FamNet: A Framework to Identify Multiplied Modules Driving Pathway Expansion in Plants
Author(s) -
Colin Ruprecht,
Amelie Mendrinna,
Takayuki Tohge,
Arun Sampathkumar,
Sebastian Klie,
Alisdair R. Fernie,
Zoran Nikoloski,
Staffan Persson,
Marek Mutwil
Publication year - 2016
Publication title -
plant physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.554
H-Index - 312
eISSN - 1532-2548
pISSN - 0032-0889
DOI - 10.1104/pp.15.01281
Subject(s) - biology , computational biology , gene , genome , nicotiana tabacum , identification (biology) , secondary metabolite , organism , r package , computer science , genetics , botany , computational science
Gene duplications generate new genes that can acquire similar but often diversified functions. Recent studies of gene coexpression networks have indicated that, not only genes, but also pathways can be multiplied and diversified to perform related functions in different parts of an organism. Identification of such diversified pathways, or modules, is needed to expand our knowledge of biological processes in plants and to understand how biological functions evolve. However, systematic explorations of modules remain scarce, and no user-friendly platform to identify them exists. We have established a statistical framework to identify modules and show that approximately one-third of the genes of a plant's genome participate in hundreds of multiplied modules. Using this framework as a basis, we implemented a platform that can explore and visualize multiplied modules in coexpression networks of eight plant species. To validate the usefulness of the platform, we identified and functionally characterized pollen- and root-specific cell wall modules that multiplied to confer tip growth in pollen tubes and root hairs, respectively. Furthermore, we identified multiplied modules involved in secondary metabolite synthesis and corroborated them by metabolite profiling of tobacco (Nicotiana tabacum) tissues. The interactive platform, referred to as FamNet, is available at http://www.gene2function.de/famnet.html.
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