Local and regional scale genetic variation in the Cape dune mole-rat, Bathyergus suillus

Abstract

The distribution of genetic variation is determined through the interaction of life history, morphology and habitat specificity of a species in conjunction with landscape structure. While numerous studies have investigated this interplay of factors in species inhabiting aquatic, riverine, terrestrial, arboreal and saxicolous systems, the fossorial system has remained largely unexplored. In this study we attempt to elucidate the impacts of a subterranean lifestyle coupled with a heterogeneous landscape on genetic partitioning by using a subterranean mammal species, the Cape dune mole-rat (Bathyergus suillus), as our model. Bathyergus suillus is one of a few mammal species endemic to the Cape Floristic Region (CFR) of the Western Cape of South Africa. Its distribution is fragmented by rivers and mountains; both geographic phenomena that may act as geographical barriers to gene-flow. Using two mitochondrial fragments (cytochrome b and control region) as well as nine microsatellite loci, we determined the phylogeographic structure and gene-flow patterns at two different spatial scales (local and regional). Furthermore, we investigated genetic differentiation between populations and applied Bayesian clustering and assignment approaches to our data. Nearly every population formed a genetically unique entity with significant genetic structure evident across geographic barriers such as rivers (Berg, Verlorenvlei, Breede and Gourits Rivers), mountains (Piketberg and Hottentots Holland Mountains) and with geographic distance at both spatial scales. Surprisingly, B. suillus was found to be paraphyletic with respect to its sister species, B. janetta-a result largely overlooked by previous studies on these taxa. A systematic revision of the genus Bathyergus is therefore necessary. This study provides a valuable insight into how the biology, life-history and habitat specificity of animals inhabiting a fossorial system may act in concert with the structure of the surrounding landscape to influence genetic distinctiveness and ultimately speciation.

Figure 1. Sampling map of the 10 B. suillus populations in this study.

Map showing the 10 B. suillus collection sites sampled across the Cape Floristic Region of South Africa. The geographic phenomena named in this study are A.) the Sandveld region with A1) the Redelinghuys, A2.) inner-Sandveld and A3.) Vredenburg areas, B.) the Verlorenvlei- and C.) Berg Rivers, D.) the Piketberg mountain, E.) the Hottentots Holland Mountains, F.) the Breede River and G.) the Gourits River. (The sampling map was adapted from ESRI (2007) ArcGIS version 9.3 Media Kit. Redlands, CA: Environmental Systems Research Institute).

Figure 2. Bayesian phylogram and haplotype network demonstrating the different mitochondrial DNA clades across the sampled distribution.

Figure 2A) Bayesian phylogram and B) haplotype networks obtained from the analyses based on combined cytochrome b and control region sequences demonstrating the different mitochondrial DNA clades detected in B. Suillus from localities across the Cape Floristic Region. For the Bayesian tree, a “*” above each node represent an acceptable posterior probability (pP>0.90) value derived from the Bayesian inference (MrBayes and BEAST) analyses and those below nodes are the Maximum Parsimony values (MP>70). A “-” indicate that the grouping was not found by the particular analysis. For the haplotype network, the size of each circle reflects the number of specimens with a particular haplotype. Numbers on branches represent the mutational steps separating haplotypes.

Figure 3. Genetic groupings revealed by the Geneland analysis at regional and local scales.

Genetic groupings revealed by the Geneland analysis of the microsatellite data on a A) regional (Cape Floristic Region) and B) local (Sandveld) spatial scale. Dots reflect the location of each population and the colours correspond to each separate genetic grouping.