Comparative single-cell transcriptomics of complete insect nervous systems

Abstract

SummaryMolecular profiles of neurons influence information processing, but bridging the gap between genes, circuits, and behavior has been very difficult. Furthermore, the behavioral state of an animal continuously changes across development and as a result of sensory experience. How behavioral state influences molecular cell state is poorly understood. Here we present a complete atlas of the Drosophila larval central nervous system composed of over 200,000 single cells across four developmental stages. We develop polyseq, a python package, to perform cell-type analyses. We use single-molecule RNA-FISH to validate our scRNAseq findings. To investigate how internal state affects cell state, we optogentically altered internal state with high-throughput behavior protocols designed to mimic wasp sting and over activation of the memory system. We found nervous system-wide and neuron-specific gene expression changes. This resource is valuable for developmental biology and neuroscience, and it advances our understanding of how genes, neurons, and circuits generate behavior.

Toward a Consensus in the Repertoire of Hemocytes Identified in Drosophila

“…Two scRNAseq datasets on the larval brain from 1st instar to 3rd instar larvae (Brunet Avalos et al, 2019;Cocanougher et al, 2019) report the presence of hemocytes ( Supplementary Figure S3D), in line with the hemocytes observed in close contact with this tissue ( Figure 4B). The comparison of the pseudo-transcriptomes of hemocytes from the 1st instar brain and of Cattenoz et al subgroups highlights the highest correlation with the PLprolif and PL-Inos subgroups (Supplementary Figure S3E).…”

Useful road maps: studying Drosophila larva’s central nervous system with the help of connectomics

“…[ 8 , 11 , 16 , 18 , 52 ]). In parallel, whole-brain RNAseq reveals genes expressed in individual neurons [ 74 , 75 ] that might be essential for these computations. The comparatively small size enables rapid reconstruction of connectomes from multiple individuals ( e.g.…”

Parallel evolution of a splicing program controlling neuronal excitability in flies and mammals

“…Figure 7A-C), likely reflecting the higher proportion of immature neurons in L3 CNS when compared to L1 CNS 40 . Next, we profiled eMIC-dependent exon expression across cell types in neural tissues, using a recent RNA-seq dataset of cell types in the fly optic lobe 70, 71 as well as other datasets of sorted neurons 72 (Figure 6D, Supp. Figure 7D-H and Table S1).…”