Novel ways of managing tree crop fungal diseases – using precision diagnostic technologies to tailor disease management strategies (Ref: CTP_FCR_2018_1)

For major foliar and trunk pathogens of apple (Venturia inaequalis [scab], Podosphaera leutricha [powdery mildew] and Neonectria ditissima [European apple canker]) there is a wealth of evidence, both for the host relating to major gene resistances, and for the pathogen about population-level variation and structure that is associated with host development. However, this information is currently not applied in the field to inform deployment. Rapid single molecule sequencing of DNA and RNA is now possible using Oxford Nanopore Technology (ONT). The aim of this project is to develop this technology for the rapid in-field monitoring of pathogen populations, in order to inform management strategies. The PhD project fully meets the BBSRC objectives of better countering of diseases of crops and greater resilience of crops to abiotic stresses.

NIAB EMR are early access members of the ONT MinION and VolTRAX programmes and have been working for over 14 months on applications for these technologies in the horticultural industry. Currently it is being applied to bacterial and fungal genomes, resulting in complete assembled genomes for many major horticultural pathogens. Bioinformatics pipelines are now well established and significant investment in hardware has been made to ensure that planned future developments in the technology do not impede progress.

Approaches and workpackges

Workpackage 1– Assay development

Read-until sequencing (Loose et.al. 2016), whereby specific DNA molecules can be selected for sequencing, has been shown to be an important and useful tool for detecting specific DNA molecules within a mixed population. Using available genome sequences for Venturia and Neonectria (10+ unique genome sequences for each pathogen at NIAB EMR), the student will devise a real-time sequencing approach that facilitates detection of the pathogen at the level of candidate effector genes using ‘read until’ from pathogens sampled from monoculture and mixed orchards. The student will develop a database of sequences in order to facilitate real time lookup of target sequences.

The student will go on to attempt to gather sequence data for Podosphaera using low volume, purified conidia using the 1D rapid run kit for the ONT minion. Direct RNA sequencing in planta using the minion will reveal expressed effectors suitable for targeting in a read-until approach. The student will develop rapid extraction methods of leaf and stem tissues to ensure that the DNA quality is sufficient for use in the ONT system.

Workpackage 2 – Experimental monitoring

Using known host differentials for Venturia and Podosphaera segregating for major gene resistances, pathogen samples will be collected from existing and new experimental plots, subject to natural epidemics of the diseases. Using the method developed in WP1 the read-until system will be tested, to understand whether discrimination of known races of the pathogens can be detected. Pilot experiments will reveal not only whether pathogens can be detected down to the level of race, but for powdery mildew, where the factors controlling race variation are unknown; the method may reveal variation in candidate effectors directly – allowing the determination of race from the causative gene. This is most likely to succeed if direct RNA sequencing in planta is used. Similarly, using Venturia the presence of target-site resistance to fungicides will be also monitored using experimental strains in addition to candidate effectors. For Neonectria, where there is no reported race structure, the diversity of the pathogen will be monitored and based on phylogenetically informative loci, population level parameters, such as diversity and linkage disequilibrium will be calculated to understand the fungal population structure for inferring the level of sexual recombination in the field.

Workpackage 3 – In field monitoring

Based upon the results in WP1 and WP2, the student will visit selected grower sites and conduct a sampling of leaves and stem tissue at two points in the season. A subset of these samples will then be sequenced to report the status of the three pathogens at the grower sites. The student will work to optimise the method for in-field diagnosis using rapid DNA preparation and extraction. Anticipated developments in ONT technology (even now the device can theoretically run on an android phone) may mean that within the lifetime of the project, on-site diagnosis could be carried out (for example using the SmidgION). The student will therefore attempt to ensure that the method is portable. These data will be integrated and a view of site by site and orchard by orchard variability of pathogen populations will be assembled for the first time.

Workpackage 4 – Theoretical reappraisal of disease management strategies

Data from WP3 will be analysed to assess the extent of particular pathogen races (informing future planting decisions), the presence of fungicide resistance traits (affecting IPM) and the level of spatial variability within orchards, indicating how lifecycle (clonal or sexual) affects population-level variation at the molecular level. The information can then be used to assess the appropriateness of current disease management strategies and inform novel ways of managing tree crop fungal diseases.

Anyone interested should send your application (CV, cover letter, personal statement and two names for reference) to [Email Address Removed], citing the project reference.