Linking gene expression profiles to firing properties in the Drosophila thermosensory circuit

Abstract: We will use neurons that are part of the Drosophila thermosensory circuit as models to explore the extent to which molecular profiling data obtained through single-cell patch-sequencing can be used to predict a neuron’s firing properties. We will develop new information theory-based data filtering and similarity methods to compare patch-seq and single-cell data and obtain improved estimates of ion channel expression in these neurons. We will then produce anatomically realistic models of thermosensory neurons by using the expression data to populate models of these neurons with candidate ion channels and regulators. Furthermore, we will extend current evolutionary algorithms to incorporate ion expression correlation data to improve fits to in-vivo electrophysiological measurements of each cell type. Our goal is two fold: to determine the extent to which a neuron’s firing properties can be extrapolated from its gene expression profile and to explore how underlying variability in a neuron’s repertoire of components can nevertheless lead to robust firing properties. Overall, we expect that our methods and models will bring clarity regarding the patterns of expression of ion channels, receptors, and signal transduction components that are key determinants of the functional properties of neurons in the thermosensory circuit, point to nodes of the network that may be particularly sensitive to perturbation, and make specific predictions on the effects of such perturbations, eventually directing new experiments that exploit cell-type specific RNAi and genetic mutants.