About: Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions     Goto   Sponge   NotDistinct   Permalink

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  • High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P. trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28 831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Trans
  • High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P. trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28 831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Trans (en)
Title
  • Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions
  • Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions (en)
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  • Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions
  • Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions (en)
skos:notation
  • RIV/60460709:41320/13:61286!RIV14-MSM-41320___
http://linked.open...avai/riv/aktivita
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  • 91424
http://linked.open...ai/riv/idVysledku
  • RIV/60460709:41320/13:61286
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  • network analysis, phenotype prediction, Populus trichocarpa, single nucleotide polymorphisms (SNP), transcriptomics, wood chemistry, wood density, wood properties (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • GB - Spojené království Velké Británie a Severního Irska
http://linked.open...ontrolniKodProRIV
  • [2D4ABC27206B]
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  • New Phytologist
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http://linked.open...UplatneniVysledku
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  • 200
http://linked.open...iv/tvurceVysledku
  • Klápště, Jaroslav
  • El-Kassaby, Yousry
  • Douglas, Carl
  • Mansfield, Shawn
  • Ehlting, Juergen
  • Friedmann, Michael
  • Hannemann, Jan
  • Porth, Ilga
  • Skyba, Oleksandr
http://linked.open...ain/vavai/riv/wos
  • 000325555400016
issn
  • 0028-646X
number of pages
http://localhost/t...ganizacniJednotka
  • 41320
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