3 RAD ‐Guided SNP Discovery for Species Identification and Conservation of the Medicinal Southern African Tree Genus Greyia Hook. & Harv.

ABSTRACT Accurate species identification is essential for conserving and managing plants that provide important ecosystem services and have ethnobotanical value. The Greyia tree genus ( G. sutherlandii , G. radlkoferi and G. flanaganii ) is endemic to South Africa and Eswatini, and certain genotypes have medicinal value for treating skin hyper‐pigmentation. However, distinguishing among species is difficult because of overlapping phenotypes and the limited resolution of standard DNA barcodes. To overcome these limitations, a robust molecular identification assay was developed using a two‐phase strategy. First, de novo SNP discovery using 3RAD sequencing identified 47,726 genome‐wide SNPs from two to three plants sampled from each species' core geographic range: G. radlkoferi in northern Limpopo, G. sutherlandii in eastern KwaZulu‐Natal, and G. flanaganii in the south‐eastern Eastern Cape. Principal component analysis and coancestry matrices revealed three discrete genetic clusters, supporting the recognition of the three species. Selecting a set of 200 SNPs with intermediate Fst values (0.2–0.5) resulted in optimal separation of the three clusters. This led to the final selection of a 23‐SNP panel that included five informative barcoding loci (ITS, trnL‐F , matK ). Second, the 23 SNPs were converted into allele‐specific fluorescent PCR assays (SNP Type) for genotyping on the BioMark HD platform. The panel was validated using genomic DNA from 17 individuals from the 3RAD population groups and successfully differentiated all three species. It was then applied to 73 trees sampled across a 1000‐km transect from the Eastern Cape to Limpopo. Genetic clustering (PCA, UPGMA and ADMIXTURE) assigned each tree to one of three species‐level groups matching their expected ranges. In a practical case study, the assay also identified the species origin of 33 Greyia trees of unknown provenance from production orchards. This study provides an efficient SNP‐based tool for accurate species identification, supporting conservation planning and the sustainable management of Greyia populations.