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 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.
Project description:IntroductionAscochyta blight (AB) caused by the necrotrophic fungus Ascochyta rabiei is one of the most significant diseases that limit the production of chickpea. Understanding the metabolic mechanisms underlying chickpea-A.rabiei interactions will provide important clues to develop novel approaches to manage this disease.MethodsWe performed metabolite profiling of the aerial tissue (leaf and stem) of two chickpea accessions comprising a moderately resistant breeding line (CICA1841) and a highly susceptible cultivar (Kyabra) in response to one of the highly aggressive Australian A. rabiei isolates TR9571 via non-targeted metabolomics analysis using liquid chromatography-mass spectrometry.ResultsThe results revealed resistance and susceptibility-associated constitutive metabolites for example the moderately resistant breeding line had a higher mass abundance of ferulic acid while the levels of catechins, phthalic acid, and nicotinic acid were high in the susceptible cultivar. Further, the host-pathogen interaction resulted in the altered levels of various metabolites (induced and suppressed), especially in the susceptible cultivar revealing a possible reason for susceptibility against A.r abiei. Noticeably, the mass abundance of salicylic acid was induced in the aerial tissue of the susceptible cultivar after fungus colonization, while methyl jasmonate (MeJA) was suppressed, elucidating the key role of phytohormones in chickpea-A. rabiei interaction. Many differential metabolites in flavonoid biosynthesis, phenylalanine, Aminoacyl-tRNA biosynthesis, pentose and glucuronate interconversions, arginine biosynthesis, valine, leucine, and isoleucine biosynthesis, and alanine, aspartate, and glutamate metabolism pathways were up- and down-regulated showing the involvement of these metabolic pathways in chickpea-A. rabiei interaction.DiscussionTaken together, this study highlights the chickpea - A. rabiei interaction at a metabolite level and shows how A. rabiei differentially alters the metabolite profile of moderately resistant and susceptible chickpea accessions and is probably exploiting the chickpea defense pathways in its favour.
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:Necrotrophic pathogens experience host-generated oxidative stress during pathogenesis. They overcome such hostile environment by intricate mechanisms which are largely understudied. In this article, reference-based transcriptome analysis of a devastating Ascochyta Blight (AB) disease causing chickpea pathogen Ascochyta rabiei was explored to get insights into survival mechanisms under oxidative stress. Here, expression profiling of mock-treated and menadione-treated fungus was carried out by RNA-Seq approach. A significant number of genes in response to oxidative stress were overrepresented, suggestive of a robust and coordinated defense system of A. rabiei. A total 73 differentially expressed genes were filtered out from both the transcriptomes, among them 64 were up-regulated and 9 were found down-regulated. The gene ontology and KEGG mapping were conducted to comprehend the possible regulatory roles of differentially expressed genes in metabolic networks and biosynthetic pathways. Transcript profiling, KEGG pathway and gene ontology-based enrichment analysis revealed 12 (16.43%) stress responsive factors, 25 (34.24%) virulence associated genes, 10 (13.69%) putative effectors and 28 (38.35%) important interacting proteins associated with various metabolic pathways. In addition, genes with differential expression were further explored for underlying putative pathogenicity factors. We identified five genes ST47_g10291, ST47_g9396, ST47_g10294, ST47_g4395, and ST47_g7191 that were common to stress and fungal pathogenicity. The factors recognized in this work can be used to establish molecular tools to explain the regulatory gene networks engaged in stress response of fungal pathogens and disease management.
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 (AB), caused by the fungal pathogen Ascochyta rabiei, is a devastating foliar disease of chickpea (Cicer arietinum L.). The genotyping-by-sequencing (GBS)-based approach was deployed for mapping QTLs associated with AB resistance in chickpea in two recombinant inbred line populations derived from two crosses (AB3279 derived from ILC 1929 × ILC 3279 and AB482 derived from ILC 1929 × ILC 482) and tested in six different environments. Twenty-one different genomic regions linked to AB resistance were identified in regions CalG02 and CalG04 in both populations AB3279 and AB482. These regions contain 1,118 SNPs significantly associated with AB resistance (p ≤ 0.001), which explained 11.2-39.3% of the phenotypic variation (PVE). Nine of the AB resistance-associated genomic regions were newly detected in this study, while twelve regions were known from previous AB studies. The proposed physical map narrows down AB resistance to consistent genomic regions identified across different environments. Gene ontology (GO) assigned these QTLs to 319 genes, many of which were associated with stress and disease resistance, and with most important genes belonging to resistance gene families such as leucine-rich repeat (LRR) and transcription factor families. Our results indicate that the flowering-associated gene GIGANTEA is a possible key factor in AB resistance in chickpea. The results have identified AB resistance-associated regions on the physical genetic map of chickpea and allowed for the identification of associated markers that will help in breeding of AB-resistant varieties.
Project description:Ascochyta blight is one of the major diseases of chickpea worldwide. The genetic resistance to ascochyta blight in chickpea is complex and governed by multiple QTLs. However, the molecular mechanism of quantitative disease resistance to ascochyta blight and the genes underlying these QTLs are still unknown. Most often disease resistance is determined by resistance (R) genes. The most predominant R-genes contain nucleotide binding site and leucine rich repeat (NBS-LRR) domains. A total of 121 NBS-LRR genes were identified in the chickpea genome. Ninety-eight of these genes contained all essential conserved domains while 23 genes were truncated. The NBS-LRR genes were grouped into eight distinct classes based on their domain architecture. Phylogenetic analysis grouped these genes into two major clusters based on their structural variation, the first cluster with toll or interleukin-1 like receptor (TIR) domain and the second cluster either with or without a coiled-coil domain. The NBS-LRR genes are distributed unevenly across the eight chickpea chromosomes and nearly 50% of the genes are present in clusters. Thirty of the NBS-LRR genes were co-localized with nine of the previously reported ascochyta blight QTLs and were tested as potential candidate genes for ascochyta blight resistance. Expression pattern of these genes was studied in two resistant (CDC Corinne and CDC Luna) and one susceptible (ICCV 96029) genotypes at different time points after ascochyta blight infection using real-time quantitative PCR. Twenty-seven NBS-LRR genes showed differential expression in response to ascochyta blight infection in at least one genotype at one time point. Among these 27 genes, the majority of the NBS-LRR genes showed differential expression after inoculation in both resistant and susceptible genotypes which indicates the involvement of these genes in response to ascochyta blight infection. Five NBS-LRR genes showed genotype specific expression. Our study provides a new insight of NBS-LRR gene family in chickpea and the potential involvement of NBS-LRR genes in response to ascochyta blight infection.
Project description:Ascochyta blight (AB), caused by a necrotrophic fungus, Ascochyta rabiei (syn. Phoma rabiei) has the potential to destroy the chickpea industry worldwide, due to limited sources of genetic resistance in the cultivated gene pool, high evolutionary potential of the pathogen and challenges with integrated disease management. Therefore, the deployment of stable genetic resistance in new cultivars could provide an effective disease control strategy. To investigate the genetic basis of AB resistance, genotyping-by-sequencing based DArTseq-single nucleotide polymorphism (SNP) marker data along with phenotypic data of 251 advanced breeding lines and chickpea cultivars were used to perform genome-wide association (GWAS) analysis. Host resistance was evaluated seven weeks after sowing using two highly aggressive single spore isolates (F17191-1 and TR9571) of A. rabiei. GWAS analyses based on single-locus and multi-locus mixed models and haplotyping trend regression identified twenty-six genomic regions on Ca1, Ca4, and Ca6 that showed significant association with resistance to AB. Two haplotype blocks (HB) on chromosome Ca1; HB5 (992178-1108145 bp), and HB8 (1886221-1976301 bp) were associated with resistance against both isolates. Nine HB on the chromosome, Ca4, spanning a large genomic region (14.9-56.6 Mbp) were also associated with resistance, confirming the role of this chromosome in providing resistance to AB. Furthermore, trait-marker associations in two F3 derived populations for resistance to TR9571 isolate at the seedling stage under glasshouse conditions were also validated. Eighty-nine significantly associated SNPs were located within candidate genes, including genes encoding for serine/threonine-protein kinase, Myb protein, quinone oxidoreductase, and calmodulin-binding protein all of which are implicated in disease resistance. Taken together, this study identifies valuable sources of genetic resistance, SNP markers and candidate genes underlying genomic regions associated with AB resistance which may enable chickpea breeding programs to make genetic gains via marker-assisted/genomic selection strategies.