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Constructive connectomics: How neuronal axons get from here to there using gene-expression maps derived from their family trees

Kerstjens, Stan; Michel, Gabriela; Douglas, Rodney J (2022). Constructive connectomics: How neuronal axons get from here to there using gene-expression maps derived from their family trees. PLoS Computational Biology, 18(8):e1010382.

Abstract

During brain development, billions of axons must navigate over multiple spatial scales to reach specific neuronal targets, and so build the processing circuits that generate the intelligent behavior of animals. However, the limited information capacity of the zygotic genome puts a strong constraint on how, and which, axonal routes can be encoded. We propose and validate a mechanism of development that can provide an efficient encoding of this global wiring task. The key principle, confirmed through simulation, is that basic constraints on mitoses of neural stem cells—that mitotic daughters have similar gene expression to their parent and do not stray far from one another—induce a global hierarchical map of nested regions, each marked by the expression profile of its common progenitor population. Thus, a traversal of the lineal hierarchy generates a systematic sequence of expression profiles that traces a staged route, which growth cones can follow to their remote targets. We have analyzed gene expression data of developing and adult mouse brains published by the Allen Institute for Brain Science, and found them consistent with our simulations: gene expression indeed partitions the brain into a global spatial hierarchy of nested contiguous regions that is stable at least from embryonic day 11.5 to postnatal day 56. We use this experimental data to demonstrate that our axonal guidance algorithm is able to robustly extend arbors over long distances to specific targets, and that these connections result in a qualitatively plausible connectome. We conclude that, paradoxically, cell division may be the key to uniting the neurons of the brain.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Modeling and Simulation
Physical Sciences > Ecology
Life Sciences > Molecular Biology
Life Sciences > Genetics
Life Sciences > Cellular and Molecular Neuroscience
Physical Sciences > Computational Theory and Mathematics
Uncontrolled Keywords:Computational Theory and Mathematics, Cellular and Molecular Neuroscience, Genetics, Molecular Biology, Ecology, Modeling and Simulation, Ecology, Evolution, Behavior and Systematics
Language:English
Date:25 August 2022
Deposited On:26 Feb 2023 10:03
Last Modified:29 Dec 2024 02:36
Publisher:Public Library of Science (PLoS)
ISSN:1553-734X
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1371/journal.pcbi.1010382
PubMed ID:36006873
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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