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Uncovering the genetic blueprint of the C. elegans nervous system.
Kovács, István A; Barabási, Dániel L; Barabási, Albert-László.
Afiliação
  • Kovács IA; Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208.
  • Barabási DL; Department of Data and Network Science, Central European University, Budapest 1051, Hungary.
  • Barabási AL; Network Science Institute, Northeastern University, Boston, MA 02115.
Proc Natl Acad Sci U S A ; 117(52): 33570-33577, 2020 12 29.
Article em En | MEDLINE | ID: mdl-33318182
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Caenorhabditis elegans / Sistema Nervoso Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Caenorhabditis elegans / Sistema Nervoso Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article