Gauging ages of tiger swallowtail butterflies using alternate SNP analyses.

Divergence times underpin diverse evolutionary hypotheses, but conflicting age estimates across studies diminish the validity of such hypotheses. These conflicts have continued to grow as large genomics datasets become commonplace and analytical approaches proliferate. To provide more stable temporal intervals, age estimations should be interpreted in the context of both the type of data and analysis being used. Here, we use multispecies coalescent (MSC), concatenation-based, and categorical data transformation approaches on genome-wide SNP data to infer divergence ages within the Papilio glaucus group of tiger swallowtail butterflies in North America. While the SNP data supported previously recognized relationships within the group (P. multicaudata, ((P. eurymedon, P. rutulus), (P. appalachiensis, P. canadensis, P. glaucus))), estimated ages of divergence between the major lineages varied substantially among analyses. MSC produced wide credibility intervals particularly for deeper nodes, reflecting uncertainty in the coalescence times as a possible result of conflicting signal across gene trees. Concatenation, in contrast, gave narrower and more well-defined posterior distributions for the node ages; however, the higher precision of these time estimates is a likely artefact due to more simplistic underlying assumptions of this approach that do not account for conflict among gene trees. Transformed categorical data analysis gave the least precise and the most variable results, with its simple substitution model coupled with a relaxed clock tending to produce spurious results from large genome-wide datasets. While median node ages differed considerably between analyses (∼2 Mya between MSC and concatenation-based results), their corresponding credibility intervals nonetheless highlight common temporal patterns for deeper divergences in the group as well as finer-scale phylogeography. Age distributions across analyses support an origin of the group during the warm period of the early to mid-Pliocene. Late Pliocene climate aridification and cooling drove divergence between eastern and western groups that further diversified during the period of repeated Pleistocene glaciations. Our results provide a structured comparative assessment of divergence time estimates and evolutionary relationships in a well-studied group of butterflies, and support better understanding of analytical biases in divergence time estimation.

Genomics and ecological modelling clarify species integrity in a confusing group of butterflies.

Recent advances in both genomics and ecological modelling present new, multidisciplinary opportunities for resolving species boundaries and understanding the mechanisms that maintain their integrity in regions of contact. Here, we use a combination of high-throughput DNA sequencing and ecological niche modelling to resolve species boundaries and niche divergence within the Speyeria atlantis-hesperis (Lepidoptera: Nymphalidae) complex, a confusing group of North American butterflies. This complex is notorious for its muddled species delimitations, morphological ambiguity, and extensive mitonuclear discordance. Our admixture and multispecies coalescent-based analyses of single nucleotide polymorphisms identified substantial divergences between S. atlantis and S. hesperis in areas of contact, as well as between distinct northern and southern lineages within S. hesperis. Our results also provide evidence of past introgression relating to another species, S. zerene, which previous work has shown to be more distantly related to the S. atlantis-hesperis complex. We then used ecological models to predict habitat suitability for each of the three recovered genomic lineages in the S. atlantis-hesperis complex and assessed their pairwise niche divergence. These analyses resolved that these three lineages are significantly diverged in their respective niches and are not separated by discontinuities in suitable habitat that might present barriers to gene flow. We therefore infer that ecologically-mediated selection resulting in disparate habitat associations is a principal mechanism reinforcing their genomic integrity. Overall, our results unambiguously support significant evolutionary and ecological divergence between the northern and southern lineages of S. hesperis, sufficient to recognize the southern evolutionary lineage as a distinct species, called S. nausicaa based on taxonomic priority.

Chromosome-level genome assembly reveals genomic architecture of northern range expansion in the mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae).

Genome sequencing methods and assembly tools have improved dramatically since the 2013 publication of draft genome assemblies for the mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae). We conducted proximity ligation library sequencing and scaffolding to improve contiguity, and then used linkage mapping and recent bioinformatic tools for correction and further improvement. The new assemblies have dramatically improved contiguity and gaps compared to the originals: N50 values increased 26- to 36-fold, and the number of gaps were reduced by half. Ninety per cent of the content of the assemblies is now contained in 12 and 11 scaffolds for the female and male assemblies, respectively. Based on linkage mapping information, the 12 largest scaffolds in both assemblies represent all 11 autosomal chromosomes and the neo-X chromosome. These assemblies now have nearly chromosome-sized scaffolds and will be instrumental for studying genomic architecture, chromosome evolution, population genomics, functional genomics, and adaptation in this and other pest insects. We also identified regions in two chromosomes, including the ancestral-X portion of the neo-X chromosome, with elevated differentiation between northern and southern Canadian populations.

De Novo Whole-Genome Assembly of the Swede Midge (Contarinia nasturtii), a Specialist of Brassicaceae, Using Linked-Read Sequencing.

The swede midge, Contarinia nasturtii, is a cecidomyiid fly that feeds specifically on plants within the Brassicaceae. Plants in this family employ a glucosinolate-myrosinase defense system, which can be highly toxic to nonspecialist feeders. Feeding by C. nasturtii larvae induces gall formation, which can cause substantial yield losses thus making it a significant agricultural pest. A lack of genomic resources, in particular a reference genome, has limited deciphering the mechanisms underlying glucosinolate tolerance in C. nasturtii, which is of particular importance for managing this species. Here, we present an annotated, scaffolded reference genome of C. nasturtii using linked-read sequencing from a single individual and explore systems involved in glucosinolate detoxification. The C. nasturtii genome is similar in size and annotation completeness to that of the Hessian fly, Mayetiola destructor, but has greater contiguity. Several genes encoding enzymes involved in glucosinolate detoxification in other insect pests, including myrosinases, sulfatases, and glutathione S-transferases, were found, suggesting that C. nasturtii has developed similar strategies for feeding on Brassicaceae. The C. nasturtii genome will, therefore, be integral to continued research on plant-insect interactions in this system and contribute to effective pest management strategies.

Disjunction between canola distribution and the genetic structure of its recently described pest, the canola flower midge (Contarinia brassicola).

Population genomics is a useful tool to support integrated pest management as it can elucidate population dynamics, demography, and histories of invasion. Here, we use a restriction site-associated DNA sequencing approach combined with whole-genome amplification (WGA) to assess genomic population structure of a newly described pest of canola, the diminutive canola flower midge, Contarinia brassicola. Clustering analyses recovered little geographic structure across the main canola production region but differentiated several geographically disparate populations at edges of the agricultural zone. Given a lack of alternative hypotheses for this pattern, we suggest these data support alternative hosts for this species and thus our canola-centric view of this midge as a pest has limited our understanding of its biology. These results speak to the need for increased surveying efforts across multiple habitats and other potential hosts within Brassicaceae to improve both our ecological and evolutionary knowledge of this species and contribute to effective management strategies. We additionally found that use of WGA prior to library preparation was an effective method for increasing DNA quantity of these small insects prior to restriction site-associated DNA sequencing and had no discernible impact on genotyping consistency for population genetic analysis; WGA is therefore likely to be tractable for other similar studies that seek to randomly sample markers across the genome in small organisms.

Evaluating the Performance of Probabilistic Algorithms for Phylogenetic Analysis of Big Morphological Datasets: A Simulation Study.

Reconstructing the tree of life is an essential task in evolutionary biology. It demands accurate phylogenetic inference for both extant and extinct organisms, the latter being almost entirely dependent on morphological data. While parsimony methods have traditionally dominated the field of morphological phylogenetics, a rapidly growing number of studies are now employing probabilistic methods (maximum likelihood and Bayesian inference). The present-day toolkit of probabilistic methods offers varied software with distinct algorithms and assumptions for reaching global optimality. However, benchmark performance assessments of different software packages for the analyses of morphological data, particularly in the era of big data, are still lacking. Here, we test the performance of four major probabilistic software under variable taxonomic sampling and missing data conditions: the Bayesian inference-based programs MrBayes and RevBayes, and the maximum likelihood-based IQ-TREE and RAxML. We evaluated software performance by calculating the distance between inferred and true trees using a variety of metrics, including Robinson-Foulds (RF), Matching Splits (MS), and Kuhner-Felsenstein (KF) distances. Our results show that increased taxonomic sampling improves accuracy, precision, and resolution of reconstructed topologies across all tested probabilistic software applications and all levels of missing data. Under the RF metric, Bayesian inference applications were the most consistent, accurate, and robust to variation in taxonomic sampling in all tested conditions, especially at high levels of missing data, with little difference in performance between the two tested programs. The MS metric favored more resolved topologies that were generally produced by IQ-TREE. Adding more taxa dramatically reduced performance disparities between programs. Importantly, our results suggest that the RF metric penalizes incorrectly resolved nodes (false positives) more severely than the MS metric, which instead tends to penalize polytomies. If false positives are to be avoided in systematics, Bayesian inference should be preferred over maximum likelihood for the analysis of morphological data.

Cross-platform compatibility of de novo-aligned SNPs in a nonmodel butterfly genus.

High-throughput sequencing methods for genotyping genome-wide markers are being rapidly adopted for phylogenetics of nonmodel organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in nonmodel systems. Using double-digest restriction site-associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria and support the use and long-term viability of SNP genotyping applications in nonmodel systems.

Mite choice generates sex- and size-biased infection in Drosophila hydei.

Heterogeneities in parasite infection among conspecific hosts often manifest as sex- or size-biased infections, which are typically attributed to differential host susceptibility and exposure. Since parasite fitness is often tied to host quality, host preference by parasites is likely to be under strong selection. We test the hypothesis that host preference is sufficient to generate variability in infection rate among conspecifics. Specifically, we ask whether the mite Macrocheles muscaedomesticae is able to discriminate between Drosophila hydei hosts of different sex and size, while explicitly accounting for the potential confounding effects of these two factors. Our results indicate a preference for female hosts, but this preference appears to be driven by size and not sex per se. When differences in body size were controlled for, the sex-biased infection disappeared, while mites presented with the choice of two female flies of disparate sizes were more likely to select the larger host. Across the distribution of fly body weight in this study, mites preferentially attached to flies of intermediate size. This study provides evidence that mite choice for certain host types can play an important role in parasite transmission, even in the absence of differential susceptibility or exposure among hosts.