Flavonols are an important class of flavonoids that play a role in plant growth, development, and environmental stress mitigation and have well-documented health-promoting activities. Targeted manipulation of flavonoid biosynthesis has emerged as a promising approach for improving crop nutritional quality through precision genome editing. Anthocyanidin synthase (ANS) catalyses the final step in anthocyanin biosynthesis and represents an important point for redirecting metabolic flux within the flavonoid biosynthetic pathway. In this study, an in silico approach was used to identify and assess high-confidence CRISPR/Cas9 guide RNAs (gRNAs) targeting the ANS in selected cereal crops (Oryza sativa and Zea mays). The ANS sequences of Oryza sativa and Zea mays were retrieved from the NCBI GenBank database and subjected to guide RNA prediction using the CHOPCHOP platform. Candidate gRNAs were subsequently evaluated using CRISPOR based on their Massachusetts Institute of Technology (MIT) specificity score, Cutting Frequency Determination (CFD) score, and predicted off-target profiles. Twelve candidate gRNAs were identified for each of rice and maize. Based on the CRISPOR-based specificity assessment, OsANS-5 and OsANS-8 were identified as the most suitable guide RNAs for O. sativa, each with MIT specificity and CFD scores of 100 and three predicted off-target sites. In Z. mays, ZmANS-9 was identified as the most suitable candidate, with an MIT specificity score of 99, a CFD score of 100, and six predicted off-target sites. Comparative analysis indicated that combining CHOPCHOP for guide RNA design with CRISPOR for specificity assessment helped distinguish guide RNAs with high predicted specificity from candidates with greater predicted off-target potential. These results underscore the value of comprehensive computational screening before experimental genome editing in crops. The guide RNAs identified in this study provide candidates for future CRISPR/Cas9-mediated disruption of the ANS to explore its role in the flavonoid biosynthesis pathway. This workflow also provides a computational framework for functional genomics and future metabolic engineering studies focused on understanding flavonoid pathway regulation and evaluating the potential effects of ANS knockout on flavonol accumulation in crop plants.
Groundnut (Arachis hypogaea L.) is an important oilseed and legume crop for global food security, yet its genetic advancement remains constrained by a narrow genetic base. Improving pod yield and kernel quality by systematically exploiting available genetic variability is a primary objective in groundnut breeding. In this study, we evaluated 35 groundnut accessions, comprising 30 advanced breeding lines (ICGV series) and five commercial checks during the rainy season of 2024 using an Augmented Randomised Block Design (Augmented RBD) at the Seed Research and Technology Centre (SRTC), PJTAU. A total of 11 quantitative morphological and agronomic traits were recorded and subjected to multivariate analysis. Hierarchical cluster analysis using Euclidean distance and Ward’s minimum variance method (Ward.D2) partitioned the genotypes into four distinct clusters. Cluster II was the largest (n = 22), comprised lines with a low average yield (2,589.30 kg ha-1) and seed weight, whereas Cluster III (n = 2) exhibited the maximum plant height (56.29 cm) and 100-seed weight (58.80 g), but fewer pods per plant (8.60), suggesting a trade-off between seed size and pod proliferation. Cluster IV (n = 3, including K6, JCG 2141, and G5) demonstrated superior agronomic performance, combining early maturity (110 days) with the highest pod yield (5,215.28 kg ha-1). The maximum inter-cluster distance occurred between Clusters II and III (6.32), followed by Clusters III and IV (6.10), highlighting substantial genetic divergence. Principal component analysis (PCA) identified four principal components (λ > 1.0) accounting for 76.81% of the total phenotypic variation, with PC1 (33.74%) dominated by 100-seed weight, pod wall thickness, kernel diameter, and pod yield. Crossing genotypes from Cluster IV with those from Cluster III offers the potential to combine large kernel traits with early maturity and high pod yield, facilitating transgressive segregation in future groundnut improvement programmes. Furthermore, targeted hybridisation between the high-yielding, early-maturing lines of Cluster IV and the bold-seeded lines of Cluster III may help to overcome the physiological trade-off between kernel mass and pod density, establishing a strategic foundation for future high-yielding groundnut cultivars.
RNA interference (RNAi) is a highly sequence-specific regulatory process that suppresses gene expression at the post-transcriptional level. It serves essential biological functions in eukaryotes, including antiviral defence, control of transposable elements, and regulation of endogenous gene activity. Owing to its high specificity and targeted mode of action, RNAi has gained recognition as a precise and environmentally sustainable tool for next-generation pest management strategies. By targeting essential genes involved in development, metabolism, reproduction, and cellular homeostasis, double-stranded RNA (dsRNA)-mediated silencing induces high mortality, growth inhibition, and reduced fecundity across diverse insect orders. Functional genomic studies have identified numerous high-efficacy targets across insect orders, particularly genes involved in proteasomal degradation, transcriptional regulation, chitin biosynthesis, hormonal signalling (ecdysone pathway), vacuolar ATPase activity, and apoptosis. Host-Induced Gene Silencing (HIGS), Spray-Induced Gene Silencing (SIGS) and plastid-mediated RNAi (PM-RNAi) are among the delivery mechanisms for dsRNA. While HIGS and PM-RNAi provide sustained in planta dsRNA expression, SIGS offers a flexible, non-transgenic alternative for rapid field application. Advances in genome-wide target identification, optimised delivery systems, and nanocarrier-mediated stabilisation have significantly improved dsRNA stability against UV exposure and nuclease degradation, as well as RNAi efficacy through transcuticular and gut epithelial uptake. These developments position RNAi as a highly specific, environmentally benign, and scalable biopesticide strategy with strong potential to complement or replace conventional chemical insecticides in integrated pest management programmes.
Plants resist insect herbivores through interconnected structural, chemical and inducible defence mechanisms that influence insect behaviour, development and survival. This review examines the contributions of plant specialised metabolites, particularly terpenoids and tannins, and epicuticular lipids to host-plant resistance and plant–insect interactions. Terpenoids can function as feeding deterrents, toxic compounds and volatile signals that influence herbivore behaviour and the recruitment of predators and parasitoids. Tannins may reduce food palatability, interfere with digestion and affect nutrient utilisation, although their effectiveness varies with chemical structure, concentration and insect physiology. Epicuticular lipids influence insect landing, attachment, locomotion, feeding and oviposition through their chemical composition and surface microstructure. However, individual compounds may function as either deterrents or stimulants, depending on the interacting plant and insect species. The review further considers insect counter-adaptations, plant defence signalling, environmental variation and interactions with beneficial organisms. Recent developments in metabolomics, lipid profiling and functional genomics provide opportunities to identify resistance-associated traits and investigate their underlying mechanisms. Nevertheless, the combined effects of specialised metabolites and epicuticular waxes remain insufficiently established through causal experiments and field validation. Future investigations should integrate chemical characterisation, insect behavioural assays, functional validation and multi-environment assessments. Incorporating experimentally validated defensive traits into crop improvement and integrated pest management may contribute to sustainable insect pest suppression while limiting reliance on broad-spectrum insecticides.
Aims: To quantify genetic variability, trait associations and genetic divergence for yield, seed-quality and nutritional traits in finger millet, and to identify selection criteria and parental genotypes for developing high-yielding, nutrient-rich cultivars. Study Design: An alpha lattice design with two replications was used. Place and Duration of Study: Genetics and Plant Breeding Farm, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya, Uttar Pradesh, India, during Kharif 2025. Methodology: Fifty diverse finger millet genotypes were evaluated for seven agro-morphological traits, two seed-quality traits (germination percentage and seed vigour index-I) and three nutritional traits (protein, calcium and iron content). The data were analysed for variance, genetic variability parameters, correlation and path coefficients, and Mahalanobis D² genetic divergence. Results: Iron content (genotypic coefficient of variation 33.05%, heritability 95%, genetic advance as percent of mean 66.51%), calcium content (20.88%, 100%, 43.01%), grain yield per plant (21.40%, 88%, 41.45%), protein content and ear head length exhibited high variability alongside high heritability and genetic advance, indicating good scope for direct selection. Grain yield per plant correlated positively with germination percentage (0.49), seed vigour index-I (0.40) and days to maturity (0.39). Germination percentage (0.877) and days to maturity (0.775) had the largest direct effects, followed by plant height and ear head length. Fourteen clusters were formed; calcium content (35.0%), grain yield per plant (25.0%) and thousand-grain weight (15.0%) contributed 75% of the divergence, with Clusters VIII and XI being the most distant. IC473320, IC475858, IC473207, IC474354 and IC475565 were promising for grain yield; IC475559, IC473332 and IC475858 were the top donors for calcium, iron and protein content, respectively. Conclusion: Germination percentage, days to maturity, plant height, ear head length, protein content and seed vigour index-I are reliable selection criteria, and crosses between the divergent clusters should be rewarding for combining high grain yield with improved nutritional quality in finger millet.
