify variations since you still might identify differentially expressed miRNAs at low levels with low fold changes  - standard curves will then give you an estimation of how reliable these fold changes are (not to forget samples size, replicates, etc). Since you didn’t write if you are going to analyze several miRNAs (e.g > 100) or just a few, you could to some absolute quantification only for dysregulated mIRNAs that you have identified after you finished your experiments. Here are some papers of how to generate miRNA standard curves:

https://www.ncbi.nlm.nih.gov/pubmed/20146939

https://www.ncbi.nlm.nih.gov/pubmed/18663219 (look at the SI material)

Specifically, I suggest to order synthetic ss RNA oligos matching the mature mIRNA sequences of your interest (e.g. from IDT), adapt each to an equal conc like 100 µM, pool these to obtain an oligo pool of e.g. 10 µM (each oligo). Then you can do a serial dilution (10X, 5X, 2X – depends on how close your curves should be). Pay attention that your very diluted oligos theoretically cover the LOD (e.g. 5-50 copies) since this is what you want to test. From each dilution of interest do cDNA synthesis (with replicates) following PCR. I think serial dilutions from RNA better simulates the reality (RT efficiency) instead of doing cDNA dilutions. Plot log conc versus Cq values and fit a regression line. You will get R2, LDR (how many points are linear) and variation (PCR and cDNA replicates at each dilution). Efficiency can be calculated by using E = [10^(-1/slope)] – 1. Errors like SE or CI’s can be obtained by using a statistics tool (like GraphPad or GenEx).

4.       LOD can be obtained by performing replicate standard curves (e.g. 6 replicate curves). Here I would refer to GenEx which offers a great explanation to this topic and how to statistically obtain the LOD at a given confidence (which is then your evidence for your LOD).

5.       Here you could e.g. optimize your RNA input amounts for cDNA synthesis, trying varying amounts of RNA to check at which point inhibition occurs (e.g using too much RNA).

6.       I’m not familiar with ABI since we are using the LC480 (Roche) – however, to do absolute quantification I think use “standard curve”. For calculating differential expression (fold changes, e.g. two different developmental time points in your case) you could use comparative Ct method (2^-ddCt).

To your normalization problem, you could to an exploratory study by using you different samples (stages) and measure some miRS to see which display low variation (e.g. by using GeNorm or NormFinder).

Hope the recommendations will help you – but consider that there are always alternative strategies around.

Johannes

Thanks a lot Johannes!

I am going to work on these suggestions and have a read of the mentioned papers. I like your recommendation of using RNA oligos for calibration/standard curve. I guess that will help me a lot to move one with this experiment.

My Experiment is small scale, I am looking at 6 microRNAs at the moment.

I am gonna post how things progress later.

Dear Johannes,

Have you considered digital PCR?  It has many advantages over qPCR including the ability to provide absolute quantification and robustness to variations in PCR efficiency across different samples and assays.