Sabadilla (Schoenocaulon officinale), a perennial geophytic species with various medicinal properties and historical uses as a natural insecticide or “green pesticide”, has been used by human cultures in the Americas for >2,000 years. Its history parallels the domestication of pyrethrum (Chrysanthemum cinerariifolium) in Europe with similar green pesticidal properties, although the active ingredients differ. Alkaloids extracted from sabadilla seeds have been used to control many insect pests also killed by pyrethrum as well as additional insect pests. With the renewed consumer interest in botanically derived products and the growth of organic chemical industries, S. officinale has re-emerged as a viable source for insect management. To meet market demands, rapid crop domestication must occur. However, sabadilla is an herbaceous perennial geophyte (tunicate bulbs) with an extended juvenility period of at least 64 wks and little is known about the phenotypic and genetic structure of wild populations, alkaloid content variation, and flowering times from seed. Current production is limited to wild-harvested seed (open-pollinated) in Venezuela which is threatening native populations. The purpose of this study was to assess phenotypic and genotypic structure of wild sabadilla populations and seed lots; species comparison with S. texanum were also performed. Through introduction of wild-sourced composite seed into a modern breeding and cropping system, phenotypic traits (rate of seed germination, growth rates, factors of flowering, timing of seed maturity, seed yield, and alkaloid content) were assessed in multiple locations. Genotypic analyses (GBS; DArTseqLD) were used to identify low density SNPs and determine genetic structure within and among wild species populations. Seed lots from varying locations in Venezuela showed distinct SNP arrays with little overlap. SNP-trait association of seed germination weeks was an unexpected, rather tight linkage. Both species are genetically distinct from each other. Phenotypic and genotypic data will be integrated with a genome-wide association study (GWAS) to identify SNP-trait associations and aid in marker-assisted selection.
