Fully funded PhD position available

Sleep is a behavioural quiescence widely observed in the animal kingdom. Evidence indicates that daily light and visual stimuli contribute to sleep pressure; our lab is interested in identifying the elusive molecular and neural basis of such vision-driven sleep. We have identified various genetic components in the light/vision-driven sleep in the fruit fly Drosophila melanogaster. Circuit-based manipulation also indicates parallel neurogenetic pathways linking the visual system and the known sleep homeostatic centre in the fly brain. This PhD project, therefore, aims to combine the latest techniques in connectomics and Drosophila sleep to map out these neural pathways in the fly brain. The student will conduct this exciting project through the following three objectives.

1)Identifying sleep-controlling genetic network: By apply bulk-RNAseq, we will identify common differentially expressed genes (DEGs) in sleep altering visual mutants. In collaboration with Feuda lab, we will then map these DEGs onto scRNA-Seq data (2) to identify the commonly affected neural clusters.

2)Identification of neural connection of vision-sleep pathway: Working with Dr Nils Reinhart, we will use the fly brain connectome (3) to digitally construct neural connection of vision-sleep pathway and examine its overlaps with the DEGs enriched neural clusters. The finding will be confirmed experimentally by confocal brain imaging using customised DEGs-based reporter (2).

3)Verification of the sleep modifying effect of DEGs and associated cell clusters: upon generation of the gene/neural cluster list, automatic high throughput sleep monitor system will be used to test if reduction of these genes modifies the sleep phenotype. The reduction will be implemented in all neurons as well as in the neural clusters identified.

Techniques that will be undertaken during the project

Drosophila Genetics, behaviour assay, in silico brain imaging, Bioinformatics on

scRNA-Seq and Connectome, immuno-confocal brain imaging. 

References:

(1). PMID: 30865587 (2). PMID: 37523539 (3).PMID: 39638801

Application procedure see: 

https://le.ac.uk/study/research-degrees/funded-opportunities/bbsrc-mibtp

contact Ko-Fan Chen directly for more information