Maneveldt, Gavin W.Janion-Scheepers, CharlenePitcher, Tristan R.Kgatla, Mahlatse M.Barker, Cassandra2026-06-232026-06-232026Kgatla, M.M., Barker, C., Baxter, J.R., Bester-Van der Merwe, A.E., Chaisi, M., Chakona, A., Cherry, M.I., Daniels, S.R., Du Preez, L.H., Haddad, C.R. and Hawkes, P.G., 2026. An overview of DNA barcoding of biodiversity in South Africa. PLoS One, 21(4), p.e0345173.https://doi.org/10.1371/journal.pone.0345173https://hdl.handle.net/10566/24688The global decline in biodiversity, driven by habitat loss, overexploitation, climate change, biological invasions, and illegal trade, poses significant challenges for conservation management. Although many South African ecosystems and species are under threat, effective conservation efforts are hindered by incomplete foundational biodiversity data and assessments, caused by taxonomic gaps and unverified distributions. DNA barcoding has emerged as an invaluable tool for species identification and classification of biodiversity. While substantial barcoding progress has been made, for many taxa, others remain underrepresented in sequence databases. This study evaluates the status and progress of DNA barcoding in South Africa through a gap analysis, comparing verified species checklists with barcoded sequences from the Barcode of Life Database (BOLD) and GenBank to assess taxonomic and geographic representation. A literature review (2003–2023) highlights applications across terrestrial, freshwater, and marine habitats. Of the 931,476 South African species barcode records, 52% were publicly available. Although the insects dominated with the highest number of records and BINs, reptiles had the highest taxonomic representation. Plants and fungi were underrepresented (16.1% and 2.8%, respectively). Regionally, Mpumalanga and Limpopo provinces showed the highest BIN counts, while North-West and Free State provinces had the lowest. The majority of barcode records were for mtDNA genes such as cytochrome c oxidase subunit I (COI) and were contributed by both local and international institutions. Discrepancies between GenBank records and those mined by BOLD indicated that many GenBank sequences for South Africa have poor quality metadata, including geographic sampling locality information. While significant progress has been made across taxa, further efforts are needed to expand species and geographic coverage, enhance sequence quality, improve species metadata, and resolve inconsistencies in BIN assignments, particularly for underrepresented groups such as plants and fungi. These advances would strengthen biodiversity assessments and support conservation efforts in South Africa.enBiodiversityConservation of natural resourcesDNA barcodingTaxonomicEcosystemArticle