Identification of Sclerotinia stem rot resistance quantitative trait loci in a chickpea (Cicer arietinum) recombinant inbred line population.

Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum , is one of the most economically devastating diseases in chickpea (Cicer arietinum L.). No complete resistance is available in chickpea to this disease, and the inheritance of partial resistance is not understood. Two hundred F7 recombinant inbred lines (RILs) derived from a cross between a partially resistant variety PBA HatTrick, and a highly susceptible variety Kyabra were characterised for their responses to SSR inoculation. Quantitative trait locus (QTL) analysis was conducted for the area under the disease progress curve (AUDPC) after RIL infection with S. sclerotiorum . Four QTLs on chromosomes, Ca4 (qSSR4-1, qSSR4-2), Ca6 (qSSR6-1) and Ca7 (qSSR7-1), individually accounted for between 4.2 and 15.8% of the total estimated phenotypic variation for the response to SSR inoculation. Candidate genes located in these QTL regions are predicted to be involved in a wide range of processes, including phenylpropanoid biosynthesis, plant-pathogen interaction, and plant hormone signal transduction. This is the first study investigating the inheritance of resistance to S. sclerotiorum in chickpea. Markers associated with the identified QTLs could be employed for marker-assisted selection in chickpea breeding.

Analysis of differentially expressed Sclerotinia sclerotiorum genes during the interaction with moderately resistant and highly susceptible chickpea lines.

BACKGROUND: Sclerotinia sclerotiorum, the cause of Sclerotinia stem rot (SSR), is a host generalist necrotrophic fungus that can cause major yield losses in chickpea (Cicer arietinum) production. This study used RNA sequencing to conduct a time course transcriptional analysis of S. sclerotiorum gene expression during chickpea infection. It explores pathogenicity and developmental factors employed by S. sclerotiorum during interaction with chickpea. RESULTS: During infection of moderately resistant (PBA HatTrick) and highly susceptible chickpea (Kyabra) lines, 9491 and 10,487 S. sclerotiorum genes, respectively, were significantly differentially expressed relative to in vitro. Analysis of the upregulated genes revealed enrichment of Gene Ontology biological processes, such as oxidation-reduction process, metabolic process, carbohydrate metabolic process, response to stimulus, and signal transduction. Several gene functional categories were upregulated in planta, including carbohydrate-active enzymes, secondary metabolite biosynthesis clusters, transcription factors and candidate secreted effectors. Differences in expression of four S. sclerotiorum genes on varieties with different levels of susceptibility were also observed. CONCLUSION: These findings provide a framework for a better understanding of S. sclerotiorum interactions with hosts of varying susceptibility levels. Here, we report for the first time on the S. sclerotiorum transcriptome during chickpea infection, which could be important for further studies on this pathogen's molecular biology.

Identification of Sources of Sclerotinia sclerotiorum Resistance in a Collection of Wild Cicer Germplasm.

Sclerotinia sclerotiorum is an important fungal pathogen of chickpea (Cicer arietinum L.), and it can cause yield losses up to 100%. The wild progenitors are much more diverse than domesticated chickpea, and this study describes how this relates to S. sclerotiorum resistance. Initially, the pathogenicity of nine Australian S. sclerotiorum isolates was examined on three Cicer lines to develop a robust phenotyping assay, and significant differences in isolate aggressiveness were identified with six isolates being classed as highly aggressive and three as moderately aggressive. We identified two S. sclerotiorum isolates, CU8.20 and CU10.12, to be highly aggressive and moderately aggressive, respectively. A subsequent phenotyping assay was conducted using the two isolates to evaluate 86 wild Cicer accessions (Cicer reticulatum and Cicer echinospermum) and two C. arietinum varieties for resistance to S. sclerotiorum. A subset of 12 genotypes was further evaluated, and subsequently, two wild Cicer accessions with consistently high levels of resistance to S. sclerotiorum were examined using the initially characterized nine isolates. Wild Cicer accessions Karab_084 and Deste_063 demonstrated consistent partial resistance to S. sclerotiorum. There were significant differences in responses to S. sclerotiorum across wild Cicer collection sites. The Cermik, Karabahce, and Destek sites' responses to the aggressive isolate CU8.20 ranged from resistant to susceptible, highlighting an interaction between isolate genotype and chickpea collection site for sclerotinia stem rot resistance. This is the first evidence of partial stem resistance identified in wild Cicer germplasm, which can be adopted in chickpea breeding programs to enhance S. sclerotiorum resistance in future chickpea varieties.

Modeling first order additive × additive epistasis improves accuracy of genomic prediction for sclerotinia stem rot resistance in canola.

The fungus Sclerotinia sclerotiorum infects hundreds of plant species including many crops. Resistance to this pathogen in canola (Brassica napus L. subsp. napus) is controlled by numerous quantitative trait loci (QTL). For such polygenic traits, genomic prediction may be useful for breeding as it can capture many QTL at once while also considering nonadditive genetic effects. Here, we test application of common regression models to genomic prediction of S. sclerotiorum resistance in canola in a diverse panel of 218 plants genotyped at 24,634 loci. Disease resistance was scored by infection with an aggressive isolate and monitoring over 3 wk. We found that including first-order additive × additive epistasis in linear mixed models (LMMs) improved accuracy of breeding value estimation between 3 and 40%, depending on method of assessment, and correlation between phenotypes and predicted total genetic values by 14%. Bayesian models performed similarly to or worse than genomic relationship matrix-based models for estimating breeding values or overall phenotypes from genetic values. Bayesian ridge regression, which is most similar to the genomic relationship matrix-based approach in the amount of shrinkage it applies to marker effects, was the most accurate of this family of models. This confirms several studies indicating the highly polygenic nature of sclerotinia stem rot resistance. Overall, our results highlight the use of simple epistasis terms for prediction of breeding values and total genetic values for a complex disease resistance phenotype in canola.