Wolbachia association with the tsetse fly, Glossina fuscipes fuscipes, reveals high levels of genetic diversity and complex evolutionary dynamics

BACKGROUND: Wolbachia pipientis, a diverse group of α-proteobacteria, can alter arthropod host reproduction and confer a reproductive advantage to Wolbachia-infected females (cytoplasmic incompatibility (CI)). This advantage can alter host population genetics because Wolbachia-infected females produce more offspring with their own mitochondrial DNA (mtDNA) haplotypes than uninfected females. Thus, these host haplotypes become common or fixed (selective sweep). Although simulations suggest that for a CI-mediated sweep to occur, there must be a transient phase with repeated initial infections of multiple individual hosts by different Wolbachia strains, this has not been observed empirically. Wolbachia has been found in the tsetse fly, Glossina fuscipes fuscipes, but it is not limited to a single host haplotype, suggesting that CI did not impact its population structure. However, host population genetic differentiation could have been generated if multiple Wolbachia strains interacted in some populations. Here, we investigated Wolbachia genetic variation in G. f. fuscipes populations of known host genetic composition in Uganda. We tested for the presence of multiple Wolbachia strains using Multi-Locus Sequence Typing (MLST) and for an association between geographic region and host mtDNA haplotype using Wolbachia DNA sequence from a variable locus, groEL (heat shock protein 60). RESULTS: MLST demonstrated that some G. f. fuscipes carry Wolbachia strains from two lineages. GroEL revealed high levels of sequence diversity within and between individuals (Haplotype diversity = 0.945). We found Wolbachia associated with 26 host mtDNA haplotypes, an unprecedented result. We observed a geographical association of one Wolbachia lineage with southern host mtDNA haplotypes, but it was non-significant (p = 0.16). Though most Wolbachia-infected host haplotypes were those found in the contact region between host mtDNA groups, this association was non-significant (p = 0.17). CONCLUSIONS: High Wolbachia sequence diversity and the association of Wolbachia with multiple host haplotypes suggest that different Wolbachia strains infected G. f. fuscipes multiple times independently. We suggest that these observations reflect a transient phase in Wolbachia evolution that is influenced by the long gestation and low reproductive output of tsetse. Although G. f. fuscipes is superinfected with Wolbachia, our data does not support that bidirectional CI has influenced host genetic diversity in Uganda

Trypanosoma brucei gambiense group 1 is distinguished by a unique amino acid substitution in the HpHb receptor implicated in human serum resistance

Trypanosoma brucei rhodesiense (Tbr) and T. b. gambiense (Tbg), causative agents of Human African Trypanosomiasis (sleeping sickness) in Africa, have evolved alternative mechanisms of resisting the activity of trypanosome lytic factors (TLFs), components of innate immunity in human serum that protect against infection by other African trypanosomes. In Tbr, lytic activity is suppressed by the Tbr-specific serum-resistance associated (SRA) protein. The mechanism in Tbg is less well understood but has been hypothesized to involve altered activity and expression of haptoglobin haemoglobin receptor (HpHbR). HpHbR has been shown to facilitate internalization of TLF-1 in T.b. brucei (Tbb), a member of the T. brucei species complex that is susceptible to human serum. By evaluating the genetic variability of HpHbR in a comprehensive geographical and taxonomic context, we show that a single substitution that replaces leucine with serine at position 210 is conserved in the most widespread form of Tbg (Tbg group 1) and not found in related taxa, which are either human serum susceptible (Tbb) or known to resist lysis via an alternative mechanism (Tbr and Tbg group 2). We hypothesize that this single substitution contributes to reduced uptake of TLF and thus may play a key role in conferring serum resistance to Tbg group 1. In contrast, similarity in HpHbR sequence among isolates of Tbg group 2 and Tbb/Tbr provides further evidence that human serum resistance in Tbg group 2 is likely independent of HpHbR functio

Evolutionary and ecological influences on color pattern variation in the Australian common froglet, Crinia signifera

textElucidation of mechanisms that generate and maintain population-level phenotypic variability provides insight into processes that influence within-species genetic divergence. Historically, color pattern polymorphisms were used to infer population-level genetic variability, but recent approaches directly capture genetic variability using molecular markers. Here, I clarify the relationship between genetic variability and color pattern polymorphism within and among populations using the Australian common froglet, Crinia signifera. To illustrate genetic variability in C. signifera, I used phylogenetic analysis of mitochondrial DNA and uncovered three ancient geographically restricted lineages whose distributions are consistent with other southeastern Australian species. Additional phylogeographic structure was identified within the three ancient lineages and was consistent with geographic variation in male advertisement calls. Natural selection imposed by predators has been hypothesized to act on black-and-white ventral polymorphisms in C. signifera, specifically through mimicry of another Australian frog, Pseudophryne. I used clay replicas of C. signifera to test whether predators avoid black-and-white coloration. In fact, black-and-white replicas were preferentially avoided by predators in some habitats, but not in others, indicating that differential selection among habitats plays a role in maintaining color pattern polymorphism. When black-and-white color patterns in a sample of C. signifera populations were compared with those in sympatric Pseudophryne, several color pattern characteristics were correlated between the species. Furthermore, where C. signifera and Pseudophryne are sympatric, color patterns are more similar compared to those in allopatry. Extensive phylogenetic variability suggests that phylogenetic history and genetic drift may also influence C. signifera color pattern. Fine-scale phylogenetic analysis uncovered additional genetic diversity within lineages and low levels of introgression among previously identified clades. Measures of color pattern displayed low levels of phylogenetic signal, indicating that relationships among individuals only slightly influence color patterns. Finally, simulations of trait evolution under Brownian motion illustrated that the phylogeny alone cannot generate the pattern of variation observed in C. signifera color pattern. Therefore, this indicates a minimal role for genetic drift, but instead supports either the role of stabilizing selection due to mimicry, or diversifying selection due to habitat differences, in color pattern variation in C. signifera.Biological Sciences, School o

Data from: Extending phylogeography to account for lineage fusion

Secondary contact between long isolated populations has several possible outcomes. These include the strengthening of preexisting reproductive isolating mechanisms via reinforcement, the emergence of a hybrid lineage that is distinct from its extant parental lineages and which occupies a spatially restricted zone between them, or complete merging of two populations such that parental lineages are no longer extant ("lineage fusion" herein). The latter scenario has rarely been explicitly considered in single-species and comparative phylogeographic studies, yet it has the potential to impact inferences about population history and levels of congruence. In this paper, we explore the idea that insights into past lineage fusion may now be possible, owing to the advent of next-generation sequencing. Using simulated DNA sequence haplotype datasets (i.e., loci with alleles comprised of a set of linked nucleotide polymorphisms), we examined basic requirements (number of loci and individuals sampled) for identifying cases when a present-day panmictic population is the product of lineage fusion, using an exemplar statistical framework—approximate Bayesian computation. We found that with approximately 100 phased haplotype loci (400 bp) and modest sample sizes of individuals (10 per population), lineage fusion can be detected under rather challenging scenarios. This included some scenarios where reticulation was fully contained within a Last Glacial Maximum timeframe, provided that mixing was symmetrical, ancestral gene pools were moderately to deeply diverged, and the lag time between the fusion event and gene pool sampling was relatively short. However, the more realistic case of asymmetrical mixing is not prohibitive if additional genetic data (e.g., 400 loci) are available. Notwithstanding some simplifying assumptions of our simulations and the knowledge gaps that remain about the circumstances under which lineage fusion is potentially detectable, we suggest that the recent release from data limitation allows phylogeographers to expand the scope of inferences about long-term population history

<it>Wolbachia</it> association with the tsetse fly, <it>Glossina fuscipes fuscipes</it>, reveals high levels of genetic diversity and complex evolutionary dynamics

<p>Abstract</p> <p>Background</p> <p><it>Wolbachia pipientis</it>, a diverse group of α-proteobacteria, can alter arthropod host reproduction and confer a reproductive advantage to <it>Wolbachia</it>-infected females (cytoplasmic incompatibility (CI)). This advantage can alter host population genetics because <it>Wolbachia</it>-infected females produce more offspring with their own mitochondrial DNA (mtDNA) haplotypes than uninfected females. Thus, these host haplotypes become common or fixed (selective sweep). Although simulations suggest that for a CI-mediated sweep to occur, there must be a transient phase with repeated initial infections of multiple individual hosts by different <it>Wolbachia</it> strains, this has not been observed empirically. <it>Wolbachia</it> has been found in the tsetse fly, <it>Glossina fuscipes fuscipes,</it> but it is not limited to a single host haplotype, suggesting that CI did not impact its population structure. However, host population genetic differentiation could have been generated if multiple <it>Wolbachia</it> strains interacted in some populations. Here, we investigated <it>Wolbachia</it> genetic variation in <it>G. f. fuscipes</it> populations of known host genetic composition in Uganda. We tested for the presence of multiple <it>Wolbachia</it> strains using Multi-Locus Sequence Typing (MLST) and for an association between geographic region and host mtDNA haplotype using <it>Wolbachia</it> DNA sequence from a variable locus, <it>gro</it>EL (heat shock protein 60).</p> <p>Results</p> <p>MLST demonstrated that some <it>G. f. fuscipes</it> carry <it>Wolbachia</it> strains from two lineages. G<it>ro</it>EL revealed high levels of sequence diversity within and between individuals (Haplotype diversity = 0.945). We found <it>Wolbachia</it> associated with 26 host mtDNA haplotypes, an unprecedented result<it>.</it> We observed a geographical association of one <it>Wolbachia</it> lineage with southern host mtDNA haplotypes, but it was non-significant (p = 0.16). Though most <it>Wolbachia</it>-infected host haplotypes were those found in the contact region between host mtDNA groups, this association was non-significant (p = 0.17).</p> <p>Conclusions</p> <p>High <it>Wolbachia</it> sequence diversity and the association of <it>Wolbachia</it> with multiple host haplotypes suggest that different <it>Wolbachia</it> strains infected <it>G. f. fuscipes</it> multiple times independently. We suggest that these observations reflect a transient phase in <it>Wolbachia</it> evolution that is influenced by the long gestation and low reproductive output of tsetse. Although <it>G. f. fuscipes</it> is superinfected with <it>Wolbachia</it>, our data does not support that bidirectional CI has influenced host genetic diversity in Uganda.</p

Data from: The evolution of phylogeographic datasets

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. Single-species 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

Garrick_etal_MEC2015_Survey_Data

The survey database is comprised of data reported in empirical phylogeography papers that satisfied search / inclusion criteria described in the main text of Garrick et al. (2015, Mol. Ecol.). Detailed descriptions of column headers are given in the "read me" Metadata file