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Q-PCR in microarray data validation - the consistency of the two kinds of data (Apr/30/2008 )

I finished about 110 expriments of Q-PCR for microarray data validation. The microarray data (ratio=treat/control) was between 2-3. And my Q-PCR data had not good consistency with the microarray data. There was no correlation between the two kinds of data.

I thought the main reason was that the microarray data did not have a big change. So it was very difficult to detect the gene expression change by Q-PCR.

I need your any advise. Do you think my reason is acceptable?

Thank you very much!

-sunnycougar-

Hi,

no, I don't think that this is an explanation.
The experience is rather, that qRT-PCR is more sensitve than microarray and microarray results rather underestimate actual changes in gene expression.
However, I am not sure what you mean by the ratio of treatment and control is 2-3; could you explain that a bit more - what kind of microarray did you perform?
In the meantime many people have the opinion that certain microarray platforms don't even need any further validation because they perform very accurate. People might even run into trouble regarding the validation due to the RT-PCR and not because their microarray results. In my hands, I was trying to do a validation with qRT-PCR , which looked really weird in the first shot, however than we realised that the primer design might have been problematic and indeed by getting new primers (more 3' end of the transcript) gave good validation.

Well, I don't know what is the case with your data, maybe you can provide more details?

Cheers

-Bomber-

Thank you, Bomber!
It seemed that I did not describe my question clearly. I am try again now.
The microarray I used in my expriment is cDNA microarray, which included two different probes which were marked by Cy3 and Cy5. The RNA from control material was marked by Cy3, and the RNA from treated material was marked by Cy5. At last, we can calculate every gene's expression change after a treatment in the microarray. The value could be a ratio of Cy5/Cy3. I chose some genes whose ratio was between 2 and 3 and did Real Time RT-PCR.
This is the list of the comparison my microarray data and q-pcr data. The two kinds of data both were change to log2 Ratio. The two kinds of data did not have a good consistency.
gene name log2q-pcr log2microarray
1 0.7499285 1.249112029
2 1.7217975 1.42438873
3 -2.86736 1.955151271
4 1.3685495 1.88545653
5 1.242764 1.919889301
6 -0.2926855 1.459066001
7 -0.2277845 1.839907101
8 0.318496 1.436780115
9 2.916016 1.309565173
10 2.2759585 1.105204791
11 2.723563 1.204778564
12 2.5005285 1.225522545
13 0.7021205 1.424103371
14 1.398424 1.34353522
15 6.5231575 1.537154045
16 2.191803 1.204289671
17 3.1475955 1.384053091
18 -0.0853065 1.569243697
19 0.563935 1.522348885
20 -0.27723375 1.444902373
21 3.0688365 2.517266472
22 0.5568515 1.491719901
23 0.477264 1.43074959
24 -0.5022315 1.698106595
25 -2.422176 2.300318891
26 0.161479 1.195473829
27 0.893623 1.665677193

-sunnycougar-