DNA-based species delineation in tropical beetles using mitochondrial and nuclear markers

Abstract

DNA barcoding has been successfully implemented in the identification of previously described species, and in the process has revealed several cryptic species. It has been noted that such methods could also greatly assist in the discovery and delineation of undescribed species in poorly studied groups, although to date the feasibility of such an approach has not been examined explicitly. Here, we investigate the possibility of using short mitochondrial and nuclear DNA sequences to delimit putative species in groups lacking an existing taxonomic framework. We focussed on poorly known tropical water beetles (Coleoptera: Dytiscidae, Hydrophilidae) from Madagascar and dung beetles (Scarabaeidae) in the genus Canthon from the Neotropics. Mitochondrial DNA sequence variation proved to be highly structured, with >95% of the observed variation existing between discrete sets of very closely related genotypes. Sequence variation in nuclear 28S rRNA among the same individuals was lower by at least an order of magnitude, but 16 different genotypes were found in water beetles and 12 genotypes in Canthon , differing from each other by a minimum of two base pairs. The distribution of these 28S rRNA genotypes in individuals exactly matched the distribution of mtDNA clusters, suggesting that mtDNA patterns were not misleading because of introgression. Moreover, in a few cases where sequence information was available in GenBank for morphologically defined species of Canthon , these matched some of the DNA-based clusters. These findings demonstrate that clusters of close relatives can be identified readily in the sequence variation obtained in field collected samples, and that these clusters are likely to correspond to either previously described or unknown species. The results suggest that DNA-assisted taxonomy will not require more than a short fragment of mtDNA to provide a largely accurate picture of species boundaries in these groups. Applied on a large scale, this DNA-based approach could greatly improve the rate of species discovery in the large assemblages of insects that remain undescribed.