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Towards systems biology of heterosis

  • We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity—a known phenomenon in the literature.

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Metadaten
Author:Sandra AndorfORCiD, Tanja Gärtner, Matthias Steinfath, Hanna Witucka-Wall, Thomas AltmannORCiD, Dirk Repsilber
URN:urn:nbn:de:kobv:517-opus4-436274
DOI:https://doi.org/10.25932/publishup-43627
ISSN:1866-8372
Parent Title (German):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Subtitle (English):a hypothesis about molecular network structure applied for the Arabidopsis metabolome
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (949)
Document Type:Postprint
Language:English
Date of first Publication:2020/06/08
Year of Completion:2008
Publishing Institution:Universität Potsdam
Release Date:2020/06/08
Tag:biological network; metabolite profile; molecular network; partial correlation; significant edge
Issue:949
Page Number:14
Source:EURASIP Journal on Bioinformatics and Systems Biology 2009 (2008) 147157 DOI: 10.1155/2009/147157
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer Review:Referiert
Publication Way:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, 4.0 International