Limitations of ad hoc genotyping in detecting ash dieback tolerance in Fraxinus excelsior

Ash dieback (ADB), caused by the invasive alien fungal pathogen Hymenoscyphus fraxineus, is an emerging disease that poses major threats to the survival of common ash (Fraxinus excelsior) in Europe. Here, we report on a field trial aiming at the identification of ADB tolerant genotypes while encompassing the genetic diversity of common ash in Austria. Over 35,000 progenies from more than 600 putative tolerant mother trees were assessed for ADB symptoms over a period of three years. One tolerant and one susceptible progeny from a subset of the mother tree range (570 trees) were genotyped using the 4TREE array, a genotyping tool developed specifically to screen common ash provenances for their tolerance to ash dieback. We aimed to (1) better characterize the genetic structure of common ash in Austria, (2) identify hybrids between common ash and F. angustifolia (narrow-leaved ash), (3) detect genetic loci associated with tolerance to ADB, and (4) identify genetic variation associated with abiotic factors such as temperature and precipitation influencing the severity of ADB. We identify ash individuals from Eastern Austria matching putative hybrids with F. angustifolia showing varying degrees of F. angustifolia ancestry in structure analyses. The non-hybrid gene pool is characterized by shallow genetic structure following a west to east geographic pattern. In contrast to our expectations, genotype-damage association analyses overall fail to detect SNPs associated with tolerance to ADB. Our findings underscore that the polygenic architecture governing tolerance and the rapid decay of genomic linkage disequilibrium (LD) (within approximately 10 kb) significantly limit the ability to identify association outliers using the 4TREE SNP array. This highlights the constrained utility of chip genotyping approaches for this specific purpose. In contrast, the array proves successful in detecting hybrids between common ash and narrow-leaved ash, as well as outlier SNPs associated with abiotic predictors (such as annual precipitation and temperature) known to influence the severity of ADB damage.