Unfortunately, there is no way to draw conclusions about differential expression unless there are biological replicates. By pooling samples as described, the 'n' has effectively been reduced to one. There is no way to know whether any given result is associated with the experimental variable or technical variations in the pooling procedure, an outlier sample, etc. The experiment can be best used to show that you can or cannot detect a given transcript, or as the basis for a follow-up experiment with biological replicates.

Unfortunately, there is no way to draw conclusions about differential expression unless there are biological replicates. By pooling samples as described, the 'n' has effectively been reduced to one. There is no way to know whether any given result is associated with the experimental variable or technical variations in the pooling procedure, an outlier sample, etc. The experiment can be best used to show that you can or cannot detect a given transcript, or as the basis for a follow-up experiment with biological replicates.

Pooling more than one animal for each sample will minimize the effects of biological variation between individuals. I did this recently for a microarray experiment. However, Kenneth is right that this does not mean you have an n3 simply by pooling three. You would need at least 3x3 controls and 3x3 tests.

This paper describes the common practice of pooling, which is often done due to low RNA yields:

Kendziorski, C., et al. "On the utility of pooling biological samples in microarray experiments." Proceedings of the National Academy of Sciences of the United States of America 102.12 (2005): 4252-4257.

It is clear that, after you pooled equal amount of tissues from three different animals in each time point, the qPCR data you got for each time point has to be considered as " n = 1" instead of "n=3", although the number you got could represent the average of these three animals theoratically. It seems to me you need to repeat the same exp and collect the tissue from each animal separately and process them separately from RNA isolation and all the way to qPCR data, this way you will have n =3 to do statistical analysis correctly.

I agree with Kenneth Witwer. You can't used pooled samples to draw conclusions about differential expression.

Agree with Kenneth point, there is no statistical support to draw the conclusion of differential expressed genes from pooled sample although there are some publications using pooled samples. However, it may give some indications of likely gene expression change you can follow up with other techniques like qPCR with individual sample.

It was actually a strange idea to pool when you finally made three measurements anyway. Measuring each individual sample one provides considerably more useful information than measuring a pool of 3 three times.

I agree with Kenneth Witwer and the peers here above that you can not pool samples and afterwards draw conclusions about differential expression. Measuring a pool three times is just checking the accuracy of your measuring technique. What about if everything you revealed came from only one animal? And what about biological variations? Is this a known or previously unknown expression? Especially important and in fact completely wrong to pool if you are discovering previously unknown expression. In that case you must have minimally 3 but preferebly n >3 individuals or animals.

My apologies for not replying earlier, but I do have a question. You are asking the community to find reasons to "justify" why you pooled samples. My question is "Why did YOU pool them?". What I mean is that at some point, you must have had a reason to pool the samples. Perhaps it was a very good reason. Perhaps you just didn't think about it. Regardless, I believe that the only answer you need to provide you colleague is the "truth". Perhaps this means that you will have to repeat the experiment to obtain statistically valid results. Perhaps it may be easier to simply say that the results you have currently are consistent with your hypothesis, but not statistically significant. I guess I'm simply saying that there are alternatives to trying to find reasons "after the fact" as to why you may have done something.