Metabolite profiling of Douglas-fir (Pseudotsuga menziesii) field trials reveals strong environmental and weak genetic variation

Andrew R. Robinson, Nicholas K. Ukrainetz, Kyu Young Kang, Shawn D. Mansfield

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

• The primary objective of this study was to assess metabolomics for its capacity to discern biological variation among 10 full-sib families of a Douglas-fir tree breeding population, replicated on two sites. • The differential accumulation of small metabolites in developing xylem was examined through metabolite profiles (139 metabolites common to 181 individual trees) generated by gas chromatography mass spectrometry and a series of statistical analyses that incorporated family, site, and tree growth and quantitative phenotypic wood traits (wood density, microfibril angle, wood chemistry and fiber morphology). • Multivariate discriminant, canonical discriminant and factor analyses and broad-sense heritabilities revealed that metabolic and phenotypic traits alike were strongly related to site, while similar associations relating to genetic (family) structure were weak in comparison. Canonical correlation analysis subsequently identified correlations between specific phenotypic traits (i.e. tree growth, fibre morphology and wood chemistry) and metabolic traits (i.e. carbohydrate and lignin biosynthetic metabolites), demonstrating a coherent relationship between genetics, metabolism, environmental and phenotypic expression in wood-forming tissue. • The association between cambial metabolites and tree phenotype, as revealed by metabolite profiling, demonstrates the value of metabolomics for systems biology approaches to understanding tree growth and secondary cell wall biosynthesis in plants.

Original languageEnglish
Pages (from-to)762-773
Number of pages12
JournalNew Phytologist
Volume174
Issue number4
DOIs
StatePublished - Jun 2007

Keywords

  • Douglas-fir (Pseudotsuga menziesii)
  • Gas chromatography mass spectrometry (GC-MS)
  • Genetics x environment
  • Heritability
  • Metabolite profiling
  • Metabolomics
  • Quantitative phenotypic traits
  • Wood chemistry and density

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