Comparative Gene Expression Analysis Reveals Mechanism of Pinus contorta Response to the Fungal Pathogen Dothistroma septosporum.

Many conifers have distributions that span wide ranges in both biotic and abiotic conditions, but the basis of response to biotic stress has received much less attention than response to abiotic stress. In this study, we investigated the gene expression response of lodgepole pine (Pinus contorta) to attack by the fungal pathogen Dothistroma septosporum, which causes Dothistroma needle blight, a disease that has caused severe climate-related outbreaks in northwestern British Columbia. We inoculated tolerant and susceptible pines with two D. septosporum isolates and analyzed the differentially expressed genes (DEGs), differential exon usage, and coexpressed gene modules using RNA-sequencing data. We found a rapid and strong transcriptomic response in tolerant lodgepole pine samples inoculated with one D. septosporum isolate, and a late and weak response in susceptible samples inoculated with another isolate. We mapped 43 of the DEG- or gene module-identified genes to the reference plant-pathogen interaction pathway deposited in the Kyoto Encyclopedia of Genes and Genomes database. These genes are present in PAMP-triggered and effector-triggered immunity pathways. Genes comprising pathways and gene modules had signatures of strong selective constraint, while the highly expressed genes in tolerant samples appear to have been favored by selection to counterattack the pathogen. We identified candidate resistance genes that may respond to D. septosporum effectors. Taken together, our results show that gene expression response to D. septosporum infection in lodgepole pine varies both among tree genotypes and pathogen strains and involves both known candidate genes and a number of genes with previously unknown functions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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.