BackgroundAphids are one of the most important insect taxa in terms of ecology, evolutionary biology, genetics and genomics, and interactions with endosymbionts. Additionally, many aphids are serious pest species of agricultural and horticultural plants. Recent genetic and genomic research has expanded molecular resources for many aphid species, including the whole genome sequencing of the pea aphid, Acrythosiphon pisum. However, the invasive soybean aphid, Aphis glycines, lacks in any significant molecular resources.Methodology/Principal FindingsTwo next-generation sequencing technologies (Roche-454 and Illumina GA-II) were used in a combined approach to develop both transcriptomic and genomic resources, including expressed genes and molecular markers. Over 278 million bp were sequenced among the two methods, resulting in 19,293 transcripts and 56,688 genomic sequences. From this data set, 635 SNPs and 1,382 microsatellite markers were identified. For each sequencing method, different soybean aphid biotypes were used which revealed potential biotype specific markers. In addition, we uncovered 39,822 bp of sequence that were related to the obligatory endosymbiont, Buchnera aphidicola, as well as sequences that suggest the presence of Hamiltonella defensa, a facultative endosymbiont.Conclusions and SignificanceMolecular resources for an invasive, non-model aphid species were generated. Additionally, the power of next-generation sequencing to uncover endosymbionts was demonstrated. The resources presented here will complement ongoing molecular studies within the Aphididae, including the pea aphid whole genome, lead to better understanding of aphid adaptation and evolution, and help provide novel targets for soybean aphid control.

Heteroecious holocyclic aphids exhibit both sexual and asexual reproduction and alternate among primary and secondary hosts. Most of these aphids can feed on several related hosts, and invasions to new habitats may limit the number of suitable hosts. For example, the aphid specialist Aphis glycines survives only on the primary host buckthorn (Rhamnus spp.) and the secondary host soybean (Glycine max) in North America where it is invasive. Owing to this specialization and sparse primary host distribution, host colonization events could be localized and involve founder effects, impacting genetic diversity, population structure and adaptation. We characterized changes in the genetic diversity and structure across time among A. glycines populations. Populations were sampled from secondary hosts twice in the same geographical location: once after secondary colonization (early season), and again immediately before primary host colonization (late season). We tested for evidence of founder effects and genetic isolation in early season populations, and whether or not late-season dispersal restored genetic diversity and reduced fragmentation. A total of 24 single-nucleotide polymorphisms and 6 microsatellites were used for population genetic statistics. We found significantly lower levels of genotypic diversity and more genetic isolation among early season collections, indicating secondary host colonization occurred locally and involved founder effects. Pairwise F ST decreased from 0.046 to 0.017 in early and late collections, respectively, and while genetic relatedness significantly decreased with geographical distance in early season collections, no spatial structure was observed in late-season collections. Thus, late-season dispersal counteracts the secondary host colonization through homogenization and increases genetic diversity before primary host colonization.

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Chagas disease, considered a neglected disease by the World Health Organization, is caused by the protozoan parasite Trypanosoma cruzi, and transmitted by >140 triatomine species across the Americas. In Central America, the main vector is Triatoma dimidiata, an opportunistic blood meal feeder inhabiting both domestic and sylvatic ecotopes. Given the diversity of interacting biological agents involved in the epidemiology of Chagas disease, having simultaneous information on the dynamics of the parasite, vector, the gut microbiome of the vector, and the blood meal source would facilitate identifying key biotic factors associated with the risk of T. cruzi transmission. In this study, we developed a RADseq-based analysis pipeline to study mixed-species DNA extracted from T. dimidiata abdomens. To evaluate the efficacy of the method across spatial scales, we used a nested spatial sampling design that spanned from individual villages within Guatemala to major biogeographic regions of Central America. Information from each biotic source was distinguished with bioinformatics tools and used to evaluate the prevalence of T. cruzi infection and predominant Discrete Typing Units (DTUs) in the region, the population genetic structure of T. dimidiata, gut microbial diversity, and the blood meal history. An average of 3.25 million reads per specimen were obtained, with approximately 1% assigned to the parasite, 20% to the vector, 11% to bacteria, and 4% to putative blood meals. Using a total of 6,405 T. cruzi SNPs, we detected nine infected vectors harboring two distinct DTUs: TcI and a second unidentified strain, possibly TcIV. Vector specimens were sufficiently variable for population genomic analyses, with a total of 25,710 T. dimidiata SNPs across all samples that were sufficient to detect geographic genetic structure at both local and regional scales. We observed a diverse microbiotic community, with significantly higher bacterial species richness in infected T. dimidiata abdomens than those that were not infected. Unifrac analysis suggests a common assemblage of bacteria associated with infection, which co-occurs with the typical gut microbial community derived from the local environment. We identified vertebrate blood meals from five T. dimidiata abdomens, including chicken, dog, duck and human; however, additional detection methods would be necessary to confidently identify blood meal sources from most specimens. Overall, our study shows this method is effective for simultaneously generating genetic data on vectors and their associated parasites, along with ecological information on feeding patterns and microbial interactions that may be followed up with complementary approaches such as PCR-based parasite detection, 18S eukaryotic and 16S bacterial barcoding.

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