I now switched the sign of the Optomotor Asymmetry Index in flies that were punished on producing right-turning torque, such that weaker punished torque shows up as a positive index. After that was done, I plotted the correlation between the optomotor index and the preference index:

I had to get rid of eight flies where the optomotor response was already asymmetric before the training started, so now I only have 33 flies. But with these flies, there is no correlation before training and a very significant correlation after training.

Any suggestions about appearance of the graphs?

Would it be useful to plot optomotor and performance indices as raincloudplots next to the regressions?

This would be the complete figure:

The results of comparing optomotor responses after self-learning remain solid. There still is a small asymmetry between the left/right groups, but nothing dramatic:

With the focus on dopaminergic neurons, I conducted two experiments with two different driver lines to see how the naive gustatory behavior in Drosophila larvae is affected.

The first cross I tested was R58E02-Gal4 x UAS-ChR2-XXL, which gave me the following results:

As seen in the figures, there was no effect under blue light.

For the second experiment I crossed TH-Gal4 x UAS-ChR2-XXL with these results:

With this experiment, there was an effect on gustatory behavior as there is a clear significant difference between the experimental group and the control group.

DNA Assembly in a 1:2 ratio of vector to insert with gRNAs of rsh and rut (Q5 and template concentration: 640 pg/µl) and 100ng of pCFD6 BbsI AP (using QuickCIP). Heat-shock (hs) transformation into E. coli (DH5α competent) with 10 µl Assembly Reaction and 100 µl cells.

For Crtl, pCFD6 BbsI AP was wrongly used.

DNA Assembly in a 1:2 ratio of vector to insert with the gRNAs of rsh and rut (Q5 and template concentration: 640 pg/µl) and 100ng of pCFD6 BbsI AP (using FastAP and 2 extraction steps). Heat-shock (hs) transformation into E. coli (DH5α competent) with 10 µl Assembly Reaction and 100 µl cells.

For Crtl, pCFD6 BbsI AP was used in reaction.

After dissecting brains from the GAL4 driver line SS56699 with GFP staining and finding no fluorescence, I dissected them again and the immunohistochemical staining showed fluorescence. To check that the correct neurons were stained, I compared the images with the image in the paper by Hulse et al (2021; https://doi.org/10.7554/eLife.66039) . The three PPL1 dopaminergic dorsal fan-shaped body tangential neurons per hemisphere are stained, but there are some additional unidentified neurons (presumably PPM1 neruons) visible.

Hulse, B. K., Haberkern, H., Franconville, R., Turner-Evans, D., Takemura, S.-y., Wolff, T., Noorman, M., Dreher, M., Dan, C., Parekh, R., Hermundstad, A. M., Rubin, G. M., & Jayaraman, V. (2021). A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection. eLife, 10, e66039. https://doi.org/10.7554/eLife.66039

The offspring of my first experimental fly cohort finally hatched! Below you find a few first pre-tests I ran last week :)

First, here are the results of a quick test to see if the offspring shows a preference for the parentally trained side after the first training period:

After that I played around with the laser a little bit to find the learning threshhold. I set the laser on 2,6V but the results I got look a bit weird:

-> untrained wtb flies

-> offspring of trained wtb flies

I´m optimistic however there is still a lot of work to do…

The following plots show the results after I increased the salt concentration from 1,5M to 2,5M. It shows that the difference between the control groups and experimental group are not significant anymore.

Via gDNA analysis and PCR was the specific area of the rsh gene extracted and amplified where the nucleotide substitution: C to T (Folkers et al., 2006) should be for the rsh¹ mutation. The amplicon was Sanger sequenced which proved the nucleotide substitution.

Despite very warm weather, some flies did fly, even though the learning performance of the control flies was really poor. At least for now, it looks like all stocks are learning and that rut and rsh flies learn at least equally well as the Berlin flies. I’ve also managed to fix the positive preference problem: