Integrative multivariate analysis of agro-chemical and genotypic traits in Indian catmint (Nepeta cataria L.) half-sib populations.

This investigation conducted a comprehensive multivariate analysis on thirty half-sib populations of Nepeta cataria L., derived from natural populations based on oil yield. The study addresses the lack of comprehensive data on genetic, phenotypic, and chemical diversity in Nepeta cataria, which is essential for material selection and for conducting effective breeding programs. A substantial amount of phenotypic diversity was observed for all eleven quantitative traits measured in the present study. The phenotypic diversity was assessed using Euclidean distance-based agglomerative hierarchical clustering and principal component analysis (PCA) which showed more than 50 % diversity existing among the studied populations. These methods delineated the populations into three primary clusters, where herb yield was a key discriminator. The GC and GC/MS-based chemical profiling of these populations identified eleven major phytochemicals. Though, significant variances in the concentrations of various nepetalactone isomers were noted, correlating with the phenotypic clusters, the major differentiation was observed for cis-trans Nepetalactone (73.45%-93.20 %). Three distinct chemical clusters were defined, each characterized by unique chemical signatures. Molecular diversity was evaluated using 21 Start Codon Targeted Polymorphic (SCoT) and 20 CAAT box-derived DNA Polymorphic (CBDP) markers, revealing high levels of polymorphism. Populations were again grouped into three clusters. A correlative Mantel test performed to determine the association between agro-chemical and genotypic traits revealed minimal correlation between them, indicating a complex interplay between genetic makeup and phenotypic traits across these populations. This study underscores the genetic and chemical diversity within Nepeta cataria half-sib populations, providing insights that could influence future breeding and conservation efforts. The distinct clustering based on agronomic, chemical, and genotypic data highlights the potential for targeted selection and breeding programs within this species. Future research should focus on integrating these findings into breeding strategies for enhancing commercial cultivation.