ArticleScientific data2017
Ash leaf metabolomes reveal differences between trees tolerant and susceptible to ash dieback disease.
Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Early-Stage Growth Restriction ofMicroorganisms · 2026Article
- Constitutive Metabolite Profiling of European and Asian Fraxinus with Varying Susceptibility to Ash Dieback.Journal of chemical ecology · 2026Article
- A recent ash dieback infection neither affects emerald ash borer performance nor triggers a substantial systemic phytochemical defense response in European ash.Journal of pest science · 2026Article
- Article
- Studying tree response to biotic stress using a multi-disciplinary approach: The pine pitch canker case study.Frontiers in plant science · 2022Review
- Diversity of secoiridoid glycosides in leaves of UK and Danish ash provide new insight for ash dieback management.Scientific reports · 2020Article
- Transcriptional responses in developing lesions of European common ash (Fraxinus excelsior) reveal genes responding to infection by Hymenoscyphus fraxineus.BMC plant biology · 2020Article
- The Relationship between Fungal Diversity and Invasibility of a Foliar Niche-The Case of Ash Dieback.Journal of fungi (Basel, Switzerland) · 2020Article
- Analytical Methods for Detection of Plant Metabolomes Changes in Response to Biotic and Abiotic Stresses.International journal of molecular sciences · 2019Review
- The Road to Resistance in Forest Trees.Frontiers in plant science · 2019Review
- A Metabolomic and HPLC-MS/MS Analysis of the Foliar Phenolics, Flavonoids and Coumarins of theMolecules (Basel, Switzerland) · 2018Article
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Authors and funding
11 authors.
Funding
Abstract
European common ash, Fraxinus excelsior, is currently threatened by Ash dieback (ADB) caused by the fungus, Hymenoscyphus fraxineus. To detect and identify metabolites that may be products of pathways important in contributing to resistance against H. fraxineus, we performed untargeted metabolomic profiling on leaves from five high-susceptibility and five low-susceptibility F. excelsior individuals identified during Danish field trials. We describe in this study, two datasets. The first is untargeted LC-MS metabolomics raw data from ash leaves with high-susceptibility and low-susceptibility to ADB in positive and negative mode. These data allow the application of peak picking, alignment, gap-filling and retention-time correlation analyses to be performed in alternative ways. The second, a processed dataset containing abundances of aligned features across all samples enables further mining of the data. Here we illustrate the utility of this dataset which has previously been used to identify putative iridoid glycosides, well known anti-herbivory terpenoid derivatives, and show differential abundance in tolerant and susceptible ash samples.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.