Abstract
BackgroundWith the expanding ash dieback epidemic that has spread across the European continent, an improved functional understanding of the disease development in afflicted hosts is needed. The study investigated whether differences in necrosis extension between common ash (Fraxinus excelsior) trees with different levels of susceptibility to the fungus Hymenoscyphus fraxineus are associated with, and can be explained by, the differences in gene expression patterns. We inoculated seemingly healthy branches of each of two resistant and susceptible ash genotypes with H. fraxineus grown in a common garden.ResultsTen months after the inoculation, the length of necrosis on the resistant genotypes were shorter than on the susceptible genotypes. RNA sequencing of bark samples collected at the border of necrotic lesions and from healthy tissues distal to the lesion revealed relatively limited differences in gene expression patterns between susceptible and resistant genotypes. At the necrosis front, only 138 transcripts were differentially expressed between the genotype categories while 1082 were differentially expressed in distal, non-symptomatic tissues. Among these differentially expressed genes, several genes in the mevalonate (MVA) and iridoid pathways were found to be co-regulated, possibly indicating increased fluxes through these pathways in response to H. fraxineus.Comparison of transcriptional responses of symptomatic and non-symptomatic ash in a controlled greenhouse experiment revealed a relatively small set of genes that were differentially and concordantly expressed in both studies. This gene-set included the rate-limiting enzyme in the MVA pathway and a number of transcription factors. Furthermore, several of the concordantly expressed candidate genes show significant similarity to genes encoding players in the abscisic acid- or Jasmonate-signalling pathways.ConclusionsA set of candidate genes, concordantly expressed between field and greenhouse experiments, was identified. The candidates are associated with hormone signalling and specialized metabolite biosynthesis pathways indicating the involvement of these pathways in the response of the host to infection by H. fraxineus.
Highlights
With the expanding ash dieback epidemic that has spread across the European continent, an improved functional understanding of the disease development in afflicted hosts is needed
Transcriptional differences between resistant and susceptible genotype categories are less pronounced in symptomatic tissue By comparing expression patterns in non-symptomatic tissues, we found 1082 differentially expressed genes (DEGs) which differed in their expression pattern between resistant and susceptible genotypes
This can be interpreted such that the difference in necrosis extension between trees with different levels of susceptibility is associated with differences in expression patterns in both non-symptomatic and symptomatic tissues, i.e. trees with different levels of resistance show different basal levels of gene expression and possibly different transcriptional responses proximal to the advancing necrosis
Summary
With the expanding ash dieback epidemic that has spread across the European continent, an improved functional understanding of the disease development in afflicted hosts is needed. The study investigated whether differences in necrosis extension between common ash (Fraxinus excelsior) trees with different levels of susceptibility to the fungus Hymenoscyphus fraxineus are associated with, and can be explained by, the differences in gene expression patterns. Metabolite profiling, genome and transcriptome sequencing has contributed understanding of the genetic diversity and level of resistance to H. fraxineus in the European ash population in the wake of the devastating epidemic [6,7,8,9,10]. The understanding of the interaction between common ash and H. fraxineus is still quite limited and this may hamper attempts to control the ash dieback epidemic using genetic selection. The potential to select superior genotypes based on metabolite profiles has been explored [11]
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