Background Glossina fuscipes fuscipes, a riverine species of tsetse, is the main vector of both human and animal trypanosomiasis in Uganda. Successful implementation of vector control will require establishing an appropriate geographical scale for these activities. Population genetics can help to resolve this issue by characterizing the extent of linkage among apparently isolated groups of tsetse.Methodology/Principal FindingsWe conducted genetic analyses on mitochondrial and microsatellite data accumulated from approximately 1000 individual tsetse captured in Uganda and neighboring regions of Kenya and Sudan. Phylogeographic analyses suggested that the largest scale genetic structure in G. f. fuscipes arose from an historical event that divided two divergent mitochondrial lineages. These lineages are currently partitioned to northern and southern Uganda and co-occur only in a narrow zone of contact extending across central Uganda. Bayesian assignment tests, which provided evidence for admixture between northern and southern flies at the zone of contact and evidence for northerly gene flow across the zone of contact, indicated that this structure may be impermanent. On the other hand, microsatellite structure within the southern lineage indicated that gene flow is currently limited between populations in western and southeastern Uganda. Within regions, the average FST between populations separated by less than 100 km was less than ∼0.1. Significant tests of isolation by distance suggested that gene flow is ongoing between neighboring populations and that island populations are not uniformly more isolated than mainland populations.Conclusions/SignificanceDespite the presence of population structure arising from historical colonization events, our results have revealed strong signals of current gene flow within regions that should be accounted for when planning tsetse control in Uganda. Populations in southeastern Uganda appeared to receive little gene flow from populations in western or northern Uganda, supporting the feasibility of area wide control in the Lake Victoria region by the Pan African Tsetse and Trypanosomiasis Eradication Campaign.

Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20 years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5 years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Singlespecies studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach~20 000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field.Keywords: DNA sequences, information content, phylogeography, sampling, single nucleotide polymorphisms, temporal trends IntroductionPhylogeographers have been working to collect multilocus data ever since a series of theoretical papers pertinent to the discipline demonstrated that estimates of key demographic parameters improve as the number of loci increases (e.g. Edwards & Beerli 2000;Hey & Nielsen 2004;Felsenstein 2006;Carling & Brumfield 2007). Recent improvements in DNA sequencing technology have led to platforms with greater speed, resolution and/or output (e.g. Margulies et al. 2005;Bentley et al. 2008;Rothberg et al. 2011) when compared to the traditional Sanger method. These technological advances, together with the development of general-purpose protocols for discovering and screening many DNA sequence polymorphisms arrayed across a species' genome (e.g. Baird et al. 2008;Kerstens et al. 2009;Faircloth et al. 2012;Peterson et al. 2012), are transforming the field of phylogeography to one that is no longer data limited. Investigations concerned with reconstructing long-term population history generally require large numbers of sampled alleles (i.e. many individuals and populations), across multiple loci, to adequately characterize levels of diversity and spatial genetic structuring (McCor...

Although many classic radiations on islands are thought to be the result of repeated lineage splitting, the role of past fusion is rarely known because during these events, purebreds are rapidly replaced by a swarm of admixed individuals. Here, we capture lineage fusion in action in a Galápagos giant tortoise species, Chelonoidis becki, from Wolf Volcano (Isabela Island). The long generation time of Galápagos tortoises and dense sampling (841 individuals) of genetic and demographic data were integral in detecting and characterizing this phenomenon. In C. becki, we identified two genetically distinct, morphologically cryptic lineages. Historical reconstructions show that they colonized Wolf Volcano from Santiago Island in two temporally separated events, the first estimated to have occurred ~199 000 years ago. Following arrival of the second wave of colonists, both lineages coexisted for approximately ~53 000 years. Within that time, they began fusing back together, as microsatellite data reveal widespread introgressive hybridization. Interestingly, greater mate selectivity seems to be exhibited by purebred females of one of the lineages. Forward-in-time simulations predict rapid extinction of the early arriving lineage. This study provides a rare example of reticulate evolution in action and underscores the power of population genetics for understanding the past, present and future consequences of evolutionary phenomena associated with lineage fusion.

ABSTRACTTsetse flies (Diptera: Glossinidae) are vectors for African trypanosomes (Euglenozoa: kinetoplastida), protozoan parasites that cause African trypanosomiasis in humans (HAT) and nagana in livestock. In addition to trypanosomes, two symbiotic bacteria (Wigglesworthia glossinidiaandSodalis glossinidius) and two parasitic microbes,Wolbachiaand a salivary gland hypertrophy virus (SGHV), have been described in tsetse. Here we determined the prevalence of and coinfection dynamics betweenWolbachia, trypanosomes, and SGHV inGlossina fuscipes fuscipesin Uganda over a large geographical scale spanning the range of host genetic and spatial diversity. Using a multivariate analysis approach, we uncovered complex coinfection dynamics between the pathogens and statistically significant associations between host genetic groups and pathogen prevalence. It is important to note that these coinfection dynamics and associations with the host were not apparent by univariate analysis. These associations between host genotype and pathogen are particularly evident forWolbachiaand SGHV where host groups are inversely correlated forWolbachiaand SGHV prevalence. On the other hand, trypanosome infection prevalence is more complex and covaries with the presence of the other two pathogens, highlighting the importance of examining multiple pathogens simultaneously before making generalizations about infection and spatial patterns. It is imperative to note that these novel findings would have been missed if we had employed the standard univariate analysis used in previous studies. Our results are discussed in the context of disease epidemiology and vector control.