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Genetic networks encode secrets of their past.
Crawford-Kahrl, Peter; Nerem, Robert R; Cummins, Bree; Gedeon, Tomas.
Afiliação
  • Crawford-Kahrl P; Courant Institute of Mathematical Sciences, New York University, New York, NY, USA.
  • Nerem RR; Institute for Quantum Science and Technology, University of Calgary, Alberta T2N 1N4, Canada.
  • Cummins B; Department of Mathematical Sciences, Montana State University, Bozeman, MT, USA.
  • Gedeon T; Department of Mathematical Sciences, Montana State University, Bozeman, MT, USA.
J Theor Biol ; 541: 111092, 2022 05 21.
Article em En | MEDLINE | ID: mdl-35307408
ABSTRACT
Research shows that gene duplication followed by either repurposing or removal of duplicated genes is an important contributor to evolution of gene and protein interaction networks. We aim to identify which characteristics of a network can arise through this process, and which must have been produced in a different way. To model the network evolution, we postulate vertex duplication and edge deletion as evolutionary operations on graphs. Using the novel concept of an ancestrally distinguished subgraph, we show how features of present-day networks require certain features of their ancestors. In particular, ancestrally distinguished subgraphs cannot be introduced by vertex duplication. Additionally, if vertex duplication and edge deletion are the only evolutionary mechanisms, then a graph's ancestrally distinguished subgraphs must be contained in all of the graph's ancestors. We analyze two experimentally derived genetic networks and show that our results accurately predict lack of large ancestrally distinguished subgraphs, despite this feature being statistically improbable in associated random networks. This observation is consistent with the hypothesis that these networks evolved primarily via vertex duplication. The tools we provide open the door for analyzing ancestral networks using current networks. Our results apply to edge-labeled (e.g. signed) graphs which are either undirected or directed.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Reguladoras de Genes / Mapas de Interação de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Reguladoras de Genes / Mapas de Interação de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article