In fact parallel control will reveal best results as output as compared to fixed one

Prof. Singh made a good point. In addition, what kind of comparisons make more sense to you?

Regards

Thanks for the comments. Due to the limited funding and time constraint, it's not feasible for me to repeat the whole experiment. Any suggestions on how should I perform the DE analysis using these data? My aim is to discover DEGs expressed in unstressed, mild and serious stressed tissues and also comparison between mild and serious stages.

I would do a pairwise DEG comparison between day 0 against mild treated and day 0 against severely treated samples. The two lists of DE transcripts are ones compared your control. DE transcripts of untreated samples is a bit confusing, you would need to elaborate what you mean by unstressed differentially expressed genes..

Another way, that would probably be more appropriate for your experimental design, is to do a time-course DE analysis and compare all three time-points at once. DESeq2 and (I believe) EdgeR both support time-course DE analysis.

Thanks for the suggestion, Noor. At first, I do plan to do a pairwise DEG comparison like what you suggested. However, my supervisor committees were questioning about the validity of the data since there is no parallel control for mild and severely stressed samples. The identified DEGs might due to development or environment factor because the plants were stressed for a month long (severe stage).

Noted. I will try to do a time-course DE analysis using DESeq2. Thank you so much.

Evelyn, your committee has a very valid point, you don't know if the DEGs are due to non-target environmental or developmental factors or the drought stress treatment you imposed.

Depending on how many levels/factors that you are comparing you may be able to tell if the variance (significance of DEGs) are due to time or another factor (i.e. other genotypes screened, physiological data taken in parallel ect.). For example, if you took W.U.E. or stomatal conductance or any other quantitative trait you may have measured during your trial and your DEG time-course analysis found significant transcript abundances was due to W.U.E over time then you know that those genes are probably due to your drought treatment.

Also you would not be the only scientist that has published time-course studies where there isn't a control for every time-point. Thats why validation with qPCR or other methods are usually necessary to publish this type of time-course. Hope this helps!

Thank you very much Noor for your valuable comments. I will incorporate them soon.