Modular gene expression in Poplar: a multilayer network approach.
Identifieur interne : 003562 ( Main/Exploration ); précédent : 003561; suivant : 003563Modular gene expression in Poplar: a multilayer network approach.
Auteurs : Andreas Grönlund [Suède] ; Rishikesh P. Bhalerao [Suède] ; Jan Karlsson [Suède]Source :
- The New phytologist [ 1469-8137 ] ; 2009.
Descripteurs français
- KwdFr :
- Algorithmes (MeSH), Analyse de profil d'expression de gènes (MeSH), Biologie informatique (MeSH), Cartographie d'interactions entre protéines (MeSH), Gènes dupliqués (MeSH), Populus (génétique), Régulation de l'expression des gènes végétaux (MeSH), Séquençage par oligonucléotides en batterie (méthodes), Transduction du signal (MeSH).
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
By applying a multilayer network approach to an extensive set of Poplar microarray data, a genome-wide coexpression network has been detected and explored. Multilayer networks were generated from minimum spanning trees (MSTs) using Kruskal's algorithm from random jack-knife resamplings of half of the full data set. The final network is obtained from the union of all the generated MSTs. The gene expression correlations display a highly clustered topology, which is more pronounced when introducing links appearing in relatively few of the generated MSTs. The network also reveals a modular architecture, reflecting functional groups with relatively frequent gene-to-gene communication. Furthermore, the observed modular structure overlaps with different gene activities in different tissues, and closely related tissues show similar over- and/or under-expression patterns at the modular scale. It is shown that including links that appear in a few of the generated MSTs increases the information quality of the network. In other words, a link may be 'weak' because it reflects rare signaling events rather than merely a signal weakened by noise. The method allows, from comparisons of random 'null networks', tuning to maximize the information obtainable.
DOI: 10.1111/j.1469-8137.2008.02668.x
PubMed: 19121030
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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<front><div type="abstract" xml:lang="en">By applying a multilayer network approach to an extensive set of Poplar microarray data, a genome-wide coexpression network has been detected and explored. Multilayer networks were generated from minimum spanning trees (MSTs) using Kruskal's algorithm from random jack-knife resamplings of half of the full data set. The final network is obtained from the union of all the generated MSTs. The gene expression correlations display a highly clustered topology, which is more pronounced when introducing links appearing in relatively few of the generated MSTs. The network also reveals a modular architecture, reflecting functional groups with relatively frequent gene-to-gene communication. Furthermore, the observed modular structure overlaps with different gene activities in different tissues, and closely related tissues show similar over- and/or under-expression patterns at the modular scale. It is shown that including links that appear in a few of the generated MSTs increases the information quality of the network. In other words, a link may be 'weak' because it reflects rare signaling events rather than merely a signal weakened by noise. The method allows, from comparisons of random 'null networks', tuning to maximize the information obtainable.</div>
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