Hi Suzan

RNU6B is not the best choice for normalization of serum miRNAs. In my hands the best strategy to normalize cT values is to use an spike-in synthetic miRNA added either before RNA extraction or before cDNA synthesis. Some authors also used highly abundant circulating miRNAs as miR-16. However in my hands those miRNAs are very variable among samples and experimental conditions, and sometimes will give you bad results.

If you are dealing with miRNA screening with more than 50 determinations per sample, you can use the global normalization strategy as implemented in several software packages.

Hope it helps. Best

Paco

You can use the most stably expressed miRNA as housekeeing for normalization.

Hi Suzan

RNU6B is not the best choice for normalization of serum miRNAs. In my hands the best strategy to normalize cT values is to use an spike-in synthetic miRNA added either before RNA extraction or before cDNA synthesis. Some authors also used highly abundant circulating miRNAs as miR-16. However in my hands those miRNAs are very variable among samples and experimental conditions, and sometimes will give you bad results.

If you are dealing with miRNA screening with more than 50 determinations per sample, you can use the global normalization strategy as implemented in several software packages.

Hope it helps. Best

Paco

what about using total RNAs such as B-actin or GAPDH as housekeeping for MIRNAs

as done by chen et al in his paper: Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases.Cell Research (2008) 18:997-1006.

I am not an expert but the absence of a consensus miRnome of the serum makes spiking the best choice. If you really want to use an endogenous normalizer, "just" go a few datasets that are publicly available and determine which microRNAs are always present at similar levels in normal control sera. That sounds like a lot of work but that is needed eventually in order to use microRNAs as serum markers for diseases. Was such a screen done already? If microRNAs want to make the jump into the clinic, somehow it has to be defined what is normal and pathological relative to something else. Basically, the entire filed has to be standardized. Most sense makes to use microRNAs as normalizers. you want ot compare apples with apples. The easiest way out may be checking for the biggest single study ever performed with the largest number of healthy controls from different genders and age groups. Then confirm the normalizers, the microRNAs that are stable in between controls, confirm them by checking other datasets. Kind of a meta-analysis. Does that make sense?