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Inter-specific hybridization is a key strategy in modern crop improvement, aiming to integrate desirable traits from wild species into cultivated backgrounds. This study delves into the evaluation and identification of advanced inter-specific derivatives (IDs) derived from crosses of cultivated chickpea with Cicer reticulatum and C. echinospermum. The primary aim was to incorporate desirable yield enhancement traits, disease resistance, and nutritional quality traits into cultivated chickpea. The IDs were assessed during rabi 2021-22 and 2022-23 in the northern plains zone of India. Significant amount of genetic variability was observed for key agro-morphological traits having high heritability and genetic advance. Superior derivatives were identified for early flowering, high seed yield, and resistance to Ascochyta blight, Botrytis grey mould, and Fusarium wilt. Significant variability for crude protein and total soluble sugar content was also observed among the derivatives. The findings highlight the potential of utilizing wild Cicer species to broaden the genetic base of cultivated chickpea for the development of robust, high-yielding, disease-resistant varieties with improved nutritional traits suitable for diverse environmental conditions. The superior derivatives identified in this study hold promise for future breeding programmes for improving productivity, disease resistance and nutritional quality. [ABSTRACT FROM AUTHOR]

Micronutrient malnutrition is a serious concern in many parts of the world; therefore, enhancing crop nutrient content is an important challenge. Chickpea (Cicer arietinum L.), a major food legume crop worldwide, is a vital source of protein and minerals in the vegetarian diet. This study evaluated a diverse set of 258 chickpea germplasm accessions for 12 key nutritional traits. A significant variation was observed for several nutritional traits, including crude protein (16.56–24.64/100 g), β-Carotene (0.003–0.104 mg/100 g), calcium (60.69–176.55 mg/100 g), and folate (0.413–6.537 mg/kg). These data, combined with the available whole-genome sequencing data for 318,644 SNPs, were used in genome-wide association studies comprising single-locus and multi-locus models. We also explored the effect of varying the minor allele frequency (MAF) levels and heterozygosity. We identified 62 significant marker-trait associations (MTAs) explaining up to 28.63% of the phenotypic variance (PV), of which nine were localized within genes regulating G protein-coupled receptor signaling pathway, proteasome assembly, intracellular signal transduction, and oxidation–reduction process, among others. The significant effect MTAs were located primarily on Ca1, Ca3, Ca4, and Ca6. Importantly, varying the level of heterozygosity was found to significantly affect the detection of associations contributing to traits of interest. We further identified seven promising accessions (ICC10399, ICC1392, ICC1710, ICC2263, ICC1431, ICC4182, and ICC16915) with superior agronomic performance and high nutritional content as potential donors for developing nutrient-rich, high-yielding chickpea varieties. Validation of the significant MTAs with higher PV could identify factors controlling the nutrient acquisition and facilitate the design of biofortified chickpeas for the future.

Chickpea yield is severely affected by drought stress, which is a complex quantitative trait regulated by multiple small-effect genes. Identifying genomic regions associated with drought tolerance component traits may increase our understanding of drought tolerance mechanisms and assist in the development of drought-tolerant varieties. Here, a total of 187 F8 recombinant inbred lines (RILs) developed from an interspecific cross between drought-tolerant genotype GPF 2 (Cicer arietinum) and drought-sensitive accession ILWC 292 (C. reticulatum) were evaluated to identify quantitative trait loci (QTLs) associated with drought tolerance component traits. A total of 21 traits, including 12 morpho-physiological traits and nine root-related traits, were studied under rainfed and irrigated conditions. Composite interval mapping identified 31 QTLs at Ludhiana and 23 QTLs at Faridkot locations for morphological and physiological traits, and seven QTLs were identified for root-related traits. QTL analysis identified eight consensus QTLs for six traits and five QTL clusters containing QTLs for multiple traits on linkage groups CaLG04 and CaLG06. The identified major QTLs and genomic regions associated with drought tolerance component traits can be introgressed into elite cultivars using genomics-assisted breeding to enhance drought tolerance in chickpea.

In chickpea breeding, drought is a major concern and a complex trait controlled by several genes. To develop drought-tolerant varieties, it is essential to use the available germplasm and genomic resources. Over the years, the landraces have proven to be a good source for the dissection of genes for different yield and yield-related traits. The present investigation for marker-trait associations (MTAs) and candidate gene identification was conducted by studying 125 chickpea landraces collected from the West Asia and North Africa (WANA) region, along with 4 varieties suitable for irrigated and rainfed environments. This study analyzed 13 physio-morphological traits in 2 consecutive years at two isolated locations (IARI, New Delhi, and Dharwad). A strong correlation coefficient was observed between the trait seed yield (SY) and biological yield (BY) under both conditions. The Drought Susceptibility Index (DSI) ranged from 0.02 to 1.84 and 0.10 to 2.04 at the IARI, New Delhi and Dharwad locations, respectively. The genotypic data of 6,367 single nucleotide polymorphisms (SNPs) distributed across the genome were used for genetic diversity study, population structure, and genome-wide association study (GWAS). The average polymorphic information content (PIC) value observed was 0.25, and the average linkage disequilibrium (LD) decay distance was 152,269 bp across the genome. A total of four subgroups were observed within the population for genotypic data. Fixed and random model Circulating Probability Unification (FarmCPU) was used for the GWAS analysis, which considered both fixed- and random-effect models. A total of 52 significant SNPs were reported in both irrigated and rainfed conditions at low locations; 7 SNPs were associated with more than one trait, which may have pleiotropic effects. Significant SNPs were annotated in the pulse database. The identified genomic region found in or near MTA under rainfed conditions encodes for guard cell hydrogen peroxideresistant1 (GHR1), late embryogenesis-abundant, E3 ubiquitin-protein ligase, walls are thin1 (WAT1), and beta-galactosidase that are known to be associated with drought tolerance. [ABSTRACT FROM AUTHOR]

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out singlenucleotide polymorphism (SNP) genotyping using the genotyping-bysequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker--trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of <0.05 [-log10(p) > 4.95] using the BLINK (Bayesian-information and linkagedisequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to genecoding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid--amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru, India) during the crop seasons 2011-12 and 2012-13 under rainfed and irrigated conditions. In parallel, these lines were also genotyped using DArTseq platform to generate data on 3,000 polymorphic markers. Phenotypic and genotypic data were used with six statistical GS models to estimate the prediction accuracies. GS models were tested for four yield related traits viz. seed yield, 100 seed weight, days to 50% flowering and days to maturity. Prediction accuracy for the models tested varied from 0.138 (seed yield) to 0.912 (100 seed weight), whereas performance of models did not show any significant difference for estimating prediction accuracy within traits. Kinship matrix calculated using genotyping data reaffirmed existence of two different groups within selected lines. There was not much effect of population structure on prediction accuracy. In brief, present study establishes the necessary resources for deployment of GS in chickpea breeding.

The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology have yielded high-dimensional genomic marker data which can be difficult to incorporate into statistical models. In this paper, we investigated the utility of applying dimensionality reduction (DR) methods as a pre-processing step for GS methods. We compared five DR methods and studied the trend in the prediction accuracies of each method as a function of the number of features retained. The effect of DR methods was studied using three models that involved the main effects of line, environment, marker, and the genotype by environment interactions. The methods were applied on a real data set containing 315 lines phenotyped in nine environments with 26,817 markers each. Regardless of the DR method and prediction model used, only a fraction of features was sufficient to achieve maximum correlation. Our results underline the usefulness of DR methods as a key pre-processing step in GS models to improve computational efficiency in the face of ever-increasing size of genomic data. [ABSTRACT FROM AUTHOR]

In developing a Trichoderma viride-based biocontrol program for Fusarium wilt disease in chickpea, the choice of the quality formulation is imperative. In the present study, two types of formulations i.e. powder for seed treatment (TvP) and tablet for direct application (TvT), employing T. viride as the biocontrol agent, were evaluated for their ability to control chickpea wilt under field conditions at three dosages i.e. recommended (RD), double of recommended (DD) and half of recommended (1/2 RD). A screening study for the antagonistic fungi strains based on volatile and non-volatile bioassays revealed that T. viride ITCC 7764 has the most potential among the five strains tested (ITCC 6889, ITCC 7204, ITCC 7764, ITCC 7847, ITCC 8276), which was then used to develop the TvP and TvT formulations. Gas Chromatography-Mass Spectrometry (GC-MS) analysis of volatile organic compounds (VOCs) of T. viride strain confirmed the highest abundance of compositions comprising octan-3-one (13.92%), 3-octanol (10.57%), and 1-octen-3-ol (9.40%) in the most potential T. viride 7764. Further Physico-chemical characterization by standard Collaborative International Pesticides Analytical Council (CIPAC) methods revealed the optimized TvP formulation to be free flowing at pH 6.50, with a density of 0.732 g cm-3. The TvT formulation showed a pH value of 7.16 and density of 0.0017 g cm-3 for a complete disintegration time of 22.5 min. The biocontrol potential of TvP formulation was found to be superior to that of TvT formulation in terms of both seed germination and wilt incidence in chickpea under field conditions. However, both the developed formulations (TvP and TvT) expressed greater bioefficacy compared to the synthetic fungicide (Carbendazim 50% WP) and the conventional talc-based formulation. Further research should be carried out on the compatibility of the developed products with other agrochemicals of synthetic or natural origin to develop an integrated disease management (IDM) schedule in chickpea. [ABSTRACT FROM AUTHOR]

Multidrug and toxic compound extrusion (MATE) transporters comprise a multigene family that mediates multiple functions in plants through the efflux of diverse substrates including organic molecules, specialized metabolites, hormones, and xenobiotics. MATE classification based on genome-wide studies remains ambiguous, likely due to a lack of large-scale phylogenomic studies and/or reference sequence datasets. To resolve this, we established a phylogeny of the plant MATE gene family using a comprehensive kingdom-wide phylogenomic analysis of 74 diverse plant species. We identified more than 4,000 MATEs, which were classified into 14 subgroups based on a systematic bioinformatics pipeline using USEARCH, blast+ and synteny network tools. Our classification was performed using a four-step process, whereby MATEs sharing ≥ 60% protein sequence identity with a ≤ 1E-05 threshold at different sequence lengths (either full-length, ≥ 60% length, or ≥ 150 amino acids) or retaining in the similar synteny blocks were assigned to the same subgroup. In this way, we assigned subgroups to 95.8% of the identified MATEs, which we substantiated using synteny network clustering analysis. The subgroups were clustered under four major phylogenetic groups and named according to their clockwise appearance within each group. We then generated a reference sequence dataset, the usefulness of which was demonstrated in the classification of MATEs in additional species not included in the original analysis. Approximately 74% of the plant MATEs exhibited synteny relationships with angiosperm-wide or lineage-, order/family-, and species-specific conservation. Most subgroups evolved independently, and their distinct evolutionary trends were likely associated with the development of functional novelties or the maintenance of conserved functions. Together with the systematic classification and synteny network profiling analyses, we identified all the major evolutionary events experienced by the MATE gene family in plants. We believe that our findings and the reference dataset provide a valuable resource to guide future functional studies aiming to explore the key roles of MATEs in different aspects of plant physiology. Our classification framework can also be readily extendable to other (super) families. [ABSTRACT FROM AUTHOR]

Chickpea (Cicer arietinum L.) is an economically important food legume grown in arid and semi-arid regions of the world. Chickpea is cultivated mainly in the rainfed, residual moisture, and restricted irrigation condition. The crop is always prone to drought stress which is resulting in flower drop, unfilled pods, and is a major yield reducer in many parts of the world. The present study elucidates the association between candidate gene and morpho-physiological traits for the screening of drought tolerance in chickpea. Abiotic stress-responsive gene Dehydrin (DHN) was identified in some of the chickpea genotypes based on the sequence similarity approach to play a major role in drought tolerance. Analysis of variance revealed a significant effect of drought on relative water content, membrane stability index, plant height, and yield traits. The genotypes Pusa1103, Pusa362, and ICC4958 were found most promising genotypes for drought tolerance as they maintained the higher value of osmotic regulations and yield characters. The results were further supported by a sequence similarity approach for the dehydrin gene when analyzed for the presence of single nucleotide polymorphisms (SNPs) and indels. Homozygous indels and single nucleotide polymorphisms were found after the sequencing in some of the selected genotypes. [ABSTRACT FROM AUTHOR]

Much of the world's population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia. [ABSTRACT FROM AUTHOR]

International Crops Research Institute for the Semi-Arid Tropics, Patancheru, India The large-scale mining and high-throughput genotyping of novel gene-based allelic variants in natural mapping population are essential for association mapping to identify functionally relevant molecular tags governing useful agronomic traits in chickpea. The present study employs an alternative time-saving, non-laborious and economical pool-based EcoTILLING approach coupled with agarose gel detection assay to discover 1133 novel SNP allelic variants from diverse coding and regulatory sequence components of 1133 transcription factor (TF) genes by genotyping in 192 diverse desi and kabuli chickpea accessions constituting a seed weight association panel. Integrating these SNP genotyping data with seed weight field phenotypic information of 192 structured association panel identified eight SNP alleles in the eight TF genes regulating seed weight of chickpea. The associated individual and combination of all SNPs explained 10-15 and 31% phenotypic variation for seed weight, respectively. The EcoTILLING-based large-scale allele mining and genotyping strategy implemented for association mapping is found much effective for a diploid genome crop species like chickpea with narrow genetic base and low genetic polymorphism. This optimized approach thus can be deployed for various genomics-assisted breeding applications with optimal expense of resources in domesticated chickpea. The seed weight-associated natural allelic variants and candidate TF genes delineated have potential to accelerate marker-assisted genetic improvement of chickpea. [ABSTRACT FROM AUTHOR]