Background: Seahorses, seadragons, pygmy pipehorses, and pipefishes (Syngnathidae, Syngnathiformes) are among the most recognizable groups of fishes because of their derived morphology, unusual life history, and worldwide distribution. Despite previous phylogenetic studies and recent new species descriptions of syngnathids, the evolutionary relationships among several major groups within this family remain unresolved. Results: Here, we provide a reconstruction of syngnathid phylogeny based on genome-wide sampling of 1314 ultraconserved elements (UCEs) and expanded taxon sampling to assess the current taxonomy and as a basis for macroevolutionary insights. We sequenced a total of 244 new specimens across 117 species and combined with published UCE data for a total of 183 species of Syngnathidae, about 62% of the described species diversity, to compile the most data-rich phylogeny to date. We estimated divergence times using 14 syngnathiform fossils, including nine fossils with newly proposed phylogenetic affinities, to better characterize current and historical biogeographical patterns, and to reconstruct diversification through time. We present a phylogenetic hypothesis that is well-supported and provides several notable insights into syngnathid evolution. We found nine non-monophyletic genera, evidence for seven cryptic species, five potentially invalid synonyms, and identified a novel sister group to the seahorses, the Indo-Pacific pipefishes Halicampus macrorhynchus and H. punctatus. In addition, the morphologically distinct southwest Pacific seahorse Hippocampus jugumus was recovered as the sister to all other non-pygmy seahorses. As found in many other groups, a high proportion of syngnathid lineages appear to have originated in the Central Indo-Pacific and subsequently dispersed to adjoining regions. Conversely, we also found an unusually high subsequent return of lineages from southern Australasia to the Central Indo-Pacific. Diversification rates rose abruptly during the Middle Miocene Climate Transition and peaked after the closure of the Tethys Sea. Conclusions: Our results reveal a previously underappreciated diversity of syngnathid lineages. The observed biogeographic patterns suggest a significant role of the southern Australasian region as a source and sink of lineages. Shifts in diversification rates imply possible links to declining global temperatures, the separation of the Atlantic and Pacific faunas, and the environmental changes associated with these events.

The effective population size (N_e) is a fundamental parameter in population genetics that determines the relative strength of selection and random genetic drift, the effect of migration, levels of inbreeding, and linkage disequilibrium. In many cases where it has been estimated in animals, N_e is on the order of 10%–20% of the census size. In this study, we use 12 microsatellite markers and 14,888 single nucleotide polymorphisms (SNPs) to empirically estimate N_e in Aedes aegypti, the major vector of yellow fever, dengue, chikungunya, and Zika viruses. We used the method of temporal sampling to estimate N_e on a global dataset made up of 46 samples of Ae. aegypti that included multiple time points from 17 widely distributed geographic localities. Our N_e estimates for Ae. aegypti fell within a broad range (~25–3,000) and averaged between 400 and 600 across all localities and time points sampled. Adult census size (N_c) estimates for this species range between one and five thousand, so the N_e/N_c ratio is about the same as for most animals. These N_e values are lower than estimates available for other insects and have important implications for the design of genetic control strategies to reduce the impact of this species of mosquito on human health.

Tsetse flies (Glossina spp.) are vectors of parasitic trypanosomes, which cause human (HAT) and animal African trypanosomiasis (AAT) in sub-Saharan Africa. In Uganda, Glossina fuscipes fuscipes (Gff) is the main vector of HAT, where it transmits Gambiense disease in the northwest and Rhodesiense disease in central, southeast and western regions. Endosymbionts can influence transmission efficiency of parasites through their insect vectors via conferring a protective effect against the parasite. It is known that the bacterium Spiroplasma is capable of protecting its Drosophila host from infection with a parasitic nematode. This endosymbiont can also impact its host’s population structure via altering host reproductive traits. Here, we used field collections across 26 different Gff sampling sites in northern and western Uganda to investigate the association of Spiroplasma with geographic origin, seasonal conditions, Gff genetic background and sex, and trypanosome infection status. We also investigated the influence of Spiroplasma on Gff vector competence to trypanosome infections under laboratory conditions. Generalized linear models (GLM) showed that Spiroplasma probability was correlated with the geographic origin of Gff host and with the season of collection, with higher prevalence found in flies within the Albert Nile (0.42 vs 0.16) and Achwa River (0.36 vs 0.08) watersheds and with higher prevalence detected in flies collected in the intermediate than wet season. In contrast, there was no significant correlation of Spiroplasma prevalence with Gff host genetic background or sex once geographic origin was accounted for in generalized linear models. Additionally, we found a potential negative correlation of Spiroplasma with trypanosome infection, with only 2% of Spiroplasma infected flies harboring trypanosome co-infections. We also found that in a laboratory line of Gff, parasitic trypanosomes are less likely to colonize the midgut in individuals that harbor Spiroplasma infection. These results indicate that Spiroplasma infections in tsetse may be maintained by not only maternal but also via horizontal transmission routes, and Spiroplasma infections may also have important effects on trypanosome transmission efficiency of the host tsetse. Potential functional effects of Spiroplasma infection in Gff could have impacts on vector control approaches to reduce trypanosome infections. We investigated the association of symbiotic Spiroplasma with the tsetse fly host Glossina fuscipes fuscipes (Gff) to assess if Spiroplasma infections are correlated with Gff genetic background, geography, or season and its interaction with trypanosome parasites. We analyzed distribution and prevalence of Spiroplasma infections across different Gff sampling sites in northern and western Uganda, and found that the symbiont is unevenly distributed and infections have not reached fixation within these sampling sites. We tested for associations with geographic origin of the collections, seasonal environmental conditions at the time of collection, Gff host genetic background and sex, plus trypanosome co-infections. Spiroplasma prevalence was strongly correlated with geographic origin and seasonal environmental conditions. Our parasite infection data suggested a negative correlation of Spiroplasma with trypanosome infection, with only 5 out of 243 flies harboring trypanosome co-infections. We further investigated the influence of Spiroplasma on trypanosome parasite infections in the laboratory. We found that trypanosomes were less likely to establish an infection in Gff individuals that carried Spiroplasma infections. Our results provide new information on host-endosymbiont dynamics in an important human disease vector, and provide evidence that Spiroplasma may confer partial resistance to Gff trypanosome infections. These findings provide preliminary evidence that a symbiont-based control method could be successful in combating tsetse trypanosome transmission to humans and livestock in sub-Saharan Africa.

Significance: Aedes mosquitoes are projected to continue expanding their ranges, which could expose millions more humans to the diseases they carry. The implementation of vector control methods ranging from traditional (e.g., insecticides) to cutting edge (e.g., genetic modification) could be improved with landscape connectivity maps and increased understanding of the factors that affect mosquito dispersal. Here we present an iterative random forest method for integrating genetic and environmental data to map landscape connectivity. We achieve a correlation of 0.83 between the model’s predicted genetic distance and actual genetic distance. We produce a genetic connectivity map for the southern tier of the United States and discuss important factors to consider in mosquito control, e.g., the release of genetically modified mosquitoes.