Genomic Selection for Combined Disease Resistance and Secondary Metabolite Quality in Medicinal Plants: Frameworks, Challenges, and a Strategic Roadmap

Abstract

Background: Medicinal plants represent an irreplaceable source of pharmacologically active secondary metabolites, yet breeding programs targeting these species face a structurally distinctive dual challenge: achieving simultaneous genetic improvement of secondary metabolite content while enhancing disease resistance and agronomic stability. These objectives are biologically non-independent, since terpenoids, alkaloids, and phenolics function both as pharmaceutical active ingredients and as components of the plant's chemical defense system. Methods: Genomic selection (GS), which uses genome-wide markers to estimate genomic estimated breeding values for all quantitative traits concurrently, offers a transformative framework for addressing this challenge. Results: Multi-trait GS models leverage genetic correlations between resistance and metabolite traits to improve prediction accuracy for both objectives simultaneously, and integrating metabolomic and transcriptomic data as covariates substantially enhances accuracy for complex, environmentally sensitive metabolite traits. Despite rapid advances in genomic resources for numerous medicinal species, no published GS program currently targets secondary metabolite quality in any major medicinal plant. Conclusions: Critical barriers include the absence of genotyped training populations, narrow genetic bases, prohibitive metabolite phenotyping costs, and substantial genotype-by environment interactions.