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Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

descriptionPublicationkeyboard_double_arrow_right Article , Journal 17 Jan 2017Publisher:Proceedings of the National Academy of SciencesJournal:Proceedings of the National Academy of Sciences, volume 114, pages 1,195-1,200 (issn: 0027-8424, eissn: 1091-6490,

Authors: Lieven Verbeke; Yves Van de Peer; Yves Van de Peer; Eshchar Mizrachi; Marc Van Montagu; Shawn D. Mansfield; Alexander Andrew Myburg; +7 Authors

doi: 10.1073/pnas.1620119114

pmid: 28096391

pmc: PMC5293113

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

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Abstract

Significance Carbon fixation and accumulation as lignocellulosic biomass is of global ecological and industrial importance and most significantly occurs in the form of wood development in trees. Traits of importance in biomass accumulation are highly complex and, aside from environmental factors, are affected by many pathways and thousands of genes. We have applied a network-based data integration method for a systems genetics analysis of genes, processes, and pathways underlying biomass and bioenergy-related traits using segregating Eucalyptus hybrid tree populations. We could link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Such a holistic view of the biology of wood formation will contribute to genetic improvement and engineering of plant biomass.

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University of British Columbia
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Keywords

Eucalyptus, Models, Genetic, Quantitative Trait Loci, Chromosome Mapping, Genes, Plant, Lignin, Wood, Carbon, Cell Wall, Gene Expression Regulation, Plant, Hybridization, Genetic, Gene Regulatory Networks, Biomass, Crosses, Genetic, Metabolic Networks and Pathways, Plant Proteins

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	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	43
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%