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Chickpea productivity remains low due to limited genetic variability and susceptibility to biotic and abiotic stresses. To address these challenges, the introgression of novel genes from wild relatives and multi-environment evaluations are essential for identifying high-yielding, stable interspecific derivatives (ISDs). Despite the availability of several statistical tools, few chickpea studies have used a comprehensive multi-model approach for stability analysis. This study fills the void by applying four models- AMMI, GGE, WAASB, and MTSI for the first time in chickpea to evaluate multi-trait stability across diverse environments. 19 ISDs developed from four interspecific crosses (BGD 72 × ILWC 229, PBG 5 × ILWC 229, BGD 72 × ILWC 246, and PBG 5 × ILWC 246), along with two checks (PBG 7 and PBG 8), were evaluated across six environments. Trials were conducted over three consecutive rabi seasons (2020–2023) at Ludhiana (ENV1–ENV3), followed by multi-location testing during rabi 2023–24 at Ludhiana (ENV4), Karnal (ENV5), and Kanpur (ENV6). Key yield traits, including number of pods per plant (NPP), 100-seed weight (HSW), and seed yield per plot (SYPP), were analyzed using all four models. Significant effects of genotype, environment, and genotype × environment interactions (GEIs) were detected through pooled ANOVA, and positive correlations were observed among all key traits. Genotypes GL21-1 (G1) and GL21-54 (G8) were superior performers with high trait values and stable performance across all environments, with yield variability up to 20% under stress-prone conditions. Among the models, GGE and WAASB were found effective for individual traits, while MTSI was superior for multi-trait selection. These promising ISDs can be released as high-yielding varieties or used as donor parents in climate-resilient chickpea breeding programs, addressing the rising global demand for chickpea production.

Unravelling the genetic architecture underlying yield components and agronomic traits is important for enhancing crop productivity. Here, a recombinant inbred line (RIL) population, developed from ICC 4958 and DCP 92–3 cross, was used for constructing linkage map and QTL mapping analysis. The RIL population was genotyped using a high-throughput Axiom ® CicerSNP array, which enabled the development of a high-density genetic map consisting of 3,818 SNP markers and spanning a distance of 1064.14 cM. Analysis of phenotyping data for yield, yield components and agronomic traits measured across three years together with genetic mapping data led to the identification of 10 major-effect QTLs and six minor-effect QTLs explaining up to 59.70% phenotypic variance. The major-effect QTLs identified for 100-seed weight, and plant height possessed key genes, such as C3HC4 RING finger protein, pentatricopeptide repeat (PPR) protein, sugar transporter, leucine zipper protein and NADH dehydrogenase, amongst others. The gene ontology studies highlighted the role of these genes in regulating seed weight and plant height in crop plants. The identified genomic regions for yield, yield components, and agronomic traits, and the closely linked markers will help advance genetics research and breeding programs in chickpea.

Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.

Mung bean [ Vigna radiata (L.) Wilczek] is an important short-duration grain legume widely known for its nutritional, soil ameliorative, and cropping system intensification properties. This study aims at evaluating genetic diversity among mung bean genotypes and detecting genomic regions associated with various yield attributing traits and yellow mosaic disease (YMD) resistance by association mapping. A panel of 80 cultivars and advanced breeding lines was evaluated for 10 yield-related and YMD resistance traits during kharif (monsoon) and summer seasons of 2018–2019 and 2019–2020. A total of 164 genome-wide simple sequence repeat (SSR) markers were initially screened, out of which 89 were found polymorphic which generated 317 polymorphic alleles with an average of 3.56 alleles per SSR locus. The number of alleles at each locus varied from 2 to 7. The population genetic structure analysis grouped different genotypes in three major clusters and three genetically distinct subpopulations (SPs) (i.e., SP-1, SP-2, and SP-3) with one admixture subpopulation (SP-4). Both cluster and population genetic structure analysis categorized the advanced mung bean genotypes in a single group/SP and the released varieties in other groups/SPs, suggesting that the studied genotypes may have common ancestral history at some level. The population genetic structure was also in agreement with the genetic diversity analysis. The estimate of the average degree of linkage disequilibrium (LD) present at the genome level in 80 mung bean genotypes unveiled significant LD blocks. Over the four seasons, 10 marker-trait associations were observed significant for YMD and four seed yield (SY)-related traits viz ., days to flowering, days to maturity, plant height, and number of pods per plant using the mixed linear model (MLM) method. These associations may be useful for marker-assisted mung bean yield improvement programs and YMD resistance.

Background Heat stress is one of the major abiotic threats to rice production, next to drought and salinity stress. Incidence of heat stress at reproductive phase of the crop results in abnormal pollination leading to floret sterility, low seed set and poor grain quality. Identification of QTLs and causal genes for heat stress tolerance at flowering will facilitate breeding for improved heat tolerance in rice. In the present study, we used 272 F 8 recombinant inbred lines derived from a cross between Nagina22, a well-known heat tolerant Aus cultivar and IR64, a heat sensitive popular Indica rice variety to map the QTLs for heat tolerance. Results To enable precise phenotyping for heat stress tolerance, we used a controlled phenotyping facility available at ICAR-Indian Institute of Wheat and Barley Research, Karnal, India. Based on ‘days to 50% flowering’ data of the RILs, we followed staggered sowing to synchronize flowering to impose heat stress at uniform stage. Using the Illumina infinium 5K SNP array for genotyping the parents and the RILs, and stress susceptibility and stress tolerance indices (SSI and STI) of percent spikelet sterility and yield per plant (g), we identified five QTLs on chromosomes 3, 5, 9 and 12. The identified QTLs explained phenotypic variation in the range of 6.27 to 21. 29%. Of these five QTLs, two high effect QTLs, one novel ( qSTIPSS9 .1) and one known ( qSTIY5.1/qSSIY5 .2), were mapped in less than 400 Kbp genomic regions, comprising of 65 and 54 genes, respectively. Conclusions The present study identified two major QTLs for heat tolerance in rice in narrow physical intervals, which can be employed for crop improvement by marker assisted selection (MAS) after development of suitable scorable markers for breeding of high yielding heat tolerant rice varieties. This is the first report of a major QTL for heat tolerance on chromosome 9 of rice. Further, a known QTL for heat tolerance on chromosome 5 was narrowed down from 23 Mb to 331 Kbp in this study.

In the current global warming scenario, it is imperative to develop crops with improved heat tolerance or acclimation, for which knowledge of major heat stress-tolerant genes or genomic regions is a prerequisite. Though several quantitative trait loci (QTLs) for heat tolerance have been mapped in rice, candidate genes from these QTLs have not been reported yet. The meta-analysis of microarray datasets for heat stress in rice can give us a better genomic resource for the dissection of QTLs and the identification of major candidate genes for heat stress tolerance. In the present study, a database, RiceMetaSys-H, comprising 4227 heat stress-responsive genes (HRGs), was created using seven publicly available microarray datasets. This included in-house-generated microarray datasets of Nagina 22 (N22) and IR64 subjected to 8 days of heat stress. The database has provisions for searching the HRGs through genotypes, growth stages, tissues, and physical intervals in the genome, as well as Locus IDs, which provide complete information on the HRGs with their annotations and fold changes, along with the experimental material used for the analysis. The up-regulation of genes involved in hormone biosynthesis and signalling, sugar metabolism, carbon fixation, and the ROS pathway were found to be the key mechanisms of enhanced heat tolerance. Integrating variant and expression analysis, the database was used for the dissection of the major effect of QTLs on chromosomes 4, 5, and 9 from the IR64/N22 mapping population. Out of the 18, 54, and 62 genes in these three QTLs, 5, 15, and 12 genes harboured non-synonymous substitutions. Fifty-seven interacting genes of the selected QTLs were identified by a network analysis of the HRGs in the QTL regions. Variant analysis revealed that the proportion of unique amino acid substitutions (between N22/IR64) in the QTL-specific genes was much higher than the common substitutions, i.e., 2.58:0.88 (2.93-fold), compared to the network genes at a 0.88:0.67 (1.313-fold) ratio. An expression analysis of these 89 genes showed 43 DEGs between IR64/N22. By integrating the expression profiles, allelic variations, and the database, four robust candidates (LOC_Os05g43870, LOC_Os09g27830, LOC_Os09g27650, andLOC_Os09g28000) for enhanced heat stress tolerance were identified. The database thus developed in rice can be used in breeding to combat high-temperature stress.

Background The alphabaculoviruses are lethal pathogens of lepidopteran caterpillars including a polyphagous and globally recognized pest, Helicoverpa armigera (Hubner) infesting economically important agriculture crops worldwide. The biological and molecular characterizations of indigenous nucleopolyhedrovirus of the genus Alphabaculovirus isolated from H. armigera in chickpea fields are described. Results The virulence of virus isolate was tested in 3rd instar H. armigera larvae, and LC 50 (median lethal concentration) was estimated to be 2.69 × 10 4 OBs ml −1 . The ST 50 (median survival time) was 4 days post-inoculation, when the 3rd instar H. armigera larvae were inoculated by OB (occlusion body) concentration equivalent to LC 90 . An average incubation period of the virus isolate in 3rd instar ranged between 4 and 6 days post-inoculation. The OBs of a virus isolate appeared irregular in shape and variable in size with diameter ranging from 0.57 to 1.46 μm on the longest edge and average of 1.071 ± 0.068 μm (mean ± SE). On the basis of phylogenetic analysis of polh , pif-1 , and lef-8 genes, the isolate was found to be a member of the genus Alphabaculovirus. The isolate showed a genetic affinity with species of group II Alphabaculoviruses and appeared to be a group II NPV. Conclusions On the basis of molecular phylogeny and associated host insect, this indigenous isolate was designated as HearNPV-IIPR05 isolate, which could be a potential candidate for the biological control of H. armigera infesting legumes and other commercial crops.

Chickpea ( L.) contributes 75% of total pulse production. Being cheaper than animal protein, makes it important in dietary requirement of developing countries. Weed not only competes with chickpea resulting into drastic yield reduction but also creates problem of harboring fungi, bacterial diseases and insect pests. Chemical approach having new herbicide discovery has constraint of limited lead molecule options, statutory regulations and environmental clearance. Through genetic approach, transgenic herbicide tolerant crop has given successful result but led to serious concern over ecological safety thus non-transgenic approach like marker assisted selection is desirable. Since large variability in tolerance limit of herbicide already exists in chickpea varieties, thus the genes offering herbicide tolerance can be introgressed in variety improvement programme. Transcriptome studies can discover such associated key genes with herbicide tolerance in chickpea. This is first transcriptomic studies of chickpea or even any legume crop using two herbicide susceptible and tolerant genotypes exposed to imidazoline (Imazethapyr). Approximately 90 million paired-end reads generated from four samples were processed and assembled into 30,803 contigs using reference based assembly. We report 6,310 differentially expressed genes (DEGs), of which 3,037 were regulated by 980 miRNAs, 1,528 transcription factors associated with 897 DEGs, 47 Hub proteins, 3,540 putative Simple Sequence Repeat-Functional Domain Marker (SSR-FDM), 13,778 genic Single Nucleotide Polymorphism (SNP) putative markers and 1,174 Indels. Randomly selected 20 DEGs were validated using qPCR. Pathway analysis suggested that xenobiotic degradation related gene, glutathione S-transferase (GST) were only up-regulated in presence of herbicide. Down-regulation of DNA replication genes and up-regulation of abscisic acid pathway genes were observed. Study further reveals the role of cytochrome P450, xyloglucan endotransglucosylase/hydrolase, glutamate dehydrogenase, methyl crotonoyl carboxylase and of thaumatin-like genes in herbicide resistance. Reported DEGs can be used as genomic resource for future discovery of candidate genes associated with herbicide tolerance. Reported markers can be used for future association studies in order to develop marker assisted selection (MAS) for refinement. In endeavor of chickpea variety development programme, these findings can be of immense use in improving productivity of chickpea germplasm.

Grain size is one of the three productivity related traits in rice and hence a major target for genetic improvement. Since understanding genetic variation in grain size between Basmati and indica genotypes is important for rice improvement, a recombinant inbred population was developed from a traditional aromatic cultivar ‘Basmati 370’ and a non-aromatic indica genotype ‘IRBB60’. This population was phenotyped in two locations for grain length (GL), grain breadth (GB), GL/GB ratio (LBR) and grain weight (GW). Though the RIL population reported in the current study exhibited segregation distortion (SD) for 54 % of the markers, they were utilized in analysis using an appropriate statistical package, PROC QTL in the SAS environment. Interval mapping revealed a total of 15 QTLs for GL, seven for GB, 15 for LBR and two for GW. Among them 13 were not reported earlier and thus novel. For a known major QTL identified in the study, GW8 for GB, a PCR based functional marker was designed and validated. This is the first report wherein a very high proportion of markers (>50 %) exhibiting SD have been successfully used for QTL mapping.

Vigna is a large, pan-tropic and highly variable group of the legumes family which is known for its > 10 cultivated species having significant commercial value for their nutritious grains and multifarious uses. The wild vignas are considered a reservoir of numerous useful traits which can be deployed for introgression of resistance to biotic and abiotic stresses, seed quality and enhanced survival capability in extreme environments. Nonetheless, for their effective utilization through introgression breeding information on their genetic diversity, population structure and crossability is imperative. Keeping this in view, the present experiment was undertaken with 119 accessions including 99 wild Vigna accessions belonging to 19 species and 18 cultivated genotypes of Vigna and 2 of Phaseolus. Total 102 polymorphic SSRs were deployed to characterize the material at molecular level which produced 1758 alleles. The genotypes were grouped into four major clusters which were further sub-divided in nine sub-clusters. Interestingly, all cultivated species shared a single cluster while no such similarities were observed for the wild accessions as these were distributed in different groups of sub-clusters. The co-dominant allelic data of 114 accessions were then utilized for obtaining status of the accessions and their hybrid forms. The model-based population structure analysis categorized 114 accessions of Vigna into 6 genetically distinct sub-populations (K = 6) following admixture-model based simulation with varying levels of admixture. 91 (79.82%) accessions resembled their hierarchy and 23 (20.18%) accessions were observed as the admixture forms. Maximum number of accessions (25) were grouped in sub-population (SP) 6 and the least accessions were grouped in SP3 and SP5 (11 each). The population genetic structure, therefore, supported genetic diversity analysis and provided an insight into the genetic lineage of these species which will help in effective use of germplasm for development of cultivars following selective prebreeding activities.