Clonostachys rosea is a mycoparasitic fungus that can control several important plant diseases. Here, we report on the genome sequencing of C. rosea and a comparative genome analysis, in order to resolve the phylogenetic placement of C. rosea and to study the evolution of mycoparasitism as a fungal lifestyle. The genome of C. rosea is estimated to 58.3 Mb, and contains 14,268 predicted genes. A phylogenomic analysis shows that C. rosea clusters as sister taxon to plant pathogenic Fusarium species, with mycoparasitic/saprotrophic Trichoderma species in an ancestral position. A comparative analysis of gene family evolution reveals several distinct differences between the included mycoparasites. Clonostachys rosea contains significantly more ATP-binding cassette (ABC) transporters, polyketide synthases, cytochrome P450 monooxygenases, pectin lyases, glucose-methanol-choline oxidoreductases, and lytic polysaccharide monooxygenases compared with other fungi in the Hypocreales. Interestingly, the increase of ABC transporter gene number in C. rosea is associated with phylogenetic subgroups B (multidrug resistance proteins) and G (pleiotropic drug resistance transporters), whereas an increase in subgroup C (multidrug resistance-associated proteins) is evident in Trichoderma virens. In contrast with mycoparasitic Trichoderma species, C. rosea contains very few chitinases. Expression of six group B and group G ABC transporter genes was induced in C. rosea during exposure to the Fusarium mycotoxin zearalenone, the fungicide Boscalid or metabolites from the biocontrol bacterium Pseudomonas chlororaphis. The data suggest that tolerance toward secondary metabolites is a prominent feature in the biology of C. rosea.

Clonostachys rosea strain IK726 is a mycoparasitic fungus capable of controlling mycotoxin-producing Fusarium species, including F. graminearum and F. culmorum, known to produce Zearalenone (ZEA) and Deoxynivalenol (DON). DON is a type B trichothecene known to interfere with protein synthesis in eukaryotes. ZEA is a estrogenic-mimicing mycotoxin that exhibits antifungal growth. C. rosea produces the enzyme zearalenone hydrolase (ZHD101), which degrades ZEA. However, the molecular basis of resistance to DON in C. rosea is not understood. We have exploited a genome-wide transcriptomic approach to identify genes induced by DON and ZEA in order to investigate the molecular basis of mycotoxin resistance C. rosea.

Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at epidemic levels throughout Europe. Previous studies have found significant genetic variation among genotypes in ash dieback susceptibility and that host phenology, such as autumn yellowing, is correlated with susceptibility of ash trees to H. fraxineus; however, the genomic basis of ash dieback tolerance in F. excelsior requires further investigation. Here, we integrate quantitative genetics based on multiple replicates and genome‐wide association analyses with machine learning to reveal the genetic architecture of ash dieback tolerance and of phenological traits in F. excelsior populations in six European countries (Austria, Denmark, Germany, Ireland, Lithuania, Sweden). Based on phenotypic data of 486 F. excelsior replicated genotypes we observed negative genotypic correlations between crown damage caused by ash dieback and intensity of autumn leaf yellowing within multiple sampling sites. Our results suggest that the examined traits are polygenic and using genomic prediction models, with ranked single nucleotide polymorphisms (SNPs) based on GWAS associations as input, a large proportion of the variation was predicted by unlinked SNPs. Based on 100 unlinked SNPs, we can predict 55% of the variation in disease tolerance among genotypes (as phenotyped in genetic trials), increasing to a maximum of 63% when predicted from 9155 SNPs. In autumn leaf yellowing, 52% of variation is predicted by 100 unlinked SNPs, reaching a peak of 72% using 3740 SNPs. Based on feature permutations within genomic prediction models, a total of eight nonsynonymous SNPs linked to ash dieback crown damage and autumn leaf yellowing (three and five SNPs, respectively) were identified, these were located within genes related to plant defence (pattern triggered immunity, pathogen detection) and phenology (regulation of flowering and seed maturation, auxin transport). We did not find an overlap between genes associated with crown damage level and autumn leaf yellowing. Hence, our results shed light on the difference in the genomic basis of ADB tolerance and autumn leaf yellowing despite these two traits being correlated in quantitative genetic analysis. Overall, our methods show the applicability of genomic prediction models when combined with GWAS to reveal the genomic architecture of polygenic disease tolerance enabling the identification of ash dieback tolerant trees for breeding or conservation purposes.