Differences in amplification efficiency are not the only source of variability in a qPCR experiment. Several factors are responsible for noise in qPCR experiments e.g. differences in:
Normalization will eliminate this noise as much as possible. In this way it is possible to make a distinction between genes that are really upregulated and genes with high expression levels in one group of samples simply because higher cDNA concentrations were used in these samples. In qPCR analysis, normalization is done based on housekeeping genes.
Housekeeping genes are measured in all samples along with the genes of interest. In theory, a housekeeping gene should have identical RQ values in all samples. In reality, noise generates variation in the expression levels of the housekeeping genes. This variation is a direct measure of the noise and is used to calculate a normalization factor for each sample. These normalization factors are used to adjust the RQ values of the genes of interest accordingly so that the variability is eliminated.
These adjusted RQ values are called Normalized Relative Quantities (NRQs). In qbase+ housekeeping genes are called reference genes. In our data set there are three reference genes: Stable, Non-regulated and Flexible. On the Normalization page we can define the normalization strategy we are going to use, appoint the reference genes and check their stability of expression.
You can specify the normalization strategy you want to use on the Normalization method page:
We have incorporated 3 housekeeping genes in our experiment so we select the
Reference genes strategy.
You have to indicate which targets should be used as reference genes since qbase+ treats all genes as targets of interest unless you explicitly mark them as reference genes on the Normalization method page:
We have measured 3 housekeeping genes: Stable, Flexible and Non-regulated so we tick the boxes in front of their names.
It’s not because you have appointed genes as reference genes that they necessarily are good reference genes. They should have stable expression values over all samples in your study. Fortunately, qbase+ checks the quality of the reference genes. For each appointed reference gene, qbase+ calculates two indicators of expression stability
It is considered that the higher these indicators the less stable the reference gene.
M and CV values of the appointed reference genes are automatically calculated by qbase+ and shown on the Normalization method page:
The default limits for M and CV were determined by checking M-values and CVs for established reference genes in a pilot experiment that was done by Biogazelle. Based on the results of this pilot experiment, the threshold for CV and M was set to 0.2 and 0.5 respectively. If a reference gene does not meet these criteria it is displayed in red. As you can see the M and CV values of all our reference exceed the limits and are displayed in red.
If the quality of the reference genes is not good enough, it is advised to remove the reference gene with the worst M and CV values and re-evaluate the remaining reference genes.
Both the M-value and the CV are measures of variability. The higher these values the more variable the expression values are. So we will remove the gene with the highest M and CV.
You can remove a reference gene simply by unticking the box in front of its name.
After removing Flexible as a reference gene the M and CV values of the two remaining reference genes decrease drastically to values that do meet the quality criteria. M and CV values that meet the criteria are displayed in green.
This exercise shows the importance of using a minimum of three reference genes. If one of the reference genes does not produce stable expression values as is the case for Flexible, you always have two remaining reference genes to do the normalization.
So after normalization you have one NRQ value for each gene in each sample.
Next to go to the Scaling page.