Harnessing the untapped genetic diversity of local landraces: omics technologies as a gateway to horticultural breeding

Abstract

Horticultural crops, particularly Solanaceae and Cucurbitaceae, represent a major component of global vegetable production and are increasingly exposed to climate variability and environmental constraints. Landraces and crop wild relatives constitute essential reservoirs of adaptive genetic diversity; however, their effective utilization in breeding programs remains limited by fragmented characterization, incomplete passport information, and reliance on labor-intensive morphological descriptors. These limitations hinder the systematic exploitation of conserved germplasm and restrict its integration into modern predictive breeding frameworks. Recent advances in high-throughput phenotyping, genomics, and multi-omics technologies have created new opportunities to bridge the gap between genotype and phenotype. Next-generation phenomics enables non-destructive, high-resolution quantification of plant physiological and structural traits across environments, while genomic approaches, including whole-genome resequencing, support comprehensive assessment of genetic diversity. Pangenome frameworks further extend this resolution by capturing core and variable genomic fractions, collectively defining the species variome and enabling improved identification of structural and allelic variants associated with adaptive traits. The integration of phenomic and genomic datasets through multi-omics approaches enhances the functional interpretation of trait-associated variation and strengthens the predictive capacity of breeding strategies. In this context, the genome as a functional passport constitutes a unified reference layer linking germplasm identity with genomic, phenotypic, and functional trait information, thereby enabling more systematic germplasm characterization, reduced redundancy, and improved identification of elite parental material. This mini-review highlights how the integration of phenomics, pangenomics, and multi-omics enables the transition from descriptive germplasm cataloguing toward more systematic, data-driven, and predictive breeding systems for the development of climate-resilient horticultural crops.