Systematic annotation of a complete adult male Drosophila nerve cord connectome reveals principles of functional organisation

Nervous systems function as ensembles of neurons communicating via synaptic connections, and a functional understanding of nervous systems requires extensive knowledge of their connectomes. In a companion paper (Takemura et al., 2023), we describe the acquisition of a complete fruit fly nerve cord connectome, the first for an animal that can walk or fly. Here, to efficiently navigate and to appreciate the biological significance of this connectome, we categorise and name nearly all neurons systematically and link them to the experimental literature. We employ a system of hierarchical coarse annotations and group similar neurons across the midline and across segments, then define systematic cell types for sensory neurons, intrinsic neurons, ascending neurons, and non-motor efferent neurons. Stereotyped arrays of neuroblasts generate related neuron populations called hemilineages that repeat across the segments of the nerve cord. We confirm that larval-born neurons from a given hemilineage generally express the same neurotransmitter but find that earlier born neurons often express a different one. We match over 35% of intrinsic, ascending, and non-motor efferent neurons across segments, defining serial sets which were crucial for systematic typing of motor neurons and sensory neurons. We assign a sensory modality to over 5000 sensory neurons, cluster them by connectivity, and identify serially homologous cell types and a layered organisation likely corresponding to peripheral topography. Finally, we present selected examples of sensory circuits predicated on programmatic analysis of a complete VNC connectome. Our annotations are critical for analysing the structure of descending input to the nerve cord and of motor output, both described in a third companion paper (Cheong et al., 2023). These annotations are being released as part of the neuprint.janelia.org and clio.janelia.org web applications and also serve as the basis for programmatic analysis of the connectome through dedicated tools that we describe in this paper.