Breaking the wall of silence of trees Mining metabolomics to describe hybridization and predict performance in the Populus – Sphaerulina musiva pathosystem

• Author / Creator

  Najar, Ahmed

• Stem canker diseases in poplars caused by the fungal pathogen Sphaerulina musiva Peck. remain some of the least understood forest diseases despite causing considerable damage, particularly in hybrid poplar plantations. S. musiva is endemic to eastern Canada in provinces including the Maritimes, Quebec, and Ontario. Although these provinces contain poplar species such as Populus deltoides (Bartr.) Marsh and P. balsamifera L., they are purported to be resistant to the Septoria canker in their eastern range. The Northwestern range (Alberta and British Columbia) mainly home to P. balsamifera and P. trichocarpa Torr. and Gray., the pathogen is found sporadically in shelterbelts, nurseries, and plantations. Anthropogenic crosses among native species of poplars in North America or with exotic species have been undertaken to produce clones with ‘hybrid vigour’ which combine high growth rates with ease of propagation and disease resistance. While vigour of hybrid trees can be modeled and predicted, it is still challenging to predict disease performance in anthropogenic crosses. In the present work metabolic phenotyping was successfully used as a way of predicting performance in various cross types in response to S. musiva. In its native range, P. balsamifera in Alberta has shown high susceptibility to stem canker, unlike its eastern counterpart. Selected genotypes with variable introgression levels with P. trichocarpa and covering the spectrum from P. trichocarpa to P. balsamifera were inoculated with a fungal spray mixture of S. musiva and their phenomics measured both visually (infection estimates) and phytochemically. Susceptibility in P. balsamifera was linked to two parameters: (1) the level of admixture with P. trichocarpa; and (2) their evolutionary history. Metabolic phenotyping identified metabolites involved in the genotypic responses to S. musiva and other metabolites describe hybridization between different species. Using genetic characterization along with phenomic data provides predictive tools to inform tree breeding programs, shape management decisions, and sheds light on the poorly understood Populus – S. musiva pathosystem.

• Subjects / Keywords

  • Benzoic acid derivatives
  • Metabolomics
  • Machine learning
  • Sphaerulina musiva
  • Populus

• Graduation date

  Fall 2017

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3F47H765

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.