BACKGROUND: DNA barcoding is a valuable taxonomic tool for rapid and accurate species identification and cryptic species discovery in black flies. Indonesia has 143 nominal species of black flies, but information on their biological aspects, including vectorial capacity and biting habits, remains underreported, in part because of identification problems. The current study represents the first comprehensive DNA barcoding of Indonesian black flies using mitochondrial cytochrome c oxidase subunit I (COI) gene sequences.
METHODS: Genomic DNA of Indonesian black fly samples were extracted and sequenced, producing 86 COI sequences in total. Two hundred four COI sequences, including 118 GenBank sequences, were analysed. Maximum likelihood (ML) and Bayesian inference (BI) trees were constructed and species delimitation analyses, including ASAP, GMYC and single PTP, were performed to determine whether the species of Indonesian black flies could be delineated. Intra- and interspecific genetic distances were also calculated and the efficacy of COI sequences for species identification was tested.
RESULTS: The DNA barcodes successfully distinguished most morphologically distinct species (> 80% of sampled taxa). Nonetheless, high maximum intraspecific distances (3.32-13.94%) in 11 species suggested cryptic diversity. Notably, populations of the common taxa Simulium (Gomphostilbia) cheongi, S. (Gomphostilbia) sheilae, S. (Nevermannia) feuerborni and S. (Simulium) tani in the islands of Indonesia were genetically distinct from those on the Southeast Asian mainland (Malaysia and Thailand). Integrated morphological, cytogenetic and nuclear DNA studies are warranted to clarify the taxonomic status of these more complex taxa.
CONCLUSIONS: The findings showed that COI barcoding is a promising taxonomic tool for Indonesian black flies. The DNA barcodes will aid in correct identification and genetic study of Indonesian black flies, which will be helpful in the control and management of potential vector species.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.