Diversification of the African legless skinks in the subfamily Acontinae (Family Scincidae).

Cladogenic diversification is often explained by referring to climatic oscillations and geomorphic shifts that cause allopatric speciation. In this regard, southern Africa retains a high level of landscape heterogeneity in vegetation, geology, and rainfall patterns. The legless skink subfamily Acontinae occurs broadly across the southern African subcontinent and therefore provides an ideal model group for investigating biogeographic patterns associated with the region. A robust phylogenetic study of the Acontinae with comprehensive coverage and adequate sampling of each taxon has been lacking up until now, resulting in unresolved questions regarding the subfamily's biogeography and evolution. In this study, we used multi-locus genetic markers (three mitochondrial and two nuclear) with comprehensive taxon coverage (all currently recognized Acontinae species) and adequate sampling (multiple specimens for most taxa) of each taxon to infer a phylogeny for the subfamily. The phylogeny retrieved four well-supported clades in Acontias and supported the monophyly of Typhlosaurus. Following the General Lineage Concept (GLC), many long-standing phylogenetic enigmas within Acontias occidentalis and the A. kgalagadi, A. lineatus and A. meleagris species complexes, and within Typhlosaurus were resolved. Our species delimitation analyses suggest the existence of hidden taxa in the A. occidentalis, A. cregoi and A. meleagris species groups, but also suggest that some currently recognized species in the A. lineatus and A. meleagris species groups, and within Typhlosaurus, should be synonymised. We also possibly encountered "ghost introgression" in A. occidentalis. Our inferred species tree revealed a signal of gene flow, which implies possible cross-over in some groups. Fossil evidence calibration dating results showed that the divergence between Typhlosaurus and Acontias was likely influenced by cooling and increasing aridity along the southwest coast in the mid-Oligocene caused by the opening of the Drake Passage. Further cladogenesis observed in Typhlosaurus and Acontias was likely influenced by Miocene cooling, expansion of open habitat, uplifting of the eastern Great Escarpment (GE), and variation in rainfall patterns, together with the effect of the warm Agulhas Current since the early Miocene, the development of the cold Benguela Current since the late Miocene, and their co-effects. The biogeographic pattern of the Acontinae bears close resemblance to that of other herpetofauna (e.g., rain frogs and African vipers) in southern Africa.

PhyloPi: An affordable, purpose built phylogenetic pipeline for the HIV drug resistance testing facility.

INTRODUCTION: Phylogenetic analysis plays a crucial role in quality control in the HIV drug resistance testing laboratory. If previous patient sequence data is available sample swaps can be detected and investigated. As Antiretroviral treatment coverage is increasing in many developing countries, so is the need for HIV drug resistance testing. In countries with multiple languages, transcription errors are easily made with patient identifiers. Here a self-contained blastn integrated phylogenetic pipeline can be especially useful. Even though our pipeline can run on any unix based system, a Raspberry Pi 3 is used here as a very affordable and integrated solution. PERFORMANCE BENCHMARKS: The computational capability of this single board computer is demonstrated as well as the utility thereof in the HIV drug resistance laboratory. Benchmarking analysis against a large public database shows excellent time performance with minimal user intervention. This pipeline also contains utilities to find previous sequences as well as phylogenetic analysis and a graphical sequence mapping utility against the pol area of the HIV HXB2 reference genome. Sequence data from the Los Alamos HIV database was analyzed for inter- and intra-patient diversity and logistic regression was conducted on the calculated genetic distances. These findings show that allowable clustering and genetic distance between viral sequences from different patients is very dependent on subtype as well as the area of the viral genome being analyzed. AVAILABILITY: The Raspberry Pi image for PhyloPi, source code of the pipeline, sequence data, bash-, python- and R-scripts for the logistic regression, benchmarking as well as helper scripts are available at http://scholar.ufs.ac.za:8080/xmlui/handle/11660/7638 and https://github.com/ArmandBester/phylopi. The PhyloPi image and the source code are published under the GPLv3 license. A demo version of the PhyloPi pipeline is available at http://phylopi.hpc.ufs.ac.za/.