Predicting the regenerative capacity of conifer somatic embryogenic cultures by metabolomics.

Somatic embryogenesis in gymnosperms is an effective approach to clonally propagating germplasm. However, embryogenic cultures frequently lose regenerative capacity. The interactions between metabolic composition, physiological state, genotype and embryogenic capacity in Pinus taeda (loblolly pine) somatic embryogenic cultures were explored using metabolomics. A stepwise modelling procedure, using the Bayesian information criterion, generated a 47 metabolite predictive model that could explain culture productivity. The model performed extremely well in cross-validation, achieving a correlation coefficient of 0.98 between actual and predicted mature embryo production. The metabolic composition and structure of the model implied that variation in culture regenerative capacity was closely linked to the physiological transition of cultures from the proliferation phase to the maturation phase of development. The propensity of cultures to advance into this transition appears to relate to nutrient uptake and allocation in vivo, and to be associated with the tolerance and response of cultures to stress, during the proliferation phase.

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

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.