Project description:Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) ESTs and lentil (Lens culinaris Med.) resistance gene analogs, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, where samples from mock-inoculated controls acted as references against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye-swap), the inclusion of negative controls, and strict selection criteria for differentially expressed genes including a fold change cutoff determined by self-self hybridizations, Students t test and multiple testing correction (P<0.05). Microarray observations were also validated by quantitative RT-PCR. The time-course expression patterns of 756 microarray features resulted in differential expression of 97 genes in at least one genotype at one time-point. K-means clustering grouped the genes into clusters of similar observations for each genotype, and comparisons between A. rabiei-resistant and susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, as well as several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on functional validation of the genes of interest. Keywords: time course disease state analysis
Project description:Chickpea (Cicer arietinum L.) is the second largest pulse crop grown worldwide and ascochyta blight caused by Ascochyta rabiei (Pass.) Labr. is the most devastating disease of the crop in all chickpea growing areas across the continents. The pathogen A. rabiei is highly variable. The resistant sources available are not sufficient and new sources needs to be identified from time to time as resistance breakdown in existing chickpea varieties is very frequent due to fast evolution of new pathotypes of the pathogen. Therefore, this work was undertaken to evaluate the existing chickpea germplasm diversity conserved in Indian National Genebank against the disease under artificial epiphytotic conditions. An artificial standard inoculation procedure was followed for uniform spread of the pathogen. During the last five winter seasons from 2014-15 to 2018-19, a total of 1,970 accessions have been screened against the disease and promising accessions were identified and validated. Screening has resulted in identification of some promising chickpea accessions such as IC275447, IC117744, EC267301, IC248147 and EC220109 which have shown the disease resistance (disease severity score ≤3) in multiple seasons and locations. Promising accessions can serve as the potential donors in chickpea improvement programs. The frequency of resistant and moderately resistant type accessions was comparatively higher in accessions originated from Southwest Asian countries particularly Iran and Syria than the accessions originated from Indian sub-continent. Further large scale screening of chickpea germplasm originated from Southwest Asia may result in identifying new resistant sources for the disease.
Project description:Ascochyta rabiei is the causal organism of ascochyta blight of chickpea and is present in chickpea crops worldwide. Here we report the release of a high-quality PacBio genome assembly for the Australian A. rabiei isolate ArME14. We compare the ArME14 genome assembly with an Illumina assembly for Indian A. rabiei isolate, ArD2. The ArME14 assembly has gapless sequences for nine chromosomes with telomere sequences at both ends and 13 large contig sequences that extend to one telomere. The total length of the ArME14 assembly was 40,927,385 bp, which was 6.26 Mb longer than the ArD2 assembly. Division of the genome by OcculterCut into GC-balanced and AT-dominant segments reveals 21% of the genome contains gene-sparse, AT-rich isochores. Transposable elements and repetitive DNA sequences in the ArME14 assembly made up 15% of the genome. A total of 11,257 protein-coding genes were predicted compared with 10,596 for ArD2. Many of the predicted genes missing from the ArD2 assembly were in genomic regions adjacent to AT-rich sequence. We compared the complement of predicted transcription factors and secreted proteins for the two A. rabiei genome assemblies and found that the isolates contain almost the same set of proteins. The small number of differences could represent real differences in the gene complement between isolates or possibly result from the different sequencing methods used. Prediction pipelines were applied for carbohydrate-active enzymes, secondary metabolite clusters and putative protein effectors. We predict that ArME14 contains between 450 and 650 CAZymes, 39 putative protein effectors and 26 secondary metabolite clusters.
Project description:Ascochyta blight disease, caused by the necrotrophic fungus Ascochyta rabiei, is a major biotic constraint to chickpea production in Australia and worldwide. Detailed knowledge of the structure of the pathogen population and its potential to adapt to our farming practices is key to informing optimal management of the disease. This includes understanding the molecular diversity among isolates and the frequency and distribution of the isolates that have adapted to overcome host resistance across agroecologically distinct regions. Thanks to continuous monitoring efforts over the past 6 years, a comprehensive collection of A. rabiei isolates was collated from the major Australian chickpea production regions. To determine the molecular structure of the entire population, representative isolates from each collection year and growing region have been genetically characterized using a DArTseq genotyping-by-sequencing approach. The genotyped isolates were further phenotyped to determine their pathogenicity levels against a differential set of chickpea cultivars and genotype-phenotype associations were inferred. Overall, the Australian A. rabiei population displayed a far lower genetic diversity (average Nei's gene diversity of 0.047) than detected in other populations worldwide. This may be explained by the presence of a single mating-type in Australia, MAT1-2, limiting its reproduction to a clonal mode. Despite the low detected molecular diversity, clonal selection appears to have given rise to a subset of adapted isolates that are highly pathogenic on commonly employed resistance sources, and that are occurring at an increasing frequency. Among these, a cluster of genetically similar isolates was identified, with a higher proportion of highly aggressive isolates than in the general population. The discovery of distinct genetic clusters associated with high and low isolate pathogenicity forms the foundation for the development of a molecular pathotyping tool for the Australian A. rabiei population. Application of such a tool, along with continuous monitoring of the genetic structure of the population will provide crucial information for the screening of breeding material and integrated disease management packages.
Project description:Chickpea (Cicer arietinum L.) is an important cool season food legume, however, its production is severely constrained by the foliar disease Ascochyta blight caused by the fungus Ascochyta rabiei (syn. Phoma rabiei). Several disease management options have been developed to control the pathogen, including breeding for host plant resistance. However, the pathogen population is evolving to produce more aggressive isolates. For host resistance to be effective, the plant must quickly recognize the pathogen and instigate initial defense mechanisms, optimally at the point of contact. Given that the most resistant host genotypes display rapid pathogen recognition and response, the approach taken was to assess the type, speed and pattern of recognition via Resistance Gene Analog (RGA) transcription among resistant and susceptible cultivated chickpea varieties. RGAs are key factors in the recognition of plant pathogens and the signaling of inducible defenses. In this study, a suite of RGA loci were chosen for further investigation from both published literature and from newly mined homologous sequences within the National Center for Biotechnology Information (NCBI) database. Following their validation in the chickpea genome, 10 target RGAs were selected for differential expression analysis in response to A. rabiei infection. This was performed in a set of four chickpea varieties including two resistant cultivars (ICC3996 and PBA Seamer), one moderately resistant cultivar (PBA HatTrick) and one susceptible cultivar (Kyabra). Gene expression at each RGA locus was assessed via qPCR at 2, 6, and 24 h after A. rabiei inoculation with a previously characterized highly aggressive isolate. As a result, all loci were differentially transcribed in response to pathogen infection in at least one genotype and at least one time point after inoculation. Among these, the differential expression of four RGAs was significant and consistently increased in the most resistant genotype ICC3996 immediately following inoculation, when spore germination began and ahead of penetration into the plant's epidermal tissues. Further in silico analyses indicated that the differentially transcribed RGAs function through ADP-binding within the pathogen recognition pathway. These represent clear targets for future functional validation and potential for selective resistance breeding for introgression into elite cultivars.
Project description:Ascochyta blight caused by Ascochyta rabiei is an important disease of chickpea. By using systems analysis, we retrieved and analyzed the published information on A. rabiei to develop a mechanistic, weather-driven model for the prediction of Ascochyta blight epidemics. The ability of the model to predict primary infections was evaluated using published data obtained from trials conducted in Washington (USA) in 2004 and 2005, Israel in 1996 and 1998, and Spain from 1988 to 1992. The model showed good accuracy and specificity in predicting primary infections. The probability of correctly predicting infections was 0.838 and the probability that there was no infection when not predicted was 0.776. The model's ability to predict disease progress during the growing season was also evaluated by using data collected in Australia from 1996 to 1998 and in Southern Italy in 2019; a high concordance correlation coefficient (CCC = 0.947) between predicted and observed data was obtained, with an average distance between real and fitted data of root mean square error (RMSE) = 0.103, indicating that the model was reliable, accurate, and robust in predicting seasonal dynamics of Ascochyta blight epidemics. The model could help growers schedule fungicide treatments to control Ascochyta blight on chickpea.