A molecular diagnostic for identifying central Africa forest artiodactyls from faecal pellets. - (:unkn) unknown (My University, 2010)
Small to medium-sized central African forest artiodactyls constitute a diverse yet heavily hunted group composed primarily of species within the genera Cephalophus, Neotragus, Tragelaphus and Hyemoschus. Of these genera, Cephalophus is the richest with as many as seven sympatric species known to occur in central African forests. However, differentiating species from their faeces or from tissue where the whole carcass is unavailable is very difficult. In order to develop a robust molecular diagnostic for species identification, a database of mitochondrial cytochrome b (553 bp) and control region (675 bp) sequences was compiled from all forest Cephalophus species and other similarly sized, sympatric Tragelaphus, Neotragus and Hyemoschus species. Reference phylogenies from each marker were then used to recover the identity of sequences obtained from unknown faecal samples collected in the field. Results were then compared to determine which region best recovered species identity with the highest statistical support. Restriction fragment length polymorphisms (RFLPs) were also assessed as an alternative method for rapid species identification. Of themethods examined, tree-based analyses built on a geographically comprehensive database of control region sequences was the best means of reliably recovering species identity from central African duikers. However, three sister taxa appear indistinguishable (Cephalophus callipygus, Cephalophus ogilbyi and Cephalophus weynsi) and not all species were monophyletic. This lack of monophyly may be due to incomplete lineage sorting commonly observed in recently derived taxa, hybridization or the presence of nuclear translocated copies of mitochondrial DNA. The high level of intra-specific variation and lack of robust species-specific diagnostic sites made an RFLP-based approach to duiker species identification difficult to implement. The tree-based control region diagnostic presented here has many important applications
Keywords: African Research