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Phytophthora root rot caused by Phytophthora medicaginis is an important disease of chickpeas (Cicer arietinum) in Australia with limited management options, increasing reliance on breeding for improved levels of genetic resistance. Resistance based on chickpea–Cicer echinospermum crosses is partial with a quantitative genetic basis provided by C. echinospermum and some disease tolerance traits originating from C. arietinum germplasm. Partial resistance is hypothesised to reduce pathogen proliferation, while tolerant germplasm may contribute some fitness traits, such as an ability to maintain yield despite pathogen proliferation. To test these hypotheses, we used P. medicaginis DNA concentrations in the soil as a parameter for pathogen proliferation and disease assessments on lines of two recombinant inbred populations of chickpea–C. echinospermum crosses to compare the reactions of selected recombinant inbred lines and parents. Our results showed reduced inoculum production in a C. echinospermum backcross parent relative to the C. arietinum variety Yorker. Recombinant inbred lines with consistently low levels of foliage symptoms had significantly lower levels of soil inoculum compared to lines with high levels of visible foliage symptoms. In a separate experiment, a set of superior recombinant inbred lines with consistently low levels of foliage symptoms was tested for soil inoculum reactions relative to control normalised yield loss. The in-crop P. medicaginis soil inoculum concentrations across genotypes were significantly and positively related to yield loss, indicating a partial resistance-tolerance spectrum. Disease incidence and the rankings for in-crop soil inoculum were correlated strongly to yield loss. These results indicate that soil inoculum reactions may be useful to identify genotypes with high levels of partial resistance.

QTL controlling vigour and related traits were identified in a chickpea RIL population and validated in diverse sets of germplasm. Robust KASP markers were developed for marker-assisted selection. To understand the genetic constitution of vigour in chickpea (Cicer arietinum L.), genomic data from a bi-parental population and multiple diversity panels were used to identify QTL, sequence-level haplotypes and genetic markers associated with vigour-related traits in Australian environments. Using 182 Recombinant Inbred Lines (RILs) derived from a cross between two desi varieties, Rupali and Genesis836, vigour QTL independent of flowering time were identified on chromosomes (Ca) 1, 3 and 4 with genotypic variance explained (GVE) ranging from 7.1 to 28.8%. Haplotype analysis, association analysis and graphical genotyping of whole-genome re-sequencing data of two diversity panels consisting of Australian and Indian genotypes and an ICRISAT Chickpea Reference Set revealed a deletion in the FTa1–FTa2–FTc gene cluster of Ca3 significantly associated with vigour and flowering time. Across the RIL population and diversity panels, the impact of the deletion was consistent for vigour but not flowering time. Vigour-related QTL on Ca4 co-located with a QTL for seed size in Rupali/Genesis836 (GVE = 61.3%). Using SNPs from this region, we developed and validated gene-based KASP markers across different panels. Two markers were developed for a gene on Ca1, myo -inositol monophosphatase (CaIMP), previously proposed to control seed size, seed germination and seedling growth in chickpea. While associated with vigour in the diversity panels, neither the markers nor broader haplotype linked to CaIMP was polymorphic in Rupali/Genesis836. Importantly, vigour appears to be controlled by different sets of QTL across time and with components which are independent from phenology.

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.

Phytophthora root rot (PRR) caused by the soilborne oomycete Phytophthora medicaginis is a significant constraint to chickpea (Cicer arietinum) production across the northern grains region of Australia. In flooded soil, which is conducive to PRR disease development, up to 70% yield loss can occur in the most resistant Australian cultivars. Incorporating waterlogging tolerance in soybean (Glycine max) has been shown to improve quantitative resistance to Phytophthora sojae. Root growth of three chickpea genotypes was assessed at the seedling stage under waterlogging, PRR, and the combination of these abiotic and biotic constraints. Levels of waterlogging tolerance in chickpea are inherently low, yet selected genotypes displayed variability in root traits linked to improved waterlogging tolerance. The PRR moderately susceptible chickpea cultivar Yorker and PRR very susceptible Rupali demonstrated an eightfold increase in early adventitious root growth from the epicotyl region under waterlogging stress, compared with the PRR resistant interspecific backcross genotype 04067-81-2-1-1 (C. echinospermum × C. arietinum*2). Selection for primary root depth, which was significantly greater in 04067-81-2-1-1 under waterlogging, appears to improve PRR resistance compared with root replacement traits. Soilborne Phytophthora spp. are reportedly attracted to branch sites and leached exudates. We propose that compromised root barriers at emergence sites of adventitious roots under waterlogging conditions hasten hyphal entry, potentially increasing susceptibility to PRR. Hence, screening for root depth and absence of adventitious root development under waterlogged conditions may offer a novel proxy phenotyping method for PRR resistance traits at early stages of chickpea breeding.

Ascochyta blight (AB), caused by a necrotrophic fungus

Accelerating genetic gain in crop improvement is required to ensure improved yield and yield stability under increasingly challenging climatic conditions. This case study demonstrates the effective confluence of innovative breeding technologies within a collaborative breeding framework to develop and rapidly introgress imidazolinone Group 2 herbicide tolerance into an adapted Australian chickpea genetic background. A well-adapted, high-yielding desi cultivar PBA HatTrick was treated with ethyl methanesulfonate to generate mutations in the ACETOHYDROXYACID SYNTHASE 1 (CaAHAS1) gene. After 2 years of field screening with imidazolinone herbicide across >20 ha and controlled environment progeny screening, two selections were identified which exhibited putative herbicide tolerance. Both selections contained the same single amino acid substitution, from alanine to valine at position 205 (A205V) in the AHAS1 protein, and KASP™ markers were developed to discriminate between tolerant and intolerant genotypes. A pipeline combining conventional crossing and F2 production with accelerated single seed descent from F2:4 and marker-assisted selection at F2 rapidly introgressed the herbicide tolerance trait from one of the mutant selections, D15PAHI002, into PBA Seamer, a desi cultivar adapted to Australian cropping areas. Field evaluation of the derivatives of the D15PAHI002 × PBA Seamer cross was analyzed using a factor analytic mixed model statistical approach designed to accommodate low seed numbers resulting from accelerated single seed descent. To further accelerate trait introgression, field evaluation trials were undertaken concurrent with crop safety testing trials. In 2020, 4 years after the initial cross, an advanced line selection CBA2061, bearing acetohydroxyacid synthase (AHAS) inhibitor tolerance and agronomic and disease resistance traits comparable to parent PBA Seamer, was entered into Australian National Variety Trials as a precursor to cultivar registration. The combination of cross-institutional collaboration and the application of novel pre-breeding platforms and statistical technologies facilitated a 3-year saving compared to a traditional breeding approach. This breeding pipeline can be used as a model to accelerate genetic gain in other self-pollinating species, particularly food legumes.

Advancements in high-throughput genotyping and sequencing technologies are enabling the development of a vast range of genomic tools and resources for a new revolution in plant breeding. Several genotyping-by-sequencing (GBS) methods including capture-based, genome complexity reduction and sequencing of cDNA (GBS-t) are available for application in trait dissection, association mapping, and genomic selection (GS) in crop plants. The aims of this study were to identify genomic regions conferring resistance to Ascochyta blight (AB) introgressed from the wild Cicer echinospernum into the domesticated C. arietinum, through a conventional recombinant inbred population genotyped using a variety of GBS methods. Evaluation of GBS methods revealed that capture-based approaches are robust and reproducible while GBS-t is rapid and flexible. A genetic linkage map consisting of 5886 polymorphic loci spanning 717.26 cM was generated. Using field phenotyping data from two years, a single genomic region on LG4 was identified with quantitative trait loci (QTL) mapping. Both GBS methods reported in this study are well suited for applications in genomics assisted plant breeding. Linked markers for AB resistance, identified in the current study, provide an important resource for the deployment into chickpea breeding programs for marker-assisted selection (MAS).

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.

QTL controlling vigour and related traits were identified in a chickpea RIL population and validated in diverse sets of germplasm. Robust KASP markers were developed for marker-assisted selection. To understand the genetic constitution of vigour in chickpea (Cicer arietinum L.), genomic data from a bi-parental population and multiple diversity panels were used to identify QTL, sequence-level haplotypes and genetic markers associated with vigour-related traits in Australian environments. Using 182 Recombinant Inbred Lines (RILs) derived from a cross between two desi varieties, Rupali and Genesis836, vigour QTL independent of flowering time were identified on chromosomes (Ca) 1, 3 and 4 with genotypic variance explained (GVE) ranging from 7.1 to 28.8%. Haplotype analysis, association analysis and graphical genotyping of whole-genome re-sequencing data of two diversity panels consisting of Australian and Indian genotypes and an ICRISAT Chickpea Reference Set revealed a deletion in the FTa1-FTa2-FTc gene cluster of Ca3 significantly associated with vigour and flowering time. Across the RIL population and diversity panels, the impact of the deletion was consistent for vigour but not flowering time. Vigour-related QTL on Ca4 co-located with a QTL for seed size in Rupali/Genesis836 (GVE = 61.3%). Using SNPs from this region, we developed and validated gene-based KASP markers across different panels. Two markers were developed for a gene on Ca1, myo -inositol monophosphatase (CaIMP), previously proposed to control seed size, seed germination and seedling growth in chickpea. While associated with vigour in the diversity panels, neither the markers nor broader haplotype linked to CaIMP was polymorphic in Rupali/Genesis836. Importantly, vigour appears to be controlled by different sets of QTL across time and with components which are independent from phenology.

During the reproductive stage, chilling temperatures and frost reduce the yield of chickpea and limit its adaptation. The adverse effects of chilling temperature and frost in terms of the threshold temperatures, impact of cold duration, and genotype-by-environment-by-management interactions are not well quantified. Crop growth models that predict flowering time and yield under diverse climates can identify combinations of cultivars and sowing time to reduce frost risk in target environments. The Agricultural Production Systems Simulator (APSIM-chickpea) model uses daily temperatures to model basic crop growth but does not include penalties for either frost damage or cold temperatures during flowering and podding stages. Regression analysis overcame this limitation of the model for chickpea crops grown at 95 locations in Australia using 70 years of historic data incorporating three cultivars and three sowing times (early, mid, and late). We modified model parameters to include the effect of soil water on thermal time calculations, which significantly improved the prediction of flowering time. Simulated data, and data from field experiments grown in Australia (2013 to 2019), showed robust predictions for flowering time (n = 29; R2 = 0.97), and grain yield (n = 22; R2 = 0.63–0.70). In addition, we identified threshold cold temperatures that significantly affected predicted yield, and combinations of locations, variety, and sowing time where the overlap between peak cold temperatures and peak flowering was minimal. Our results showed that frost and/or cold temperature–induced yield losses are a major limitation in some unexpected Australian locations, e.g., inland, subtropical latitudes in Queensland. Intermediate sowing maximise yield, as it avoids cold temperature, late heat, and drought stresses potentially limiting yield in early and late sowing respectively.

Plant breeding programs use multi-environment trial (MET) data to select superior lines, with the ultimate aim of increasing genetic gain. Selection accuracy can be improved with the use of advanced statistical analysis methods that employ informative models for genotype by environment interaction, include information on genetic relatedness and appropriately accommodate within-trial error variation. The gains will only be achieved, however, if the methods are applied to suitable MET datasets. In this paper we present an approach for constructing MET datasets that optimizes the information available for selection decisions. This is based on two new concepts that characterize the structure of a breeding program. The first is that of “contemporary groups,” which are defined to be groups of lines that enter the initial testing stage of the breeding program in the same year. The second is that of “data bands,” which are sequences of trials that correspond to the progression through stages of testing from year to year. MET datasets are then formed by combining bands of data in such a way as to trace the selection histories of lines within contemporary groups. Given a specified dataset, we use the A-optimality criterion from the model-based design literature to quantify the information for any given selection decision. We demonstrate the methods using two motivating examples from a durum and chickpea breeding program. Datasets constructed using contemporary groups and data bands are shown to be superior to other forms, in particular those that relate to a single year alone.

Ascochyta blight disease, caused by the necrotrophic fungusAscochyta 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 agro-geographically distinct regions.Thanks to continuous monitoring efforts over the past six years, a comprehensive collection ofA. rabieiisolates was collated from the major Australian production regions. To determine the molecular structure of the entire population, representative isolates from each collection year and growing region have been genetically characterised 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 AustralianA. rabieipopulation 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.To better understand the mechanisms and patterns of the pathogen adaptation, multi-locus genotype analysis was performed and two hypotheses were proposed on how new genotypes emerge. These were: 1) In a local, within-region evolutionary pathway; or 2) Through inter-region dispersal, most likely due to human activities. Furthermore, a cluster of genetically similar isolates was identified, with a higher proportion of highly aggressive isolates than in the general population, indicating the adaptive evolution of a sub-set of isolates that pose a greater risk to the chickpea industry.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 AustralianA. rabieipopulation. 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.Data SummaryAn online dataset containing all supporting genotyping and phenotyping data and the code required to reproduce the results, summary tables and plots found in this publication, is publicly available at Zenodo via the following links:https://zenodo.org/record/4311477; DOI:10.5281/zenodo.4311477(1).

Ascochyta Blight (AB), caused by Ascochyta rabiei (syn Phoma rabiei), is the major endemic foliar fungal disease affecting the Australian chickpea industry, resulting with potential crop loss and management costs. This study was conducted to better understand the risk posed by the Australian A. rabiei population to current resistance sources and to provide informed decision support for chemical control strategies. Recent changes in the pathogenicity of the population were proposed based on disease severity and histopathological observations on a host set. Controlled environment disease screening of 201 isolates on the host set revealed distinct pathogenicity groups, with 41% of all isolates assessed as highly aggressive and a significant increase in the proportion of isolates able to cause severe damage on resistant and moderately resistant cultivars since 2013. In particular, the frequency of highly aggressive isolates on the widely adopted PBA HatTrick cultivar rose from 18% in 2013 to 68% in 2017. In addition, isolates collected since 2016 caused severe disease on Genesis 090, another widely adopted moderately resistant cultivar and on ICC3996, a commonly used resistance source. Of immediate concern was the 10% of highly aggressive isolates able to severely damage the recently released resistant cultivar PBA Seamer (2016). Histopathology studies revealed that the most aggressive isolates were able to germinate, develop appressoria and invade directly through the epidermis faster than lower aggressive isolates on all hosts assessed, including ICC3996. The fungal invasion triggered a common reactive oxygen species (ROS) and hypersensitive response (HR) on all assessed resistant genotypes with initial biochemical and subsequent structural defence responses initiated within 24 hours of inoculation by the most highly aggressive isolates. These responses were much faster on the less resistant and fastest on the susceptible check host, indicating that speed of recognition was correlated with resistance rating. This will inform fungicide application timing so that infected crops are sprayed with prophylactic chemistries prior to invasion and with systemic chemistries after the pathogen has invaded.

Desi chickpea is a significant export crop for Australia; Australia being the largest exporter globally. Visual appearance of the seed is an economically significant measure of seed quality by the Indian subcontinent, the major importer of desi chickpea worldwide. Any visual blemish on the seed is considered undesirable, regardless of the cause (biotic or otherwise). Literature on biotic causes of seed blemishes, such as ascochyta blight, are available; however, little could be found on abiotic blemishes. Abiotic seed blemishes caused by physiological plant responses are more commonly known as seed markings. Despite the presence of seed markings being confirmed by several chickpea‐producing countries during personal discussions (India, Canada), no scientific literature has been published. The aim of this study was to proactively seek out and characterise different types of seed marking patterns using a wide genetic pool of desi chickpea across a range of environments in Australia. Thirteen different seed marking patterns were identified in desi chickpea and three in kabuli chickpea, including several rare seed markings that were discovered, photographed, and described. Seed markings (blemishes thought to be caused by physiological plant stress) can be characterised as dark patterns on the testa (seed coat) that do not visually affect the underlying cotyledon. In contrast, other seed blemishes (caused by pests and disease, physical damage, or poor storage) were more likely to affect the cotyledons underlying the testa, but not always. This paper classifies and describes various types of seed markings and blemishes for future reference by the global chickpea industry.

Chickpea production in Australia is constrained by both waterlogging and the root disease Phytophthora root rot (PRR). Soil saturation is an important pre-condition for significant disease development for many soil-borne Phytophthora spp. In wet years, water can pool in low lying areas within a field, resulting in waterlogging, which, in the presence of PRR, can result in a significant yield loss for Australian chickpea varieties. In these circumstances, the specific cause of death is often difficult to discern, as the damage is rapid and the spread of PRR can be explosive in nature. The present study describes the impact of soil waterlogging on oxygen availability and the ability of P. medicaginis to infect chickpea plants. Late waterlogging in combination with PRR reduced the total plant biomass by an average of 94%; however, waterlogging alone accounted for 88% of this loss across three reference genotypes. Additional experiments found that under hypoxic conditions associated with waterlogging, P. medicaganis did not proliferate as determined by zoospore counts and DNA detection using qPCR. Consequently, minimizing waterlogging damage through breeding and agronomic practices should be a key priority for integrated disease management, as waterlogging alone results in plant stunting, yield loss and a reduced resistance to PRR.

Major QTL for Phytophthora root rot resistance have been identified in three mapping populations with independent sources of resistance contributed by C. echinospermum and C. arietinum. Phytophthora root rot (PRR) caused by the oomycete Phytophthora medicaginis is a major soil-borne disease of chickpea in Australia. With no economic in-crop control of PRR, a genetic approach to improve resistance is the most practical management option. Moderate field resistance has been incorporated in the cultivated C. arietinum variety, Yorker, and a higher level of resistance has been identified in a derivative of wild chickpea (C. echinospermum, interspecific breeding line 04067-81-2-1-1). These genotypes and two other released varieties were used to develop one intra-specific and two interspecific F6-derived recombinant inbred line mapping populations for genetic analysis of resistance. The Yorker × Genesis114 (YG), Rupali × 04067-81-2-1-1 (RB) and Yorker × 04067-81-2-1-1 (YB) populations were genotyped using genotyping-by-sequencing and phenotyped for PRR under three field environments with a mixture of 10 P. medicaginis isolates. Whole-genome QTL analysis identified major QTL QRBprrsi01, QYBprrsi01, QRBprrsi03 and QYBprrsi02 for PRR resistance on chromosomes 3 and 6, in RB and YB populations, respectively, with the resistance source derived from the wild Cicer species. QTL QYGprrsi02 and QYGprrsi03 were also identified on chromosomes 5 and 6 in YG population from C. arietinum. Aligning QTL regions to the corresponding chickpea reference genome suggested that the resistance source from C. arietinum and C. echinospermum may be different. The findings from this study provide tools for marker-assisted selection in chickpea breeding and information to assist the development of populations suitable for fine-mapping of resistance loci to determine the molecular basis for PRR resistance in chickpea.

Chickpea (Cicer arietinum L.) is the third most economically important food legume in the world. Its yield potential is often limited by various biotic stresses, including fungal and viral diseases, insects, nematodes and parasitic weeds. Incorporating genetic resistance into cultivars is the most effective and economical way of controlling biotic stresses and this is a major objective in many breeding programs. Extensive searches for resistances have been conducted by screening commercial varieties, landraces and closely related species. Resistances to disease such as Ascochyta blight and Fusarium wilt have been identified and molecular tools are being used to increase the efficiency of gene transfer from wild species into chickpea elite genotypes. Quantitative trait loci for resistance genes have been located on linkage maps and molecular markers associated with these loci can potentially be used for efficient pyramiding of the traits. Significant chickpea genomic resources have been developed in order to investigate resistance genes. Such resources include an integrated genetic map, expressed sequence tag libraries, bacterial artificial chromosome libraries, microarrays and draft genome sequences. Although these resources have yet to be used to improve chickpea cultivars in the field, this is likely to change in the near future. These genomic resources, as well as high-resolution phenotyping tools and cutting-edge technologies such as next-generation sequencing, promise to increase efficiency as work to identify valuable candidate genes continues.

The Australian Ascochyta rabiei (Pass.) Labr. (syn. Phoma rabiei) population has low genotypic diversity with only one mating type detected to date, potentially precluding substantial evolution through recombination. However, a large diversity in aggressiveness exists. In an effort to better understand the risk from selective adaptation to currently used resistance sources and chemical control strategies, the population was examined in detail. For this, a total of 598 isolates were quasi-hierarchically sampled between 2013 and 2015 across all major Australian chickpea growing regions and commonly grown host genotypes. Although a large number of haplotypes were identified (66) through short sequence repeat (SSR) genotyping, overall low gene diversity (Hexp = 0.066) and genotypic diversity (D = 0.57) was detected. Almost 70% of the isolates assessed were of a single dominant haplotype (ARH01). Disease screening on a differential host set, including three commonly deployed resistance sources, revealed distinct aggressiveness among the isolates, with 17% of all isolates identified as highly aggressive. Almost 75% of these were of the ARH01 haplotype. A similar pattern was observed at the host level, with 46% of all isolates collected from the commonly grown host genotype Genesis090 (classified as “resistant” during the term of collection) identified as highly aggressive. Of these, 63% belonged to the ARH01 haplotype. In conclusion, the ARH01 haplotype represents a significant risk to the Australian chickpea industry, being not only widely adapted to the diverse agro-geographical environments of the Australian chickpea growing regions, but also containing a disproportionately large number of aggressive isolates, indicating fitness to survive and replicate on the best resistance sources in the Australian germplasm.

The Australian Ascochyta rabiei (Pass.) Labr. (syn. Phoma rabiei) population has low genotypic diversity with only one mating type detected to date, potentially precluding substantial evolution through recombination. However, a large diversity in aggressiveness exists. In an effort to better understand the risk from selective adaptation to currently used resistance sources and chemical control strategies, the population was examined in detail. For this, a total of 598 isolates were quasi-hierarchically sampled between 2013 and 2015 across all major Australian chickpea growing regions and commonly grown host genotypes. Although a large number of haplotypes were identified (66) through short sequence repeat (SSR) genotyping, overall low gene diversity (Hexp = 0.066) and genotypic diversity (D = 0.57) was detected. Almost 70% of the isolates assessed were of a single dominant haplotype (ARH01). Disease screening on a differential host set, including three commonly deployed resistance sources, revealed distinct aggressiveness among the isolates, with 17% of all isolates identified as highly aggressive. Almost 75% of these were of the ARH01 haplotype. A similar pattern was observed at the host level, with 46% of all isolates collected from the commonly grown host genotype Genesis090 (classified as “resistant” during the term of collection) identified as highly aggressive. Of these, 63% belonged to the ARH01 haplotype. In conclusion, the ARH01 haplotype represents a significant risk to the Australian chickpea industry, being not only widely adapted to the diverse agro-geographical environments of the Australian chickpea growing regions, but also containing a disproportionately large number of aggressive isolates, indicating fitness to survive and replicate on the best resistance sources in the Australian germplasm.

Ascochyta blight (AB) is a fungal disease that can significantly reduce chickpea production in Australia and other regions of the world. In this study, 69 chickpea genotypes were sequenced using whole genome re-sequencing (WGRS) methods. They included 48 Australian varieties differing in their resistance ranking to AB, 16 advanced breeding lines from the Australian chickpea breeding program, four landraces, and one accession representing the wild chickpea species Cicer reticulatum. More than 800,000 single nucleotide polymorphisms (SNPs) were identified. Population structure analysis revealed relatively narrow genetic diversity amongst recently released Australian varieties and two groups of varieties separated by the level of AB resistance. Several regions of the chickpea genome were under positive selection based on Tajima’s D test. Both Fst genome- scan and genome-wide association studies (GWAS) identified a 100 kb region (AB4.1) on chromosome 4 that was significantly associated with AB resistance. The AB4.1 region co-located to a large QTL interval of 7 Mb∼30 Mb identified previously in three different mapping populations which were genotyped at relatively low density with SSR or SNP markers. The AB4.1 region was validated by GWAS in an additional collection of 132 advanced breeding lines from the Australian chickpea breeding program, genotyped with approximately 144,000 SNPs. The reduced level of nucleotide diversity and long extent of linkage disequilibrium also suggested the AB4.1 region may have gone through selective sweeps probably caused by selection of the AB resistance trait in breeding. In total, 12 predicted genes were located in the AB4.1 QTL region, including those annotated as: NBS-LRR receptor-like kinase, wall-associated kinase, zinc finger protein, and serine/threonine protein kinases. One significant SNP located in the conserved catalytic domain of a NBS-LRR receptor-like kinase led to amino acid substitution. Transcriptional analysis using qPCR showed that some predicted genes were significantly induced in resistant lines after inoculation compared to non-inoculated plants. This study demonstrates the power of combining WGRS data with relatively simple traits to rapidly develop “functional makers” for marker-assisted selection and genomic selection.

Ascochyta blight, caused by the fungus Ascochyta rabiei (Pass.) Labr., is a highly destructive disease of chickpea (Cicer arietinum L.) on a global basis, and exhibits considerable natural variation for pathogenicity. Different sources of ascochyta blight resistance are available within the cultivated species, suitable for pyramiding to improve field performance. Robust and closely linked genetic markers are desirable to facilitate this approach. A total of 4,654 simple sequence repeat (SSR) and 1,430 single nucleotide polymorphism (SNP) markers were identified from a chickpea expressed sequence tag (EST) database. Subsets of 143 EST–SSRs and 768 SNPs were further used for validation and subsequent high-density genetic mapping of two intraspecific mapping populations (Lasseter × ICC3996 and S95362 × Howzat). Comparison of the linkage maps to the genome of Medicago truncatula revealed a high degree of conserved macrosynteny. Based on field evaluation of ascochyta blight incidence performed over 2 years, two genomic regions containing resistance determinants were identified in the Lasseter × ICC3996 family. In the S95362 × Howzat population, only one quantitative trait locus (QTL) region was identified for both phenotypic evaluation trials, which on the basis of bridging markers was deduced to coincide with one of the Lasseter × ICC3996 QTLs. Of the two QTL-containing regions identified in this study, one (ab_QTL1) was predicted to be in common with QTLs identified in prior studies, while the other (ab_QTL2) may be novel. Markers in close linkage to ascochyta blight resistance genes that have been identified in this study can be further validated and effectively implemented in chickpea breeding programs.

For lentil production to expand further in Australia, adaptation to the less favourable soils of the low to medium rainfall zones is required. To improve adaptation to these regions, varieties are required with increased tolerance to soil constraints such as high concentrations of boron (B), salinity and sodicity. To evaluate the range of B tolerance in lentil germplasm, 310 lines were screened in soil with a high concentration of B and tolerance was assessed at the seedling stage. A wide range in response to high concentrations of soil B was observed in the germplasm tested. Current Australian varieties were generally very intolerant to high concentrations of soil B. High levels of B tolerance was identified in germplasm originating from Afghanistan and Ethiopia. A subsequent experiment comparing lentils with different levels of B tolerance found that tolerant accessions (ILL213A and ILL2024) produced greater above and below ground biomass than intolerant accessions. The tolerant accessions had no significant yield loss under a high B treatment (extractable B = 18.20 mg/kg) compared to the control treatment (extractable B = 1.55 mg/kg). The large improvement in B tolerance, at soil concentrations typical of those found in the target regions, suggests there is potential to improve the tolerance level of adapted varieties and expand lentil production areas to regions with higher concentrations of soil B.

A global collection of 43 chickpea (Cicer arietinum L.) genotypes, resistant and susceptible to Ascochyta blight caused by Ascochyta rabiei was evaluated for the disease under controlled conditions. In this study three known pathotypes (P-I, P-II, and P-III) were used to evaluate the reactions of this collection. the chickpea genotypes were also characterized using 14 microsatellite markers flanking the genomic regions associated with Ascochyta blight resistance quantitative trait loci (QTLs). Phenotyping results indicated that 27 genotypes were re- sistant to P-I, 14 to P-II, and five to P-III, revealing the possible erosion of resistance through the evolution of virulent pathogen pathotypes. the genetic diversity analysis revealed 67 alleles at 14 microsatellite loci with an average of 4.8 alleles per locus among the genotypes tested. Genetic similarity estimates differentiated four subclusters (A, B, C, and D) of the genotypes. However, none of sub-clusters were separated into resistant genotypes for a specific pathotype. The genetic diversity ranged from 0.48 to 0.80 which indicated that there is considerable variation in QTL regions associated with Ascochyta blight resistance among the collections of chickpea genotypes studied, as assessed using the hyper-variable microsatellite markers.