Selection for Phytophthora Root Rot Resistance in Chickpea Crosses Affects Yield Potential of Chickpea × Cicer echinospermum Backcross Derivatives.

Phytophthora root rot (PRR) of chickpea (Cicer arietinum) caused by Phytophthora medicaginis is an important disease. Partial resistance to PRR is sourced from Cicer echinospermum. In this study, we evaluated if lines with low levels of PRR foliage symptoms in two contrasting recombinant inbred line (RIL) populations parented by chickpea cultivars (Yorker and Rupali) and 04067-81-2-1-1 (C. echinospermum, interspecific breeding line) had a significant drag on yield parameters. For the Yorker × 04067-81-2-1-1 population with the highest level of PRR resistance, in the absence of PRR, low foliage symptom RIL had significantly later flowering and podding, lower grain yields, and lighter seed and shorter plant phenotypes than high foliage symptom RIL. A quantitative trait locus analysis identified significant QTL for flowering, height, 100-seed weight, and yield, and there was a significantly higher frequency of alleles for the negative agronomic traits (i.e., drag) from the 04067-81-2-1-1 parent in low foliage symptom RIL than in high foliage symptom RIL. For the Rupali × 04067-81-2-1-1 population with lower levels of PRR resistance, in the absence of PRR, low foliage symptom RIL had significantly lighter seed and shorter plants than high foliage symptom RIL. Significant QTL were detected, the majority were for the timing of flowering and podding (n = 18), others were for plant height, yield, and 100-seed weight. For this second population, the frequency of alleles for the negative agronomic traits from the 04067-81-2-1-1 parent did not differ between low and high foliage symptom RIL. The 100 seed weight of RIL under moderate PRR disease pressure showed some promise as a yield component trait to identify phenotypes with both high levels of PRR resistance and grain yield potential for further seed number evaluations. We identified that large population sizes are required to enable selection among chickpea × C. echinospermum crosses for high levels of PRR resistance without a significant drag on yield.

Rapid and High Throughput Hydroponics Phenotyping Method for Evaluating Chickpea Resistance to Phytophthora Root Rot.

Phytophthora root rot (PRR) is a major constraint to chickpea production in Australia. Management options for controlling the disease are limited to crop rotation and avoiding high risk paddocks for planting. Current Australian cultivars have partial PRR resistance, and new sources of resistance are needed to breed cultivars with improved resistance. Field- and glasshouse-based PRR resistance phenotyping methods are labour intensive, time consuming, and provide seasonally variable results; hence, these methods limit breeding programs' abilities to screen large numbers of genotypes. In this study, we developed a new space saving (400 plants/m2), rapid (<12 days), and simplified hydroponics-based PRR phenotyping method, which eliminated seedling transplant requirements following germination and preparation of zoospore inoculum. The method also provided post-phenotyping propagation all the way through to seed production for selected high-resistance lines. A test of 11 diverse chickpea genotypes provided both qualitative (PRR symptoms) and quantitative (amount of pathogen DNA in roots) results demonstrating that the method successfully differentiated between genotypes with differing PRR resistance. Furthermore, PRR resistance hydroponic assessment results for 180 recombinant inbred lines (RILs) were correlated strongly with the field-based phenotyping, indicating the field phenotype relevance of this method. Finally, post-phenotyping high-resistance genotypes were selected. These were successfully transplanted and propagated all the way through to seed production; this demonstrated the utility of the rapid hydroponics method (RHM) for selection of individuals from segregating populations. The RHM will facilitate the rapid identification and propagation of new PRR resistance sources, especially in large breeding populations at early evaluation stages.

Inoculum production of Phytophthora medicaginis can be used to screen for partial resistance in chickpea genotypes.

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.

Genome-Wide Association Analyses Track Genomic Regions for Resistance to Ascochyta rabiei in Australian Chickpea Breeding Germplasm.

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.

Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.).

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.

Genomic prediction of preliminary yield trials in chickpea: Effect of functional annotation of SNPs and environment.

Achieving yield potential in chickpea (Cicer arietinum L.) is limited by many constraints that include biotic and abiotic stresses. Combining next-generation sequencing technology with advanced statistical modeling has the potential to increase genetic gain efficiently. Whole genome resequencing data was obtained from 315 advanced chickpea breeding lines from the Australian chickpea breeding program resulting in more than 298,000 single nucleotide polymorphisms (SNPs) discovered. Analysis of population structure revealed a distinct group of breeding lines with many alleles that are absent from recently released Australian cultivars. Genome-wide association studies (GWAS) using these Australian breeding lines identified 20 SNPs significantly associated with grain yield in multiple field environments. A reduced level of nucleotide diversity and extended linkage disequilibrium suggested that some regions in these chickpea genomes may have been through selective breeding for yield or other traits. A large introgression segment that introduced from C. echinospermum for phytophthora root rot resistance was identified on chromosome 6, yet it also has unintended consequences of reducing yield due to linkage drag. We further investigated the effect of genotype by environment interaction on genomic prediction of yield. We found that the training set had better prediction accuracy when phenotyped under conditions relevant to the targeted environments. We also investigated the effect of SNP functional annotation on prediction accuracy using different subsets of SNPs based on their genomic locations: regulatory regions, exome, and alternative splice sites. Compared with the whole SNP dataset, a subset of SNPs did not significantly decrease prediction accuracy for grain yield despite consisting of a smaller number of SNPs.

The genetics of vigour-related traits in chickpea (Cicer arietinum L.): insights from genomic data.

KEY MESSAGE: 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.

Evidence for the Application of Emerging Technologies to Accelerate Crop Improvement - A Collaborative Pipeline to Introgress Herbicide Tolerance Into Chickpea.

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.

Current population structure and pathogenicity patterns of Ascochyta rabiei in Australia.

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.

Use of Contemporary Groups in the Construction of Multi-Environment Trial Datasets for Selection in Plant Breeding Programs.

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.

Mapping resistance to Phytophthora root rot identifies independent loci from cultivated (Cicer arietinum L.) and wild (Cicer echinospermum P.H. Davis) chickpea.

KEY MESSAGE: 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.

Evidence and Consequence of a Highly Adapted Clonal Haplotype within the Australian Ascochyta rabiei Population.

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.

Genome Analysis Identified Novel Candidate Genes for Ascochyta Blight Resistance in Chickpea Using Whole Genome Re-sequencing Data.

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.