Powdery mildew resistance in strawberry fruit

Reference: CTP_FCR_2019_7

This student is to be registered with the University of Reading

Lead academic supervisors: Dr Helen Cockerton and Dr Bo Li, NIAB EMR
University supervisor: Prof Jim Dumwell, University of Reading

Powdery mildew is rated the most important strawberry disease for UK strawberry growers; an untreated epidemic of powdery mildew on strawberry leads to severe yield loss and unmarketable fruit. Powdery mildew is currently controlled by regular applications of fungicide. However, the evolution of fungicide resistance to DMI compounds has exacerbated the already heightened concerns over the loss of effective fungicides. Current pre-breeding work at NIAB EMR has laid the groundwork to alleviate this problem through the identification of multiple genetic markers associated with powdery mildew resistance in strawberry foliage.


This studentship will focus on disease symptom progression in the strawberry fruits themselves. Through the utilisation of advanced imaging technologies in the assessment of pathogenicity assays we will be able to screen strawberry fruits for resistance to powdery mildew. The phenotyping data will feed into a genome wide association study, a powerful analysis that is able to identify markers linked to resistance genes present across all strawberry cultivars. Furthermore, by applying the imaging techniques, the project will determine whether powdery mildew resistance is tissue-specific and if each tissue (i.e. leaf, calyx and strawberry) contains its own suite of genes responsible for conferring resistance.


Work package 1: Pathology test and image analysis for powdery mildew on strawberry fruits

  • Development of a controlled inoculation procedure based on procedures developed for the model organism Barley powdery mildew (Blumeria graminis).
  • Pathogenicity tests on key parental and diversifying strawberry cultivars.
  • Image analysis to provide an objective assessment of fruit disease symptoms.
  • Supervised classification techniques on RGB, 3D and hyperspectral images to allow monitoring of disease severity over time.
  • Automation of microscopy spore viability counts, which will be used to indicate resistance status of cultivars and fruit.
  • Defining the potential for a race structure within powdery mildew fungal isolates on core strawberry cultivars

Work package 2: Genome wide association analysis and identification of candidate resistance genes

  • Use of pre-existing genetic resources associated with the multi parental population combined with phenotyping assays conducted as part of WP1 will allow the identification of quantitative trait loci associated with tissue specific mildew resistance
  • Single nucleotide polymorphism (SNP) data has been generated for each individual within the study population using the istraw35 axiom array as part of the “Developing resource use efficient strawberries for substrate production” Agri-tech Innovate UK project
  • Genome wide association mapping will be carried out using Plink and the octoploid strawberry consensus map generated using 5 mapping populations: ‘Redgauntlet’ × ‘Hapil’; EMR, ‘Emily’ × ‘Fenella’; NIAB-EMR, ‘Flamenco’ × ‘Chandler’; NIAB-EMR, ‘Capitola’ × ‘CF1116’; INRA, ‘Camerosa’ × ‘Dover’; CRAG
  • The student will be able to identify candidate resistance genes using the octoploid strawberry genome and gene models generated as part of “Octoseq” BBSRC project. Putative target genes neighbouring resistance QTL will be validated in WP3
  • The genetic knowledge gained as part of this project can be used to inform marker assisted and genomic selection breeding strategies to aid the breeding of mildew resistant strawberry varieties

Work package 3: Validation of strawberry resistance genes through gene deletion

  • Functional validation of candidate mildew resistance genes will be achieved through deletion of putative strawberry cultivar to contain the putative resistance gene using advanced techniques (CRISPR/Cas9)
  • Strawberry transformation using these techniques is established in the Genetics Genomics and Breeding department of NIAB EMR
  • Phenotyping mildew assays of transformed strawberries to confirm the function of the deleted resistance genes
  • Twelve mildew resistance locus O genes for Fragaria vesca (FvMLO) have been identified as up regulated in the diploid strawberry these would be prime candidates for functional validation should insufficient gene candidate numbers be identified in WP2.
  • RNA sequencing of resistant and susceptible octoploid strawberry varieties across a time course following mildew infection to help identify differentially regulated candidate resistance host transcripts.

The PhD student will be supported by an extensive pre-established knowledge base and will have access to the recently developed fruit phenotyping platform alongside being able to draw upon the NIAB-EMR strawberry germplasm collection and associated genomic resources. We know there is a large potential to enhance mildew resistance within strawberry germplasm and through embracing breeding control strategies we can minimize disease induced yield loss, reduced fungicide reliance and lower food pesticide residues.

Applying for this studentship

The most important eligibility criterion for this funded studentship is residency:

  1. UK students: If you have been ordinarily resident in the UK for three years you will normally be entitled to apply for a full studentship, covering tuition fees and a maintenance stipend.
  2. EU students: If you have been ordinarily resident in another EU country (outside the UK) for three years you will normally be able to apply for a tuition fees-only award (without a maintenance stipend). If you have lived in the UK for three years you may be eligible for a full studentship.

This eligibility is unaffected by Brexit. The UK Government has guaranteed EU eligibility for Research Council funding for PhDs beginning before the end of the 2019-20 academic year.

Anyone interested should contact recruitment@emr.ac.uk for an application form and return the form to recruitment@emr.ac.uk before the deadline of 28th February 2019.