Abstract
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.
Original language | English (US) |
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Pages (from-to) | 33570-33577 |
Number of pages | 8 |
Journal | Proceedings of the National Academy of Sciences of the United States of America |
Volume | 117 |
Issue number | 52 |
DOIs | |
State | Published - Dec 2020 |
Funding
ACKNOWLEDGMENTS. We thank Emma Towlson and Oliver Hobert for helpful discussions and data sharing, as well as Alice Grishchenko for help in designing the figures. This work was supported by the European Union’s Horizon 2020 research and innovation program under Grant Agreement 810115 - Dynamics and Structure of Networks (DYNASNET). D.L.B. was supported by NIH National Institute of General Medical Sciences Grant T32 GM008313. A.-L.B. was supported by the NSF Award 1734821.
Keywords
- C. elegans
- Connectome
- Networks
- Neuroscience
ASJC Scopus subject areas
- General