Phenotypic plasticity and its genetic regulation for yield, nitrogen fixation and δ13C in chickpea crops under varying water regimes

Advancing Chickpea Breeding: Omics Insights for Targeted Abiotic Stress Mitigation and Genetic Enhancement

Chickpea is a major source of proteins and is considered the most economically vital food legume. Chickpea production is threatened by several abiotic and biotic factors worldwide. The main constraints limiting worldwide chickpea production are abiotic conditions such as drought, heat, salinity, and cold. It is clear that chickpea is treasured for its nutritive value, in particular its high protein content, and hence study of problems like drought, cold and salinity stresses are very important concerning chickpeas. In this regard, several physiological, biochemical, and molecular mechanisms are reviewed to confer tolerance to abiotic stress. The most crippling economic losses in agriculture occur due to these abiotic stressors, which affect plants in many ways. All these abiotic stresses affect the water relations of the plant, both at the cellular level as well as the whole-plant level, causing both specific and non-specific reactions, damage and adaptation reactions. These stresses share common features. Breeding programs use a huge collection of over 100,000 chickpea accessions as their foundation. Significant advancements in conventional breeding, including mutagenesis, gene/allele introgression, and germplasm introduction, have been made through this method. Abiotic tolerance and yield component selection are made easier by creating unique DNA markers for the genus Cicer, which has been made possible by developments in high-throughput sequencing and molecular biology. Transcriptomics, proteomics, and metabolomics have also made it possible to identify particular genes, proteins, and metabolites linked to chickpea tolerance to abiotic stress. Chickpea abiotic stress tolerance has been directly and potentially improved by biotechnological applications, which are covered by all 'Omics' approaches. It requires information on the abiotic stress response at the different molecular levels, which comprises gene expression analysis for metabolites or proteins and its impact on phenotype. Studies on chickpea genome-wide expression profiling have been conducted to determine important candidate genes and their regulatory networks for abiotic stress response. This study aimed to offer a detailed overview of the diverse 'Omics' approaches for resilience's to abiotic stresses on chickpea plants.

Impact of low light intensity on biomass partitioning and genetic diversity in a chickpea mapping population

With recent climatic changes, the reduced access to solar radiation has become an emerging threat to chickpeas' drought tolerance capacity under rainfed conditions. This study was conducted to assess, and understand the effects of reduced light intensity and quality on plant morphology, root development, and identifying resistant sources from a Sonali/PBA Slasher mapping population. We evaluated 180 genotypes, including recombinant inbred lines (RILs), parents, and commercial checks, using a split-block design with natural and low light treatments. Low light conditions, created by covering one of the two benches inside two growth chambers with a mosquito net, reduced natural light availability by approximately 70%. Light measurements encompassed photosynthetic photon flux density, as well as red, and far-red light readings taken at various stages of the experiment. The data, collected from plumule emergence to anthesis initiation, encompassed various indices relevant to root, shoot, and carbon gain (biomass). Statistical analysis examined variance, treatment effects, heritability, correlations, and principal components (PCs). Results demonstrated significant reductions in root biomass, shoot biomass, root/shoot ratio, and plant total dry biomass under suboptimal light conditions by 52.8%, 28.2%, 36.3%, and 38.4%, respectively. Plants also exhibited delayed progress, taking 9.2% longer to produce their first floral buds, and 19.2% longer to commence anthesis, accompanied by a 33.4% increase in internodal lengths. A significant genotype-by-environment interaction highlighted differing genotypic responses, particularly in traits with high heritability (> 77.0%), such as days to anthesis, days to first floral bud, plant height, and nodes per plant. These traits showed significant associations with drought tolerance indicators, like root, shoot, and plant total dry biomass. Genetic diversity, as depicted in a genotype-by-trait biplot, revealed contributions to PC1 and PC2 coefficients, allowing discrimination of low-light-tolerant RILs, such as 1_52, 1_73, 1_64, 1_245, 1_103, 1_248, and 1_269, with valuable variations in traits of interest. These RILs could be used to breed desirable chickpea cultivars for sustainable production under water-limited conditions. This study concludes that low light stress disrupts the balance between root and shoot morphology, diverting photosynthates to vegetative structures at the expense of root development. Our findings contribute to a better understanding of biomass partitioning under limited-light conditions, and inform breeding strategies for improved drought tolerance in chickpeas.

Genome-wide discovery of di-nucleotide SSR markers based on whole genome re-sequencing data of Cicer arietinum L. and Cicer reticulatum Ladiz

Simple sequence repeats (SSRs) are valuable genetic markers due to their co-dominant inheritance, multi-allelic and reproducible nature. They have been largely used for exploiting genetic architecture of plant germplasms, phylogenetic analysis, and mapping studies. Among the SSRs, di-nucleotide repeats are the most frequent of the simple repeats distributed throughout the plant genomes. In present study, we aimed to discover and develop di-nucleotide SSR markers by using the whole genome re-sequencing (WGRS) data from Cicer arietinum L. and C. reticulatum Ladiz. A total of 35,329 InDels were obtained in C. arietinum, whereas 44,331 InDels in C. reticulatum. 3387 InDels with 2 bp length were detected in C. arietinum, there were 4704 in C. reticulatum. Among 8091 InDels, 58 di-nucleotide regions that were polymorphic between two species were selected and used for validation. We tested primers for evaluation of genetic diversity in 30 chickpea genotypes including C. arietinum, C. reticulatum, C. echinospermum P.H. Davis, C. anatolicum Alef., C. canariense A. Santos & G.P. Lewis, C. microphyllum Benth., C. multijugum Maesen, C. oxyodon Boiss. & Hohen. and C. songaricum Steph ex DC. A total of 244 alleles were obtained for 58 SSR markers giving an average of 2.36 alleles per locus. The observed heterozygosity was 0.08 while the expected heterozygosity was 0.345. Polymorphism information content was found to be 0.73 across all loci. Phylogenetic tree and principal coordinate analysis clearly divided the accessions into four groups. The SSR markers were also evaluated in 30 genotypes of a RIL population obtained from an interspecific cross between C. arietinum and C. reticulatum. Chi-square (χ²) test revealed an expected 1:1 segregation ratio in the population. These results demonstrated the success of SSR identification and marker development for chickpea with the use of WGRS data. The newly developed 58 SSR markers are expected to be useful for chickpea breeders.

Explaining pre-emptive acclimation by linking information to plant phenotype

We review mechanisms for pre-emptive acclimation in plants and propose a conceptual model linking developmental and evolutionary ecology with the acquisition of information through sensing of cues and signals. The idea is that plants acquire much of the information in the environment not from individual cues and signals but instead from their joint multivariate properties such as correlations. If molecular signalling has evolved to extract such information, the joint multivariate properties of the environment must be encoded in the genome, epigenome, and phenome. We contend that multivariate complexity explains why extrapolating from experiments done in artificial contexts into natural or agricultural systems almost never works for characters under complex environmental regulation: biased relationships among the state variables in both time and space create a mismatch between the evolutionary history reflected in the genotype and the artificial growing conditions in which the phenotype is expressed. Our model can generate testable hypotheses bridging levels of organization. We describe the model and its theoretical bases, and discuss its implications. We illustrate the hypotheses that can be derived from the model in two cases of pre-emptive acclimation based on correlations in the environment: the shade avoidance response and acclimation to drought.

Genetic basis and adaptive implications of temperature-dependent and temperature-independent effects of drought on chickpea reproductive phenology

Water deficit often hastens flowering of pulses partially because droughted plants are hotter. Separating temperature-independent and temperature-dependent effects of drought is important to understand, model, and manipulate phenology. We define a new trait, drought effect on phenology (DEP), as the difference in flowering time between irrigated and rainfed crops, and use FST genome scanning to probe for genomic regions under selection for this trait in chickpea (Cicer arietinum). Owing to the negligible variation in daylength in our dataset, variation in phenology with sowing date was attributed to temperature and water; hence, genomic regions overlapping for early- and late-sown crops would associate with temperature-independent effects and non-overlapping genomic regions would associate with temperature-dependent effects. Thermal-time to flowering was shortened with increasing water stress, as quantified with carbon isotope composition. Genomic regions on chromosomes 4-8 were under selection for DEP. An overlapping region for early and late sowing on chromosome 8 revealed a temperature-independent effect with four candidate genes: BAM1, BAM2, HSL2, and ANT. The non-overlapping regions included six candidate genes: EMF1, EMF2, BRC1/TCP18, BZR1, NPGR1, and ERF1. Modelling showed that DEP reduces the likelihood of drought and heat stress at the expense of increased likelihood of cold stress. Accounting for DEP would improve genetic and phenotypic models of phenology.

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.

Neighbors, Drought, and Nitrogen Application Affect the Root Morphological Plasticity of Dalbergia odorifera

In forest systems, neighbor-induced root morphological plasticity (RMP) is species specific and environment dependent. However, related studies on leguminous woody trees remain sparse. The objectives of this study were to evaluate the root morphological response of the leguminous woody Dalbergia odorifera T. Chen to different N-fixing niche neighbors under models of root system contact and isolation and to evaluate whether such response can be modified by drought or the application of nitrogen (N). The relationship between root morphology and the relative competitiveness of the whole D. odorifera plantlet was also assessed. D. odorifera plantlets from the woody Leguminosae family were used as target species and were grown with either identical N-fixing niche D. odorifera, the heterogeneous but con-leguminous Delonix regia, or the non-leguminous Swietenia mahagoni. All plants were grown under two water conditions (100% and 30% field capacity) and two N treatments (no N application and N application). Two planting models (root system contact in Experiment 1, root system isolation in Experiment 2) were applied to neighboring plantlets. The RMP of D. odorifera was assessed based on root morphology, root system classification, root nodules, and RMP-related indices. The growth of D. odorifera was estimated based on the relative growth ratio, net assimilation rate, and leaf N content. The relative competitiveness of the whole D. odorifera plantlet was evaluated through relative yield. The results of Experiment 1 showed that D. odorifera had different RMP responses to a different N-fixing niche neighbor with root system contact. The RMP of D. odorifera was promoted by a different N-fixing niche neighbor under conditions of drought or N deficiency. Drought improved the RMP of D. odorifera exposed to a different N-fixing niche neighbor. N application converted the promoting effect of D. regia on RMP to an inhibitory effect under well-watered conditions. Experiment 2 showed that belowground interaction with a different N-fixing niche neighbor may be the only way to influence RMP, as effects of aboveground interaction were negligible. Finally, correlation analysis showed that neighbor-induced RMP might predict the relative competitiveness of the whole D. odorifera plantlet under conditions of drought or N deficiency. These findings highlight the influences of neighbors, drought, and N application on the RMP of D. odorifera and contribute to understanding neighbor-induced dynamic changes in the root traits of leguminous woody species in forest systems in the context of climate change.

Genomic-based root plasticity to enhance abiotic stress adaptation and edible yield in grain crops

Phenotypic plasticity refers to changes expressed by a genotype across different environments and is one of the major means by which plants cope with environmental variability. Multi-fold differences in phenotypic plasticity have been noted across crops, with wild ancestors and landraces being more plastic than crops when under stress. Plasticity in response to abiotic stress adaptation, plant architecture, physio-reproductive and quality traits are multi-genic (QTL). Plasticity QTL (pQTL) were either collocated with main effect QTL and QEI (QTL × environment interaction) or located independently from the main effect QTL. For example, variations in root plasticity have been successfully introgressed to enhance abiotic stress adaptation in rice. The independence of genetic control of a trait and of its plasticity suggests that breeders may select for high or low plasticity in combination with high or low performance of economically important traits. Trait plasticity in stressful environments may be harnessed through breeding stress-tolerant crops. There exists a genetic cost associated with plasticity, so a better understanding of the trade-offs between plasticity and productivity is warranted prior to undertaking breeding for plasticity traits together with productivity in stress environments.

Source-Sink Relationships in Crop Plants and Their Influence on Yield Development and Nutritional Quality

For seed crops, yield is the cumulative result of both source and sink strength for photoassimilates and nutrients over the course of seed development. Source strength for photoassimilates is dictated by both net photosynthetic rate and the rate of photoassimilate remobilisation from source tissues. This review focuses on the current understanding of how the source-sink relationship in crop plants influences rates of yield development and the resilience of yield and nutritional quality. We present the limitations of current approaches to accurately measure sink strength and emphasize differences in coordination between photosynthesis and yield under varying environmental conditions. We highlight the potential to exploit source-sink dynamics, in order to improve yields and emphasize the importance of resilience in yield and nutritional quality with implications for plant breeding strategies.

Interplay between nitrogen fertilizer and biological nitrogen fixation in soybean: implications on seed yield and biomass allocation

Legumes rely on soil mineral nitrogen (N) and biological N fixation (BNF). The interplay between these two sources is biologically interesting and agronomically relevant as the crop can accommodate the cost of BNF by five non-mutually exclusive mechanisms, whereby BNF: reduces shoot growth and seed yield, or maintains shoot growth and seed yield by enhanced photosynthesis, or reduced root:shoot ratio, or maintains shoot growth but reduces seed yield by reducing the fraction of shoot biomass allocated to seed (harvest index), or reducing concentration of oil and protein in seed. We explore the impact of N application on the seasonal dynamics of BNF, and its consequences for seed yield with emphasis on growth and shoot allocation mechanisms. Trials were established in 23 locations across the US Midwest under four N conditions. Fertilizer reduced the peak of BNF up to 16% in applications at the full flowering stage. Seed yield declined 13 kg ha^-1 per % increase in RAU_R6. Harvest index accounted for the decline in seed yield with increasing BNF. This indicates the cost of BNF was met by a relative change in dry matter allocation against the energetically rich seed, and in favor of energetically cheaper vegetative tissue.

Interplay between nitrogen fertilizer and biological nitrogen fixation in soybean: implications on seed yield and biomass allocation

Legumes rely on soil mineral nitrogen (N) and biological N fixation (BNF). The interplay between these two sources is biologically interesting and agronomically relevant as the crop can accommodate the cost of BNF by five non-mutually exclusive mechanisms, whereby BNF: reduces shoot growth and seed yield, or maintains shoot growth and seed yield by enhanced photosynthesis, or reduced root:shoot ratio, or maintains shoot growth but reduces seed yield by reducing the fraction of shoot biomass allocated to seed (harvest index), or reducing concentration of oil and protein in seed. We explore the impact of N application on the seasonal dynamics of BNF, and its consequences for seed yield with emphasis on growth and shoot allocation mechanisms. Trials were established in 23 locations across the US Midwest under four N conditions. Fertilizer reduced the peak of BNF up to 16% in applications at the full flowering stage. Seed yield declined 13 kg ha-1 per % increase in RAUR6. Harvest index accounted for the decline in seed yield with increasing BNF. This indicates the cost of BNF was met by a relative change in dry matter allocation against the energetically rich seed, and in favor of energetically cheaper vegetative tissue.

Water Stress Scatters Nitrogen Dilution Curves in Wheat

Nitrogen dilution curves relate a crop's critical nitrogen concentration (%N_c) to biomass (W) according to the allometric model %N_c = a W ^-b . This model has a strong theoretical foundation, and parameters a and b show little variation for well-watered crops. Here we explore the robustness of this model for water stressed crops. We established experiments to examine the combined effects of water stress, phenology, partitioning of biomass, and water-soluble carbohydrates (WSC), as driven by environment and variety, on the %N_c of wheat crops. We compared models where %N_c was plotted against biomass, growth stage and thermal time. The models were similarly scattered. Residuals of the %N_c - biomass model at anthesis were positively related to biomass, stem:biomass ratio, Δ¹³C and water supply, and negatively related to ear:biomass ratio and concentration of WSC. These are physiologically meaningful associations explaining the scatter of biomass-based dilution curves. Residuals of the thermal time model showed less consistent associations with these variables. The biomass dilution model developed for well-watered crops overestimates nitrogen deficiency of water-stressed crops, and a biomass-based model is conceptually more justified than developmental models. This has implications for diagnostic and modeling. As theory is lagging, a greater degree of empiricism might be useful to capture environmental, chiefly water, and genotype-dependent traits in the determination of critical nitrogen for diagnostic purposes. Sensitivity analysis would help to decide if scaling nitrogen dilution curves for crop water status, and genotype-dependent parameters are needed.

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

Profligate and conservative: water use strategies in grain legumes

Yields of grain legumes are constrained by available water. Thus, it is crucial to understand traits influencing water uptake and the efficiency of using water to produce biomass. Global comparisons and comparisons at specific locations reveal that water use of different grain legumes is very similar, which indicates that water use efficiency varies over a wide range due to differences in biomass and yield. Moreover, yield increases more per millimetre of water used in cool season grain legumes than warm season species. Although greater contrasts have been observed across species and genotypes at the pot and lysimeter level, agronomic factors need to be taken into account when scaling those studies to field-level responses. Conservative water use strategies in grain legumes such as low stomatal conductance as approximated by low photosynthetic carbon isotope discrimination reduces yield potential, whereas temporal adjustments of stomatal conductance within the growing season and in response to environmental factors (such as vapour pressure deficit) helps to optimize the trade-off between carbon gain and water loss. Furthermore, improved photosynthetic capacity, reduced mesophyll conductance, reduced boundary layer, and re-fixation of respired CO2 were identified as traits that are beneficial without water deficit, but also under terminal and transient drought. Genotypic variability in some grain legume species has been observed for several traits that influence water use, water use efficiency, and yield, including root length and the temporal pattern of water use, but even more variation is expected from wild relatives. Albeit that N2 fixation decreases under drought, its impact on water use is still largely unknown, but the nitrogen source influences gas exchange and, thus, transpiration efficiency. This review concludes that conservative traits are needed under conditions of terminal drought to help maintain soil moisture until the pod-filling period, but profligate traits, if tightly regulated, are important under conditions of transient drought in order to profit from short intermittent periods of available soil moisture.

Structural modelling and molecular dynamics of a multi-stress responsive WRKY TF-DNA complex towards elucidating its role in stress signalling mechanisms in chickpea

Chickpea is a premier food legume crop with high nutritional quality and attains prime importance in the current era of 795 million people being undernourished worldwide. Chickpea production encounters setbacks due to various stresses and understanding the role of key transcription factors (TFs) involved in multiple stresses becomes inevitable. We have recently identified a multi-stress responsive WRKY TF in chickpea. The present study was conducted to predict the structure of WRKY TF to identify the DNA-interacting residues and decipher DNA-protein interactions. Comparative modelling approach produced 3D model of the WRKY TF with good stereochemistry, local/global quality and further revealed W19, R20, K21, and Y22 motifs within a vicinity of 5 Å to the DNA amongst R18, G23, Q24, K25, Y36, Y37, R38 and K47 and these positions were equivalent to the 2LEX WRKY domain of Arabidopsis. Molecular simulations analysis of reference protein -PDB ID 2LEX, along with Car-WRKY TF modelled structure with the DNA coordinates derived from PDB ID 2LEX and docked using HADDOCK were executed. Root Mean Square (RMS) Deviation and RMS Fluctuation values yielded consistently stable trajectories over 50 ns simulation. Strengthening the obtained results, neither radius of gyration, distance and total energy showed any signs of DNA-WRKY complex falling apart nor any significant dissociation event over 50 ns run. Therefore, the study provides first insights into the structural properties of multi-stress responsive WRKY TF-DNA complex in chickpea, enabling genome wide identification of TF binding sites and thereby deciphers their gene regulatory networks.

Genetic diversity and genomic strategies for improving drought and waterlogging tolerance in soybeans

Drought and its interaction with high temperature are the major abiotic stress factors affecting soybean yield and production stability. Ongoing climate changes are anticipated to intensify drought events, which will further impact crop production and food security. However, excessive water also limits soybean production. The success of soybean breeding programmes for crop improvement is dependent on the extent of genetic variation present in the germplasm base. Screening for natural genetic variation in drought- and flooding tolerance-related traits, including root system architecture, water and nitrogen-fixation efficiency, and yield performance indices, has helped to identify the best resources for genetic studies in soybean. Genomic resources, including whole-genome sequences of diverse germplasms, millions of single-nucleotide polymorphisms, and high-throughput marker genotyping platforms, have expedited gene and marker discovery for translational genomics in soybean. This review highlights the current knowledge of the genetic diversity and quantitative trait loci associated with root system architecture, canopy wilting, nitrogen-fixation ability, and flooding tolerance that contributes to the understanding of drought- and flooding-tolerance mechanisms in soybean. Next-generation mapping approaches and high-throughput phenotyping will facilitate a better understanding of phenotype-genotype associations and help to formulate genomic-assisted breeding strategies, including genomic selection, in soybean for tolerance to drought and flooding stress.

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.