We compared Mt-DNA d-loop haplotypes to look at the genetic diversity, population structure, neutrality and demographic history of cane rat population that exist in two African countries with differing climatic conditions and habitats. We found high nucleotide diversity in AGC Population from Tanzania, and large genetic variation between than within cane rat population from any of the countries studied. We also found positive Harpending raggedness index for population from Tanzania and negative for Ghana with non-significant p-values in both. Population from Tanzania had a negative Tajima’s D while it was positive for population from Ghana. Further, Fu’s test was positive for both Tanzania and Ghana populations whereas the mismatch distribution analysis revealed a bimodal and raged shape for both populations. Additionally, neighbour joining network revealed three main clades in Tanzania and two main clades in Ghana.
Low nucleotide diversity in Ghana AGC population indicates small differences between haplotypes which suggests that the genetic diversity of AGC in Ghana has declined. This may be attributed to a long domestication history in Ghana which is associated with artificial inbreeding probably as the result of small base population that is highly susceptible to inbreeding and genetic drift (Guerier et al., 2012). Domestication has been reported by Liu and colleagues (2019) to reduce diversity in both flora and fauna. Further, inbreeding reduces fitness,increasing susceptibility to diseases and accelerating loss of genetic diversity (Smallbone et al. 2016). Furthermore, defaunation caused by overhunting for bushmeat trade in most west African countries including Ghana (Benítez-López et al. 2019) is known to have reduced species diversity and consequently the genetic diversity of mammals in West Africa (Korner et al. 2017). Populations with little divergence could potentially be genetically less diverse and coupled with an inbreeding depression could affect many different fitness-related traits, including survival and reproductive success (Smallbone et al., 2016).
There was a significant and strong genetic structure between the AGC populations with every sampling locality presenting as a unique genetic entity (i.e., no haplotypes were shared between Ghana and Tanzania. The strong genetic differentiation points to a very minimal historical gene flow and no intermixing between the population from Ghana and Tanzania. Similar results were observed in Cape mole rats in South Africa (Visser et al.,2018). Further, the genetic distance between the two groups was high which also agrees with the genetic differentiation index results. Wright (1951) reported that the degree of differentiation would be high if the Fst was > 0.25. The AGC populations in this study met this criterion suggesting that the long history of spatial isolation between them has affected their genetic makeup. An alternative explanation for the observed genetic differences is that the AGC populations from Tanzania and Ghana have no female-mediated gene-flow (Tserenbataa et al., 2004). This is because there are no haplotype shared between these two populations (Tanzania and Ghana).
We found a negative Tajima’s D (not significant) for AGC population from Tanzania and a positive value for population from Ghana. A negative Tajima's D value for Tanzania signifies an excess of low frequency polymorphisms, which was not expected and indicates population size expansion (e.g., after a bottleneck or a selective sweep). A positive Tajima's D value for the Ghana AGC populations indicated a low level of low and high frequency polymorphisms, which implied a reduction in population size and/or balancing selection. On the other hand, Fu’s FS test results which are based on the distribution of haplotypes was negative and significant for both Tanzania and Ghana populations indicating excess number of alleles, as would be expected from a recent population expansion or from genetic hitch-hiking (Schierup et al., 2000). An alternative explanation is that a negative Fu’s Fs value indicated excess rare mutations within populations which could be caused by evolutionary forces due to either selective sweep or population growth (BaenyiSimon et al.,2022).
In our study, the mismatch distribution plot for both East and West Africa populations showed a multimodal and ragged shape, revealing demographic equilibrium or a stable population (Ray et al., 2003). A population usually exhibits a uni-modal mismatch distribution when it has passed through a recent demographic expansion (Elenga et al., 2000), whereas a multimodal mismatch distribution indicates that a population is comparatively stable (Lavery et al., 1996). In general, a multimodal (including bimodal) mismatch distribution indicated diminishing population sizes or structured size; and a ragged distribution suggested that the lineage was widespread (Excoffier et al., 1992; Rogers and Harpending, 1992; Rogers et al., 1995). Indeed, population sub-structuring and mutation rate heterogeneity may also account for multimodal mismatch distributions (Marjoram & Donnelly, 1994; Aris-Brosou & Excoffier, 1996) observed in this study. We therefore, interpret the bimodality of the mismatch distributions to be a result of the presence of different haplogroups as seen in the haplotype network, rather than demographic stability.
The shape of the minimum spanning network indicated a high geographical structure and very high level of sequence divergence. These results clearly mirror those from the diversity indices and AMOVA and show a high variation between AGC populations from Tanzania and Ghana. Further, our results
revealed that the populations from Ghana have little divergence and share the most common haplotypes between the three agro-ecological zones. Less divergent haplotypes within animals and geographical locations suggest that the gene flow has occurred on a regional scale during some time in the recent past and the animals have not been subdivided by long-term biogeographic barriers (Baenyi Simon et al., 2022). The AGC populations from Tanzania on the other hand showed more structured with some haplotypes unique to a single population (Udzungwa South) while other haplotypes were shared between Udzungwa North, Uluguru urban and Uluguru rural) indicating low genetic exchange.
To conclude, our analyses of the mtDNA control region (d-loop) revealed a strong genetic differentiation between these two populations, and a unique maternal origin of each population (Tanzania and Ghana) and that the two populations do not share similar genetic background. Future studies should look into the origin of these populations and explore in potential speciation across the regions.