Uncovering the genetic blueprint of the C. elegans nervous system

Significance A fundamental question of neuroscience is how the brain wires itself. Here, we propose a modeling framework that explains how cellular connectivity emerges from neuronal identity, allowing us to offer experimentally falsifiable predictions on the genetic encoding of the connectome. The rapid advances in brain science require quantitative frameworks to integrate genetic and connectome information. The proposed model responds to this need, helping us unveil the genetically driven mechanisms that govern the formation of individual links in the brain. Despite rapid advances in connectome mapping and neuronal genetics, we lack theoretical and computational tools to unveil, in an experimentally testable fashion, the genetic mechanisms that govern neuronal wiring. Here we introduce a computational framework to link the adjacency matrix of a connectome to the expression patterns of its neurons, helping us uncover a set of genetic rules that govern the interactions between neurons in contact. The method incorporates the biological realities of the system, accounting for noise from data collection limitations, as well as spatial restrictions. The resulting methodology allows us to infer a network of 19 innexin interactions that govern the formation of gap junctions in Caenorhabditis elegans, five of which are already supported by experimental data. As advances in single-cell gene expression profiling increase the accuracy and the coverage of the data, the developed framework will allow researchers to systematically infer experimentally testable connection rules, offering mechanistic predictions for synapse and gap junction formation.