Hi Subramaniam

You can do your analysis of samples in two ways:

1) Relative quantification: where you have a control sample and a treated samples/test condition and you try to estimate the relative expression of your gene of interest in both the sampes in reference to a house keeping gene (actin/GAPDH) and then estimate the extent of down-regulation/ up-regulation of the gene of interest. Here you jus estimate the fold-change and not absolute no. of transcript molecules

2) Absolute quantification: In this approach one generates a std. curve of the gene of interest and try to estimate the transcript levels in the samples...This is more precise

and for you to get best out of your data...see what type of analysis you need to do. ...and ....I would suggest go though the manual of the machine and software your are using and anlyze your data using the same software..

bye

It is important to mention:

What is the gene expression you are looking for? presence/absence of transcript, relative change, absolute quantification. What is your normal/control in that case? How are you normalising the Ct values?

Hi Subramaniam

You can do your analysis of samples in two ways:

1) Relative quantification: where you have a control sample and a treated samples/test condition and you try to estimate the relative expression of your gene of interest in both the sampes in reference to a house keeping gene (actin/GAPDH) and then estimate the extent of down-regulation/ up-regulation of the gene of interest. Here you jus estimate the fold-change and not absolute no. of transcript molecules

2) Absolute quantification: In this approach one generates a std. curve of the gene of interest and try to estimate the transcript levels in the samples...This is more precise

and for you to get best out of your data...see what type of analysis you need to do. ...and ....I would suggest go though the manual of the machine and software your are using and anlyze your data using the same software..

bye

On this website you find loads of information regarding RT-qPCR: http://www.gene-quantification.info/

May be you will find some answers to your questions there.

Good Luck with your experiments!

I am looking at relative expression levels of genes rathter than absolute quantification. I pool my samples together and then serial dilute to make a standard curve. I then plot the standard curve ct values and use the equation to calculate the relative expression in my cDNA samples.

So the graph equation is as follows (y=mx+c), Ct values are y. you can plot your x-axis as any numbers as long as they reflect the serial dilution i.e doubling dilutions i.e 1:10 1:20 1:40 etc... I also make sure the Rsquared value of the graph is >0.98

I then log my ct sample values using the graph equation as follows:

x = [(y- c)/-m] where c and m are from the standard curve. I then antilog them and then normalise to my reference gene (for which I have calculated the relative amounts too).

you can either show results as realtive expression or I calculate fold change compared to my control.

I hope this helps. I found it confusing to start with as there are many ways you can work it out.

I have attached an excel sheet as an example with made up ct values. I hope it is of use. It helps to understand why you are doing each step before using the sheet rather than just plugging numbers in.

@Sarah.....she is right in analysing the way she has explained......in the method she has explained...you get some more advantage....

1)..you are able to get the information about the appropriate concentration of cDNA for doing the qRT-PCR analysis as it should neither be too dilute and nor too concentrated...to avoid many problems..

2) one can also analyze the amplification efficiency of a new set of primers in a serially diluted cDNA samples...

and

thanks for attaching the template...it is useful...

bye

HI folks, Thank u all for ur valuable information ... :-)

Thanks Sarah for your nice answer and support as well. It is really helpful.

Dear Sarah,

Is it correct if I make a standard curve for all my primer pairs in one plate and prepare another plate only for my samples (by deciding concentration from the standard curve, usually the concentration with Ct value between 15-20); and then use Ct value of samples and m and c from the standard curve and then follow the method as explained by you.

Thanks!!!

Nidhi

Hello Nidhi,

There should not be any problem with keeping samples in one plate and standard samples in other plate. However, it is prefereable to keep std and test samples of a gene(s) on the sampe plate. This take care of moost of the factors (including background) that can change between plates. You may check the instrument you are using as some of them allow to normalize the fluorescence data across a set of experiments that is spread over several plates. if carefully done and analyzed the approach you are planning should be fine..

bye

Ajay