When science gives you lemons… find out if lemonade exists

Some days, life throws you curve balls. The lights are all red; Sainsbury sell out of orange milk; the weather forecast is clear and then it heaves down. (Seriously though, this is Britain. Who am I kidding? If I leave the house without a raincoat, it’s my own stupid fault).

More frequently – in my case at least – science throws me curve balls. In fact, what am I saying? I can’t even remember the last time science threw me a straight ball.

For the last two days I have been sat sadly staring at this data. There’s a special kind of paralysis that comes upon a PhD student when an experiment might be failing and they’re just not sure: it’s the ‘I won’t know until I’ve finished it… but I don’t want to waste my precious precious samples if I could fix it instead’ sort of feeling. This isn’t really a data set yet, just two qPCR plates. The first one looked a bit funny, but the standard curve just plain didn’t run, so I was planning to discard the plate and run a new replicate. Then the second plate came out looking exactly the same. (The green line is the same samples against a different housekeeping gene).

I am looking at the expression of a gene in the wild type plant, three single deletion lines and a double deletion. (I work with a polyploid, so by crossing and then selfing the deletion lines, multiple deletions can be stacked). I expected that either the plants would show reduced expression (because they are missing a copy of the gene), or that they would be the same as the wild type: because the plant was compensating for the loss.

These are the differences in Ct values between the gene of interest and the housekeeping genes: i.e. how many more cycles did it take for the sample to fluoresce. A value of 3 is more or less equivalent to a ten times difference in expression, so really I guess I was expecting to see a difference between lines of 1 cycle (or about a third). High values mean low expression. Low values mean high expression.

Deletion line 3 is doing what I expect it to: the delta Ct value is higher, because expression of my gene is lower. So far, so good. Expression of Deletion line 2 is static. Okay, so this one is compensating. Also good. The two deletion lines are different: that’s interesting.

Uh… hold on a second. What is deletion line ONE doing? And more to the point, what is the DOUBLE deletion line doing?

*cue freak out*

How on earth can a plant that is missing a copy of a gene then be producing MORE of the transcript associated with that gene?!

For the last day I have sat and pondered. And by pondered I mean I have tried to write an application, I have marked some A-level work, and I have tried to write a chapter for FastBleep Biology that I may never finish at this rate. Today, I cracked. I told my labmates – in a slightly hysterical voice – what my data looked like.

And without batting an eyelid, one of them said “You’ve deleted a regulator.” … I’ve pardon me? “You’ve deleted a regulatory element. Gene expression is no longer being suppressed. In fact if the double deletion is doing the same thing then that sounds even more like the answer.

There’s an answer. Not only is my science not failing dramatically, but there may even be something interesting going on.

Hello science. We meet again.


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