Abstract

The morphological identification of cryptic rodent species has historically been problematic. At best, many cryptic species have been identified by chromosomal differences. However, to study the life histories of such rodent species, there is a need for a molecular technique for cryptic species identification that does not involve destructive sampling. In this manuscript we examine mitochondrial DNA (mtDNA) cytochrome-b genetic variation in 2 cryptic murid rodent species, the red veld rat (Aethomys chrysophilus) and the Tete veld rat (A. ineptus) from southern Africa. Phylogenetic and phylogeographic analyses of these sequences showed reciprocal monophyly between populations of the 2 species in southern Africa, but no support for monophyly of A. chrysophilus from southern and eastern Africa. This suggests that the analysis of mtDNA can be used to distinguish these 2 sister species in southern Africa. However, these results need to be investigated further by DNA analyses of type specimens, topotypical material, or both from adjacent localities.

Correct species identification is important for ecological, evolutionary, systematic, and other comparative biological studies. Species identification also may have implications in epidemiological research associated with problem rodents, such as some members of the genus Aethomys (Gear et al. 1966; Hallet et al. 1970; Swanepoel et al. 1978). In South Africa, Mastomys natalensis acts as plague reservoir but its sibling species M. coucha does not (Arntzen et al. 1991). However, because of phenotypic conservatism, sibling species are often difficult to identify using morphology. Consequently, karyology is widely used to distinguish these species (Robinson et al. 1986; Watson 1987). The problem of identifying sibling species is particularly prevalent in southern Africa, where a number of small, morphologically cryptic mammal species have been discovered over the past 25 years (Bronner et al. 2003). The present study attempts to identify sibling species using a genetic approach, focusing on recently recognized species within the morphologically invariant, but chromosomally diverse genus Aethomys.

The red veld rat (Aethomys chrysophilus (sensu lato) (De Winton, 1897)), has conventionally been regarded as widely distributed in East, Central, and southern Africa including southeastern Kenya, Tanzania, Zambia, Angola, Malawi, Namibia (excluding the western desert region), northern and eastern Botswana, Zimbabwe, and central and northern South Africa (Meester et al. 1986; Skinner and Smithers 1990). Several studies revealed that A. chrysophilus has 2 electrophoretically distinct cytotypes (2n = 44 and 2n = 50) that differed in gross sperm and bacular morphology and show no evidence of hybridization in areas of sympatry (Baker et al. 1988; Breed et al. 1988; Gordon and Rautenbach 1980; Gordon and Watson 1986; Visser and Robinson 1986, 1987). In a systematic revision based on morphometric and qualitative morphological data, Chimimba (1998) elevated A. chrysophilus ineptus to A. ineptus (Tete veld rat—Thomas and Wroughton, 1908) and recognized its occurrence alongside the nominate A. chrysophilus (De Winton, 1897) in southern Africa. Chimimba et al. (1999) confirmed these conclusions by examining the type specimens of A. chrysophilus (BM 95.11.3.23 [original number 54], a female from Mazoe, Mashonaland, eastern Zimbabwe) and A. ineptus (BM 8.4.3.73 [original number 1949], a male from Tete, Mozambique). Moreover, Chimimba et al. (1999) showed that their A. chrysophilus and A. ineptus correspond, respectively, to the 2n = 50 and 2n = 44 cytotypes previously identified. Using the diagnostic morphological and cytogenetic traits established by Chimimba et al. (1999), Linzey et al. (2003) documented the distributional limits of A. chrysophilus and A. ineptus in southern Africa (Fig. 1).

Fig. 1

Collecting localities of Aethomys chrysophilus and A. ineptus in southern Africa. Numbers in circles and squares correspond to locality numbers and names in Appendix I. The areas shaded with gray dots and vertical lines indicate the hypothesized distributions of A. chrysophilus and A. ineptus, respectively (Linzey et al. 2003). Localities indicated with double squares and circles represent collecting localities of positively identified individuals of A. chrysophilus and A. ineptus, respectively, and the dark line indicates the Limpopo River flowing into the Indian Ocean.

Fig. 1

Collecting localities of Aethomys chrysophilus and A. ineptus in southern Africa. Numbers in circles and squares correspond to locality numbers and names in Appendix I. The areas shaded with gray dots and vertical lines indicate the hypothesized distributions of A. chrysophilus and A. ineptus, respectively (Linzey et al. 2003). Localities indicated with double squares and circles represent collecting localities of positively identified individuals of A. chrysophilus and A. ineptus, respectively, and the dark line indicates the Limpopo River flowing into the Indian Ocean.

Additional intraspecific morphometric analyses of these sibling species provided support for 2 of the 9 previously recognized subspecies within A. chrysophilus (sensu lato), A. c. acticola (Thomas and Wroughton, 1908) and A. c. imago (Thomas, 1927), to be provisionally retained within A. chrysophilus as subspecies (Chimimba 2000, 2001; Chimimba et al. 1999). The morphological distinction between these proposed subspecies coincided with an altitudinal limit in the eastern part of southern Africa (Clark 1967), with A. c. chrysophilus and A. c. imago occurring below and above an altitude of 500 m, respectively (Chimimba 2000). The 7 remaining subspecies were reallocated to A. ineptus and provisionally treated as junior synonyms (Chimimba 2000, 2001; Chimimba et al. 1999). Therefore, on morphological grounds, Chimimba et al. (1999) and Chimimba (2000, 2001) argued for the recognition of 2 subspecies within A. chrysophilus from southern Africa. Subspecies recognition within A. ineptus is a problem because of clinal morphometric variation.

Initial studies (Chimimba et al. 1999; Gordon and Rautenbach 1980) suggested an extensive distributional overlap between the 2 sibling species in southern Africa. Recently, however, distributions derived from positively identified (i.e., by cytogenetic, protein electrophoresis, or mitochondrial DNA [mtDNA] analyses, or a combination of these) specimens from South Africa suggested that A. chrysophilus is restricted to low-lying areas of the Limpopo River drainage system in northern South Africa. In contrast, examination of the available data suggests that A. ineptus occurs further south in the central parts of South Africa (Linzey et al. 2003; Fig. 1).

A number of cytogenetic, protein electrophoretic, morphological (sperm, bacular, cranial, or a combination of these), and morphometric studies have drawn attention to the presence of sibling rodent species in southern Africa (see Bronner et al. [2003] and references therein). However, results of these studies have not been tested using high-resolution DNA sequence data. For example, sequences of the mitochondrial cytochrome-b gene have been used to identify sibling species in several other rodent groups (e.g., Bell et al. 2001; Bradley and Baker 2001; Bradley et al. 2000; Peppers and Bradley 2000). To this end, the present study used phylogenetic analysis of cytochrome-b sequences to assess both intra- and interspecific molecular variation within A. chrysophilus and A. ineptus from southern Africa. We tested whether mtDNA can be used to distinguish between these morphologically cryptic taxa. Additionally, the results were interpreted with reference to specimens positively identified through a multidisciplinary approach by Linzey et al. (2003). We also investigated these taxa with regard to possible influences of climate change on their evolutionary history.

Materials and Methods

Study area and sampling.—Samples (ear or toe clips) were obtained from 18 localities in southern Africa, representative of the proposed South African distribution of the species (Fig. 1; Appendix I). A. ineptus was represented by 15 localities, whereas samples from only 4 geographically restricted localities were collected for A. chrysophilus (Fig. 1). Some individuals examined had previously been karyotyped (analysis of the pairs of metaphase chromosomes of an individual cell, arranged in pairs and sorted according to size—Linzey et al. 2003) and these were used as references for species designations (Fig. 1). This study was undertaken under the guidelines of the American Society of Mammalogists (Animal Care and Use Committee 1998) and was approved by the Animal Ethics Committee of the University of Pretoria (project EC 010417-004).

Laboratory protocols.—Total genomic DNA was extracted from tissue using a standard phenol-chloroform protocol (Sambrook et al. 1989). Sequences for A. chrysophilus (AF004587—Ducroz et al. 1998) and Mus musculus (J01420—Bibb et al. 1981) from GenBank were used to design a specific internal primer for the present study (H14709, 5′-CATTTCAGGTTTACAAGAC-3 '). Primers employed in this study are designated “H” or “L” to indicate their complementarity to the heavy or light strands, respectively, of the mtDNA molecule. Primer numbers refer to the position of 3′ nucleotide in each primer in the M. musculus mitochondrial genome. H14709 was used in combination with 2 published primers, L14115 (a shortened version of L14724 in Pääbo et al. [1988]) and L14233 (L14841 of Kocher et al. [1989]). The L14115-H14709 and L14233-H14709 primer pairs produced amplicons of 594 base pairs (bp) and 476 bp, respectively. Sequences of 370 bases from these amplicons were obtained for analysis. In some individuals, the complete cytochrome-b gene was amplified with primers L14115 and HI5309 (a M. musculus version of H15915 from Irwin et al. [1991]). Sequences of 1,008 bases from these amplicons were obtained for analysis.

Amplifications using polymerase chain reaction (Saiki et al. 1988) were performed in a total volume of 50 µl as described by Russo (2003). Dye-terminator cycle sequencing was performed for both the light (L14724 or L14841) and heavy (H14709 or H15309) strands according to the manufacturer's instructions (Applied Biosystems, Johannesburg, South Africa). Nucleotide sequences were determined using either an ABI 377 or an ABI 3100 automated sequencer (Applied Biosystems).

Sequencing analysis.—The quality of the raw sequence data was evaluated in Sequencing Analysis version 3 (Applied Biosystems), and a consensus sequence for each individual from forward and reverse sequences was determined in Sequence Navigator version 1.01 (Applied Biosystems). These sequences were deposited in GenBank under accession numbers AY585656-AY585676, excluding the sequences that were generated for a longer fragment. These accessions represent all unique haplotypes identified in the present study, but for each the relevant geographic information also is included (i.e., the localities of all individuals showing the same sequence).

Consensus sequences of all individuals were aligned in Clustal X (Thompson et al. 1997), and subsequent phylogenetic analyses were performed in PAUP version 4.0b 10 (Swofford 2002).

Phylogenetic analyses.—Modeltest version 3.06 (Posada and Crandall 1998) was used to determine the best-fit model of DNA substitution for the 370-base and 1,008-base sequences under the Akaike information criterion. Parameters such as base frequencies, transition : transversion (Ti:Tv) ratio, the shape parameter of the gamma distribution of rates among sites (Yang 1996; Yang et al. 1994), and the proportion of invariable sites (I) were estimated in conjunction with the models. The chosen models were subsequently used in distance, maximum-likelihood, and Bayesian phylogenetic analyses.

The selection of possible outgroups for A. chrysophilus and A. ineptus was difficult because previous studies linked the genus to numerous other murids (Chimimba [2005] and references therein). African rock rats of the genus Aethomys (Thomas 1915) represent a diverse group of rodents endemic to East, Central, and southern Africa, with a marginal extension into West Africa (Musser and Carleton 1993). The genus is currently considered to include 11 species, traditionally allocated to 2 subgenera, Aethomys and Micaelamys (Chimimba 2005). Based on a previous phylogenetic study (Castiglia et al. 2003), A. kaiseri (subgenus Aethomys; AJ604520 of Castiglia et al. [2003]) from Zambia, Central Africa, was selected as the suitable outgroup in all phylogenetic analyses. In addition, 3 A. chrysophilus individuals from Tanzania were included (AF004587 of Ducroz et al. [2001], and AJ604526 and AJ604524 of Castiglia et al. [2003]) for a preliminary assessment of evolutionary relationships between southern and eastern African A. chrysophilus.

Two separate analyses were conducted, 1 using all haplotypes of the 370-bp fragment and a 2nd based on sequences of the 1,008-bp fragment from representatives of 2 major lineages (A and B) identified in trees derived from the shorter sequences. Nodal support was assessed by 1,000 bootstrap replicates (Felsenstein 1985) for distance, maximum-parsimony, and maximum-likelihood analyses.

Neighbor-joining trees (Saitou and Nei 1987), parsimony trees (Farris et al. 1970; Kluge and Farris 1969), and maximum-likelihood trees (Felsenstein 1973, 1981) were obtained with the program PAUP version 4.0b 10 (Swofford 2002). For parsimony analyses, nucleotides were treated as unordered characters and the heuristic search option with tree-bisection-reconnection was employed. Phylogenetic signal in the data was evaluated by the tree-length distribution of 1,000 randomly generated trees using the g1 statistic (Hillis and Huelsenbeck 1992). Bayesian phylogenetic inference employed MrBayes 3 software (Ronquist and Huelsenbeck 2003). Three independent analyses of 4 chains were run for 3 × 106 generations for each of the data sets. Trees and parameters were recorded every 100 generations. All runs used the default heating and swap parameters. We excluded the first 500 generations as the “burn-in.”

A relative rate test was performed using RRTree (Robinson-Rechavi and Huchon 2000) to assess differences in the 3rd-position transversion rates among separate lineages relative to A. kaiseri as a reference taxon (Robinson et al. 1998; Robinson-Rechavi and Huchon 2000). A specific rate of change calibrated on murid rodent data was determined because murid mtDNA evolves at a faster rate than that of other rodents (Catzeflis et al. 1992). Sequence data from Rattus rattus and M. musculus, with a divergence time estimated at 12 million years ago, was used as a calibration point (Jacobs and Downs 1994). The significance threshold (traditionally 5%) was adjusted by dividing the alpha level by the number of pairwise comparisons (Robinson-Rechavi and Huchon 2000), akin to a Bonferroni adjustment (Bonferroni 1935). In addition, a likelihood ratio test (Felsenstein 1988) in PAUP version 4.0b 10 was used to test the null hypothesis that sequences were evolving at constant rates and, therefore, fit a molecular clock.

Although the use of molecular clocks is much debated and estimated divergence times are surrounded by uncertainty (Graur and Martin 2004), we wanted to obtain tentative divergence times for the sibling species. It has been suggested that 3rd-position transversions should be used as a measure of genetic divergence because of near-linear accumulation with time (Irwin et al. 1991). Our results showed, on average, 0.4 transversions between A. chrysophilus from South Africa and A. ineptus. The divergence between Mus and Rattus is commonly used as a calibration point. However, this point is not without controversy (Adkins et al. 2001; Steppan et al. 2004). For example, divergence dates of 10 million years ago (Smith and Patton 1999), 12 million years ago (Jacobs and Downs 1994), 23 million years ago (Adkins et al. 2001), and 41 million years ago (Kumar and Hedges 1998) have been suggested. The divergence time of 12 million years ago is based on the fossil record (Jacobs and Downs 1994), and we preferentially followed this dating because it provides a specific rodent calibration. The use of a nonrodent divergence date as a calibration point results in divergence times much older than the paleontological record (Kumar and Hedges 1998).

Phylogeographic analysis.—The minimum number of base substitutions between haplotypes was determined using MINSPNET (Excoffier and Smouse 1994). A minimum-spanning network, in combination with frequency and locality data, was used to depict geographic and ancestor-descendant relationships among haplotypes.

Results

Sequence statistics.—A total of 370 bp of the 5′ end of the cytochrome-b gene was compared among all individuals of A. chrysophilus and A. ineptus examined. In addition, longer fragments of 1,008 bp were generated for some individuals but sequence statistics are based on the shorter fragments. There are 25 variable positions, which define 21 haplotypes (Fig. 2). Of the 25 variable sites (excluding the outgroup and A. chrysophilus from Tanzania), 13 are phylogenetically informative. Three informative sites are 1st codon positions and 10 are 3rd positions. Most substitutions are silent; there are only 3 variable amino acid sites between the most divergent lineages.

Fig. 2

Variable sites of the 21 mitochondrial DNA cytochrome-b haplotypes (370 base pairs) of Aethomys chrysophilus (H17−H21) and A. ineptus (H01−H16) from southern Africa. Variable positions 5 and 346 correspond to positions 14247 and 14588 of Mus musculus (Bibb et al. 1981). Dots (.) indicate identity to the base in the reference sequence H01 and question marks (?) indicate undetermined bases.

Fig. 2

Variable sites of the 21 mitochondrial DNA cytochrome-b haplotypes (370 base pairs) of Aethomys chrysophilus (H17−H21) and A. ineptus (H01−H16) from southern Africa. Variable positions 5 and 346 correspond to positions 14247 and 14588 of Mus musculus (Bibb et al. 1981). Dots (.) indicate identity to the base in the reference sequence H01 and question marks (?) indicate undetermined bases.

Model of evolution.—The best-fit model for the 370-base sequences, based on Akaike information criterion values, is that of Tamura and Nei (1993), with an overall equal rate of change among variable sites and a proportion of invariable sites estimated as 0.7605 (i.e., a TrN+I model). The overall Ti:Tv ratio was estimated at 32:1 (excluding the outgroup and A. chrysophilus from Tanzania). The best-fit model for the longer sequences is also that of Tamura and Nei (1993), but with gamma distributed rates among sites (Gu and Zhang 1997) and an estimated shape parameter equal to 0.2638 (i.e., a TrN+G model).

Phylogenetic analyses.—Corrected sequence-divergence estimates (TrN+I model of substitution; Table 1) were used to summarize relationships among the 21 haplotypes in a neighbor-joining tree (Saitou and Nei 1987; Fig. 3A). Based on the inclusion of individuals that had previously been positively identified (indicated in gray in Fig. 3A), haplotypes H01−H16 represent A. ineptus, whereas haplotypes H17−H21 represent A. chrysophilus. The average separation between A. chrysophilus and A. ineptus is 2.70% (range = 1.69–3.78%). We also corrected for within-species variation using the equation of Nei and Li (1979) and obtained a net divergence of 1.64% between the species. This lower corrected value of between-species variation is probably a result of the high levels of genetic variation within A. chrysophilus. Pairwise estimates of sequence divergence between haplotypes within A. ineptus are generally low, ranging between 0.27% and 1.65%, with an average divergence of 0.80%. Greater divergences over a small geographic area were detected within A. chrysophilus from southern Africa with the average sequence divergence estimated at 1.32% (range = 0.27–2.15%).

Table 1

Pairwise estimates of Tamura-Nei sequence divergence (%) between 21 maternal haplotypes within Aethomys chrysophilus (H17−H21) and A. ineptus (H01−H16) from southern Africa (see Fig. 1 and Appendix I). Individuals of A. chrysophilus from Tanzania (H22, H23, and H24) as well as the outgroup, A. kaiseri (H25) were included.

Haplotype number H01 H02 H03 H04 H05 H06 H07 H08 H09 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 H25 
H01                          
H02 0.27                         
H03 0.55 0.28                        
H04 0.27 0.27 0.55                       
H05 0.55 0.27 0.54 0.54                      
H06 0.55 0.27 0.55 0.55 0.54                     
H07 0.28 0.55 0.27 0.82 0.82 0.82                    
H08 0.27 0.55 0.82 0.82 0.83 0.82 0.54                   
H09 0.55 0.83 1.11 0.82 1.10 1.10 0.83 0.82                  
H10 1.10 0.82 1.09 1.09 1.10 1.09 1.37 1.38 1.66                 
H11 0.82 0.55 0.82 0.82 0.82 0.82 1.10 1.09 1.38 0.82                
H12 0.83 0.56 0.82 0.82 0.82* 0.82 1.10 1.09 1.39 0.82 0.55               
H13 0.28 0.55 0.82 0.82 0.82 0.82 0.55 0.54 0.83 1.37 1.10 1.10              
H14 0.56 0.83 1.10 1.10 1.09 1.10 0.82 0.82 1.11 1.65 1.38 1.38 0.27             
H15 0.55 0.82 1.09 1.09 1.10 1.09 0.82 0.82 0.55 1.11 0.82 0.82 0.82 1.10            
H16 0.55 0.27 0.55 0.55 0.54 0.55 0.82 0.82 1.10 0.55 0.27 0.27 0.82 1.10 0.55           
H17 2.28 1.99 2.24 2.24 2.22 2.24 2.52 2.50 2.85 2.52 2.54 2.54 2.52 2.81 2.79 2.24          
H18 2.30 2.55 2.81 2.81 2.79 2.81 2.53 2.51 2.87 2.81 3.11 3.11 1.95 2.24 2.81 2.81 1.37         
H19 2.88 3.16 3.44 3.44 3.42 3.44 3.15 3.11 3.20 3.44 3.78 3.78 2.48 2.81 3.46 3.44 2.15 0.60        
H20 2.57 2.83 3.09 3.09 2.51 3.09 2.81 2.79 3.15 3.66 3.39 3.39 2.22 2.51 3.09 3.09 1.93 0.83 1.51       
H21 1.98 1.69 1.95 1.95 1.94 1.95 2.22 2.21 2.55 2.22 2.24 2.24 2.22 2.52 2.50 1.95 0.27 1.09 1.82 1.65      
H22 4.60 4.87 5.43 5.43 4.83 5.43 5.14 5.13 4.62 5.73 5.74 5.74 4.53 4.83 4.84 5.43 4.54 3.94 4.70 3.94 4.24     
H23 4.91 5.15 6.07 6.07 5.46 6.07 5.78 5.75 4.94 6.36 6.39 5.75 5.15 5.46 5.50 6.07 6.42 5.78 6.14 5.78 6.10 2.79    
H24 5.23 5.47 6.39 6.39 5.78 6.39 6.10 6.07 5.26 6.68 6.72 6.07 5.46 5.78 5.82 6.39 6.75 6.10 6.49 6.10 6.43 3.09 0.27   
H25 15.22 15.89 15.16 15.17 15.30 16.04 14.86 15.00 14.48 15.91 15.18 15.17 14.86 15.30 15.00 15.60 15.70 14.86 14.78 14.86 16.15 15.83 14.24 13.82  
Haplotype number H01 H02 H03 H04 H05 H06 H07 H08 H09 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 H25 
H01                          
H02 0.27                         
H03 0.55 0.28                        
H04 0.27 0.27 0.55                       
H05 0.55 0.27 0.54 0.54                      
H06 0.55 0.27 0.55 0.55 0.54                     
H07 0.28 0.55 0.27 0.82 0.82 0.82                    
H08 0.27 0.55 0.82 0.82 0.83 0.82 0.54                   
H09 0.55 0.83 1.11 0.82 1.10 1.10 0.83 0.82                  
H10 1.10 0.82 1.09 1.09 1.10 1.09 1.37 1.38 1.66                 
H11 0.82 0.55 0.82 0.82 0.82 0.82 1.10 1.09 1.38 0.82                
H12 0.83 0.56 0.82 0.82 0.82* 0.82 1.10 1.09 1.39 0.82 0.55               
H13 0.28 0.55 0.82 0.82 0.82 0.82 0.55 0.54 0.83 1.37 1.10 1.10              
H14 0.56 0.83 1.10 1.10 1.09 1.10 0.82 0.82 1.11 1.65 1.38 1.38 0.27             
H15 0.55 0.82 1.09 1.09 1.10 1.09 0.82 0.82 0.55 1.11 0.82 0.82 0.82 1.10            
H16 0.55 0.27 0.55 0.55 0.54 0.55 0.82 0.82 1.10 0.55 0.27 0.27 0.82 1.10 0.55           
H17 2.28 1.99 2.24 2.24 2.22 2.24 2.52 2.50 2.85 2.52 2.54 2.54 2.52 2.81 2.79 2.24          
H18 2.30 2.55 2.81 2.81 2.79 2.81 2.53 2.51 2.87 2.81 3.11 3.11 1.95 2.24 2.81 2.81 1.37         
H19 2.88 3.16 3.44 3.44 3.42 3.44 3.15 3.11 3.20 3.44 3.78 3.78 2.48 2.81 3.46 3.44 2.15 0.60        
H20 2.57 2.83 3.09 3.09 2.51 3.09 2.81 2.79 3.15 3.66 3.39 3.39 2.22 2.51 3.09 3.09 1.93 0.83 1.51       
H21 1.98 1.69 1.95 1.95 1.94 1.95 2.22 2.21 2.55 2.22 2.24 2.24 2.22 2.52 2.50 1.95 0.27 1.09 1.82 1.65      
H22 4.60 4.87 5.43 5.43 4.83 5.43 5.14 5.13 4.62 5.73 5.74 5.74 4.53 4.83 4.84 5.43 4.54 3.94 4.70 3.94 4.24     
H23 4.91 5.15 6.07 6.07 5.46 6.07 5.78 5.75 4.94 6.36 6.39 5.75 5.15 5.46 5.50 6.07 6.42 5.78 6.14 5.78 6.10 2.79    
H24 5.23 5.47 6.39 6.39 5.78 6.39 6.10 6.07 5.26 6.68 6.72 6.07 5.46 5.78 5.82 6.39 6.75 6.10 6.49 6.10 6.43 3.09 0.27   
H25 15.22 15.89 15.16 15.17 15.30 16.04 14.86 15.00 14.48 15.91 15.18 15.17 14.86 15.30 15.00 15.60 15.70 14.86 14.78 14.86 16.15 15.83 14.24 13.82  
Fig. 3

A) Neighbor-joining phylogram based on 370 base pairs of the cytochrome-b gene and B) a maximum-likelihood tree based on the longer sequences, showing clustering of 21 mitochondrial DNA haplotypes within Aethomys chrysophilus and A. ineptus from southern Africa into 2 lineages. Bootstrap values (percentage occurrence in 1,000 replicates) for internal nodes are given at each node (below or above the branches). Haplotypes from positively identified individuals of A. chrysophilus and A. ineptus are indicated in gray.

Fig. 3

A) Neighbor-joining phylogram based on 370 base pairs of the cytochrome-b gene and B) a maximum-likelihood tree based on the longer sequences, showing clustering of 21 mitochondrial DNA haplotypes within Aethomys chrysophilus and A. ineptus from southern Africa into 2 lineages. Bootstrap values (percentage occurrence in 1,000 replicates) for internal nodes are given at each node (below or above the branches). Haplotypes from positively identified individuals of A. chrysophilus and A. ineptus are indicated in gray.

Parsimony and maximum-likelihood analyses (results not shown) gave the same topology as the neighbor-joining tree (Fig. 3A). Parsimony statistics included 24 parsimony informative characters (including outgroup), number of trees = 1, tree length = 31, consistency index = 0.84, retention index = 0.90, and rescaled consistency index = 0.76. The data also were significantly more structured than expected from random data (g1 = −1.22, P < 0.01). All analyses showed moderate bootstrap support for the genetically distinct lineage A that corresponds to A. ineptus. In contrast, bootstrap values were lower in all analyses for lineage B, representing A. chrysophilus from southern Africa (Fig. 3A). The neighbor-joining tree showed paraphyly of Tanzania and southern African A. chrysophilus (Figs. 3A and 3B). Based on the analyses of the short sequences, representatives of each lineage were used to conduct a maximum-likelihood analysis (Fig. 3B) using longer sequences (Ti:Tv ratio = 6:1; proportion of A = 0.31, C = 0.27, G = 0.13, and T = 0.29 as estimated in Modeltest). This tree is consistent with the one in Fig. 2A. The Bayesian analyses (results not shown) also confirmed the paraphyly of A. chrysophilus from southern Africa and Tanzania.

The relative rate test showed no significant differences in substitution rates between lineages relative to a reference taxon at the adjusted significance level of 0.02% (P ≥ 0.0002). In addition, the log-likelihood ratio test of clocklike evolution failed to reject a molecular clock (χ2 = 5.233, d.f. = 8). Although support for the monophyly of A. chrysophilus from southern Africa was moderate to weak, we still estimated a divergence date between this group and A. ineptus (see Figs. 3A and 3B). The fossil date of 12 million years ago for Mus-Rattus separation yields a rodent calibration of 1.89% transversions per 3rd position per million years. Given an average of 0.4 transversion differences (0.33%) between haplotypes of A. ineptus and southern A. chrysophilus, the time of divergence separating these species was estimated at approximately 170,000 years ago (range = 0–30,162 years ago, reflecting the observed range of 0–1 3rd-position trans versions between species). Similarly, the average time of divergence separating Tanzan A. chrysophilus from southern African A. chrysophilus and from A. ineptus was estimated at 858,000 and 716,000 years ago, respectively. The separation between A. kaiseri and all ingroups was estimated at 2.50 million years ago.

Phylogeographic analysis.—A minimum-spanning network (Fig. 4) supported the 3 lineages delineated in the neighbor-joining phylogram (Fig. 3A). These lineages differed by 6 and 14 mutational steps, respectively, with no shared haplotypes between them (Fig. 4). Lineage A was characterized by 16 closely related haplotypes over a wide geographic area with haplotype H01 being the most widespread. This haplotype was shared by 30 individuals from 9 different localities covering a geographic distance of more than 900 km and is the most likely ancestral haplotype. Adjacent haplotypes of A. ineptus from lineage A in the minimum-spanning network differed by only 1 or 2 mutational steps. In contrast, haplotypes in lineage B corresponding to A. chrysophilus from southern Africa differed by 1−4 mutational steps, with haplotypes from different localities being more closely related than haplotypes from the same locality (H20 and H21; Figs. 1 and 3).

Fig. 4

Minimum-spanning network showing the least number of mutational steps between composite haplotypes of Aethomys chrysophilus (from southern Africa and Tanzania) and A. ineptus. Squares indicate different haplotypes in A. chrysophilus and circles those in A. ineptus from southern Africa. Pentagons indicate the different haplotypes in A. chrysophilus from Tanzania (H22, H23, and H24). Sizes of circles, squares, and pentagons represent haplotype frequencies, and cross-hatching along branches designates number of changes detected. Numbers inside circles represent haplotype designations and correspond to those in Appendix I. Numbers outside circles correspond to locality numbers in Fig. 1 and Appendix I.

Fig. 4

Minimum-spanning network showing the least number of mutational steps between composite haplotypes of Aethomys chrysophilus (from southern Africa and Tanzania) and A. ineptus. Squares indicate different haplotypes in A. chrysophilus and circles those in A. ineptus from southern Africa. Pentagons indicate the different haplotypes in A. chrysophilus from Tanzania (H22, H23, and H24). Sizes of circles, squares, and pentagons represent haplotype frequencies, and cross-hatching along branches designates number of changes detected. Numbers inside circles represent haplotype designations and correspond to those in Appendix I. Numbers outside circles correspond to locality numbers in Fig. 1 and Appendix I.

Although lineage B (southern African A. chrysophilus) was only represented by 6 individuals from a relatively small geographic area, more divergence appears to exist within it than within lineage A (considered to represent A. ineptus). Haplotypes 22, 23, and 24 represent individuals of A. chrysophilus from Tanzania. Of these, H22 was separated from the closest haplotype of A. chrysophilus from southern Africa (H18) by 14 mutational steps (Figs. 1 and 3). These individuals (H22−H24) differ from each other by 1−10 mutational steps, indicating high levels of genetic variation within Tanzan A. chrysophilus.

Discussion

The mtDNA divergence between the sibling species A. chrysophilus and A. ineptus from southern Africa was relatively low (1.93–3.75%). Although the differentiation within A. chrysophilus (0.27–2.14%) and A. ineptus (0.27–1.66%) was not much lower than between them, 2 monophyletic lineages were nonetheless discernible in southern Africa. All specimens considered to represent A. ineptus and A. chrysophilus of known cytogenetic affinity in southern Africa grouped with lineages A and B, respectively.

Clearly, these 2 sibling species in southern Africa can be distinguished using the cytochrome-b gene. Although currently available evidence suggests a lack of hybridization between the 2 species in areas of sympatry (such as Langjan Nature Reserve-Linzey et al. 2003), this needs to be investigated further using nuclear genes over the potentially extensive area of overlap. More importantly, although it is very likely that the individuals sequenced were reliably identified, this study should be extended to include sequence analyses of type specimens, topotypes, or both. Although the approach taken herein may have yielded correct taxonomic results, there is also the possibility that the types may possess very different mtDNA sequences from those individuals in our lineages A and B. This possibility can only be refuted by sequencing specimens from the type localities.

At the intraspecific level, A. chrysophilus was characterized by high levels of genetic diversity over a small geographic range in southern Africa (Figs. 1 and 3). Similarly, samples of A. chrysophilus from Tanzania showed a high level of genetic differentiation. A. chrysophilus from southern Africa, on average, differed more from the Tanzan A. chrysophilus (5.56%) than from A. ineptus (2.70%). In addition, the monophyly of A. chrysophilus was not supported by our phylogenetic analyses (Fig. 3), although the geographic coverage of this species was poor. Future in-depth analysis of differentiation within A. chrysophilus, with better sampling over its entire range and independently tested using nuclear markers, will have important taxonomic implications for the species. Given that multiple characters distinguish A. ineptus from South African A. chrysophilus, it is highly likely that several additional cryptic taxa are contained within the currently described A. chrysophilus. This study further suggests that intraspecific differentiation within all Aethomys species in Africa needs to be evaluated before phylogenetic relationships within the genus can be determined.

The high intraspecific diversity within A. chrysophilus from southern Africa could be indicative of a long period of isolation between regional populations of the species. Most analyzed samples originated from near the Limpopo River drainage basin, where high levels of intraspecific differentiation have also been detected in the scrub hare (Lepus saxatilisKryger 2002). It has been proposed that the Limpopo River experienced recurrent Pleistocene and Holocene climatic episodes of wet and dry conditions (Axelrod and Raven 1978; Marker 1974, 1975). Because scrub hares tend to avoid arid habitats, they could have dispersed during droughts, with the riverbed acting as either a permanent or temporary barrier to gene flow (Kryger 2002). Although a similar scenario may apply to A. chrysophilus, our understanding of genetic variation within the species requires further investigation with samples from throughout its range, especially from the northern side of the Limpopo River.

Although the aim of this study was not at the phylogeographic level, the mtDNA differentiation within A. ineptus was characterized by shallow geographic structuring without any major genetic gaps (Figs. 1 and 3). The geographically most widely sampled haplotype (H01) occurred in 9 of the 15 localities and haplotype H02 was found in 3 localities. Other widely distributed mammalian species such as the South African springhare (Pedetes capensisMatthee and Robinson 1997), the yellow mongoose (Cynictus penicillataJansen van Vuuren and Robinson 1997), and the four-striped mouse (Rhabdomys dilectus chakaeRambau et al. 2003) also are characterized by weak geographic structuring, possibly because they are habitat generalists that occur predominantly in grassland. It has been suggested that species exhibiting shallow intraspecific genetic structure have had recent historical interconnections through gene flow (Avise et al. 1987).

Gene flow would require the absence of geographic barriers to movement and a life history that includes dispersal (Avise et al. 1987). Interestingly, Chimimba (2001) found a clinal pattern of morphometric variation within A. ineptus that made the recognition of subspecies untenable, suggesting no disruption of gene flow. Although the life history of A. ineptus remains largely unknown, other rodents have been reported to disperse up to 400 km over long periods of time (Kim et al. 1998), particularly during population eruptions. This results in rapid population growth (Pearson 1975) that may in turn influence large-scale movements (Jaarola and Tegelström 1995). A detailed phylogeographic study of both species may reveal cryptic life-history differences, just as our preliminary comparison of intraspecific diversity showed different phylogeographic patterns.

The glacial cycles of the last 1.7 million years are believed to have altered species' distributions significantly (Avise 1989). Global temperature fluctuations could have influenced southern African climate, leading to an expansion of grassland (at the expense of other vegetation types) as temperatures dropped (Brain 1985; Coetzee 1978; Van Zinderen-Bakker 1957,1978). The time of divergence between the sibling species (i.e., less than 0.5 million years ago) broadly coincides with this period and it is plausible to suggest that the range of A. ineptus expanded southward with an increase in grassland vegetation. Further research of the Limpopo River drainage system as a barrier to gene flow in codistributed small mammals would improve our understanding of inter- and intraspecific variation and the processes associated with speciation.

Acknowledgments

We are grateful to A. V. Linzey, M. Kesner (Indiana University of Pennsylvania, Indiana, Pennsylvania), P. Muteka (University of Namibia, Windhoek, Namibia), and N. Avenant (National Museum, Bloemfontein, South Africa) for samples. E. R. Swartz and W. Delport are thanked for constructive comments on earlier drafts of the manuscript. We also thank 2 anonymous reviewers for invaluable comments on the manuscript. This study was funded by National Research Foundation grant 2053653 to PB and CTC and the University of Pretoria.

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Appendix I

Collecting localities and specimens examined, including 6 Aethomys chrysophilus from locations 1–4 and 54 A. ineptus from locations 4–18. Voucher specimens, indicated by TM numbers, are housed in the Transvaal Museum, Northern Flagship Institution, Pretoria, South Africa. Localities are shown in Fig. 1. Haplotype numbers (see Fig. 2) are indicated by H numbers and the number following the H number represents haplotype frequencies.

Aethomys chrysophilus.—1. Francistown Botswana, 21°11′15″S, 27°23′22″E (H01 = 1), 2. Messina Nature Reserve, South Africa, 22°24′45″S, 30°03′01″E (H17 = 1), 3. Pafuri, Kruger National Park, South Africa, 22°25′49″S, 31°10′25″E (H18 = 1; H19 = 1), 4. Langjan Nature Reserve, South Africa, 22°51′30″S, 29°14′30″E (H01 = 1, TM46726; H02 = 1, TM46773; H20 = 1, TM46772; H21 = 2, TM46726, TM46768).

Aethomys ineptus.—4. Langjan Nature Reserve, South Africa, 22°51′30″S, 29°14′30″E (H03 = 1, TM46769), 5. Happy Rest Nature Reserve, South Africa, 23°01 '30”S, 29°44′30″E (H01 = 11, TM46722, TM46723, TM46729, TM46730, TM46734, TM46735; H02 = 1; H04 = 2, TM46720; H05 = 3, TM46728, TM46731 ; H06 = 1, TM46727; H07 = 1, TM46732), 6. Percy Fyfe Nature Reserve, South Africa, 24°02′30″S, 29°10′30″E (H01 = 1, TM46733; H08 = 1, TM46725; H09 = 1, TM46724), 7. Selati Nature Reserve, South Africa, 24°09′30″S, 30°40′50″E (H02 = 1), 8. Orpen Gate, Kruger National Park, South Africa, 24°34′30″S, 31°06′30″E (H10 = 1), 9. Vaalkop Dam Nature Reserve, South Africa, 25°19′25″S, 27°25′52″E (H01 = 2), 10. Kruisrivier Nature Reserve, Loskop Dam, South Africa, 25°21′08″S, 29°32′26″E (H01 = 1), 11. Botsalano Game Reserve, South Africa, 25°34′30″S, 25°41′30″E (H01 = 3, TM46754, TM46765), 12. Roodeplaat Dam Nature Reserve, South Africa, 25°38′30″S, 28°22′30″E (H01 = 10), 13. Wathaba-Uitkomst, Machadodorp, South Africa, 25°47′27″S, 30°22′31″E (H11 = 1), 14. Malolotja Nature Reserve Swaziland, 26°10′30″S, 31°11′32″E (H12 = 1), 15. Farm: Vlakfontein, Vryburg, South Africa, 27°04′22″S, 24°46′07″E (H13 = 1; H14 = 1), 16. Farm: Koedoesberg, Pongola, South Africa, 27°26′31″S, 31°41′41″E (H15 = 3), 17. Albert Falls Nature Reserve, South Africa, 29°28′18″S, 30°23′53″E (H01 = 1), 18. Ashburton, South Africa, 29°38′56″S, 30°27′16″E (H16 = 1).

Author notes

Associate Editor was Carey Krajewski.