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  • Most recent tools for circadian gene expression analysis (in plants)

    Hello everyone,

    I'm going to work on a project involving circadian gene expression analysis in the next months, and I'm looking for the best and most advanced/recent tools to perform this. I am particularly interested in telling apart genes following a circadian cycle from the ones which don't, in a statistically significant way, in a given condition.

    More specifically, in the experimental design, we chose a subset of genes (about 100) involved in a biological pathway we are going to study (in plants). We are going to compare their expression levels in plants after a period (T1) exposed to continuous light (LL), in comparison to other plants exposed to light in controlled conditions, simulating real Spring ones (LD). (T1 LL vs T1 vs LD). Samples are taken at 4 different times of the day (at dawn, and after 6, 12 and 18 hours).

    We also have a second point T2 only for LL, since we assume T1 LD and T2 LD are similar we are not going to analyse those samples. The second point T2 LL is meant to confirm some genes are not influenced by light exposure because their levels keep variating periodically, while the ones influenced by it after two months in continuous light are expected to flatten. And, indeed, for some of them this may take longer than T1 to happen.

    Samples from 2 different plants are pooled together and analyzed, with 3 different technical replicates at the time of creating libraries for gene expression sequencing.

    What R script/software/tool would you use to perform such kind of analysis? I'd like to use R if possible. Do you have any experience here? I've read a lot online but still can't make a choice. I don't think I need a specific tool for plants, also more generally intended ones may work.

    Thank you in advance!

  • #2
    Hi,
    I actually did my PhD on circadian cycle (but on cyanobacteria).
    I wrote some Rscripts by this time to calculate the period and phase of the circadian gene expression.
    To be efficient, I had to take timepoints at least every 3h (2h was better) for several days, so I'm afraid your design is not the best...

    Comment


    • #3
      Hmm...

      You got a point there, but I'm working on plants, so maybe the speed gene expression changes isn't exactly the same. Bacteria are more adaptable, grow and replicate far quicker, and I can expect the levels of their transcripts to fluctuate quicker as a consequence than they would do in a more complex organism.
      In most time point experiments involving plants, tissues are sampled 4 or 6 times a day.

      You said you wrote the scripts yourselves, but did you start from premade ones? (Like the old COSOPTs not in use anymore?)
      CircWave and JTK-cycle seem to be popular choices still in use.

      Comment


      • #4
        Circadian cycle means the fluctuation follow a cycle with a period (around) 24h... and in order to be efficient, it's better to have several periods of measurement...

        I did my own scripts (it was in beginning of 2000' so didn't see anything premade. There were basic scripts which tend to fit a Fourier transformation (sinus) to the gene expression... Since then, I totally changed of topic so I'm not even aware of what was made since!

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