Periodic Reporting for period 1 - GENEVABREED (Cloning and functional characterization of a complex resistance locus from ‘Geneva’ to breed apple cultivars with durable scab resistance)
Reporting period: 2016-11-01 to 2018-10-31
In this project, we will further characterize this complex locus, employing next generation sequencing, together with bioinformatics and functional analysis of disease candidate resistance genes (CRGs): (1) we will sequence the resistance locus in ‘Geneva’ and identify CRG that are polymorphic (presence/absence, or sequence polymorphism) between the resistant ‘Geneva’ and the susceptible GD; (2) we will clone each CRG with its native promoter, terminator and introns; and (3) transform susceptible lines with the individual CRG to evaluate their effect on the level of disease resistance and its race-specific spectrum. This will not only build a better understanding of the genetic basis of apple scab resistance and the gene-for-gene relationships between the pathogen and the host, but it will enable the development of molecular markers for breeding new ‘sprayfree’ cultivars with durable scab resistance.
Research activity 2: Fine mapping of the resistance loci in the ‘Geneva’ x ‘Braeburn’ population. DNA from was extracted from each individual of the progeny and their parents. This DNA material would be used to fine map the resistance loci, and narrow down the interval between flanking molecular markers. I would use molecular markers designed from Genotyping by Sequencing, as well as from the full sequence of the ‘Geneva’ genome.
Research activity 3: Identification of CRG for the complex resistance of ‘Geneva’. I have been trained in the genomic sequence analysis to align the ‘Geneva’ sequences with the double haploid ‘GD’ genome sequence and annotate potential CRG co-localizing with the resistance loci on the ‘Geneva’ x ’Braeburn’ genetic map of Research activity 2. I would have given a priority for genes corresponding to family proteins well known to act in plant disease resistance, but also to other family proteins with unknown functions in disease resistance.
Research activity 4: Development of transient expression techniques in apple for the functional validation of CRG in ‘Geneva’. I would target functional RG identified in the Research activities 2 and 3 to transform a susceptible apple cultivar with the various CRG separately, or in pairs since pairs of CRG could be necessary to provide the recessive resistance. I would assess the effect of the plant transformation on the resistance phenotype by inoculating with well characterized monoconidial isolates of V. inaequalis (based on the Research activity 1). In collaboration with Dr Espley I have initiated setting up transient expression experiments using a Malus host. I transformed into Agrobacterium, various constructs initially developed for genes involved in the anthocyanin biosynthetic pathway of apple. Infiltration were made in tobacco leaves as a positive control, as well as into detached apple leaves grown in the greenhouse or in vitro. Each plant substrate showed various mechanical resistances to the infiltration being the tobacco leaves and detached apple leaves grown in the greenhouse the easiest to infiltrate. Red coloration has been observed in tobacco plants as well as in detached apple leaves grown in the greenhouse, but these latter one were not specific to the transient gene expression. Next, other infiltration methods would be tested, as well as more mature in vitro apple plants.
Research activity 5: Analysis of genome-wide expression of the resistance response of ‘Geneva’ to V. inaequalis. In this research activity I would evaluate the transcriptional response of the transformed plants generated in the Research activity 4 or differential hosts identified in the Research activity 1. These host plants could be expressing individual, or a complex of RG in response to infection by various V. inaequalis isolates. This would permit to better understand the transcriptional regulatory network acting in the 'Geneva' scab resistance. A bioinformatics training provided me with some additional tools for the analysis of future RNA sequencing data. I identified the weighted correlation network analysis as a suitable method of analysis. It would be used to find common patterns of gene expressions across our different samples, relate these modules of genes to one another, and find functional annotation of genes inside each module. That would give some biological insights into the transcriptional network and provide a better understanding of the complex genetic resistance of ‘Geneva’. I have started developing an R code for the WGCNA analysis.