Evolution of chemosensory genes in Colorado potato beetle, Leptinotarsa decemlineata.

Associating with plant hosts is thought to have elevated the diversification of insect herbivores, which comprise the majority of global species diversity. In particular, there is considerable interest in understanding the genetic changes that allow host-plant shifts to occur in pest insects and in determining what aspects of functional genomic diversity impact host-plant breadth. Insect chemoreceptors play a central role in mediating insect-plant interactions, as they directly influence plant detection and sensory stimuli during feeding. Although chemosensory genes evolve rapidly, it is unclear how they evolve in response to host shifts and host specialization. We investigate whether selection at chemosensory genes is linked to host-plant expansion from the buffalo burr, Solanum rostratum, to potato, Solanum tuberosum, in the super-pest Colorado potato beetle (CPB), Leptinotarsa decemlineata (Coleoptera: Chrysomelidae). First, to refine our knowledge of CPB chemosensory genes, we developed novel gene expression data for the antennae and maxillary-labial palps. We then examine patterns of selection at these loci within CPB, as well as compare whether rates of selection vary with respect to 9 closely related, non-pest Leptinotarsa species that vary in diet breadth. We find that rates of positive selection on olfactory receptors are higher in host-plant generalists, and this signal is particularly strong in CPB. These results provide strong candidates for further research on the genetic basis of variation in insect chemosensory performance and novel targets for pest control of a notorious super-pest.

Transposable elements differ between geographic populations of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae).

Agricultural insect herbivores show a remarkable ability to adapt to modern agroecosystems, making them ideal for the study of the mechanisms underlying rapid evolution. The mobilization of transposable elements is one mechanism that may help explain this ability. The Colorado potato beetle, Leptinotarsa decemlineata, is a highly adaptable species, as shown by its wide host range, broad geographic distribution, and tolerance to insecticides. However, beetle populations vary in insecticide tolerance, with Eastern US beetle populations being more adaptable than Western US ones. Here, we use a community ecology approach to examine how the abundance and diversity of transposable elements differs in 88 resequenced genomes of L. decemlineata collected throughout North America. We tested if assemblages and mobilization of transposable elements differed between populations of L. decemlineata based on the beetle's geography, host plant, and neonicotinoid insecticide resistance. Among populations of North American L. decemlineata, individuals collected in Mexico host more transposable elements than individuals collected in the United States. Transposable element insertion locations differ among geographic populations, reflecting the evolutionary history of this species. Total transposable element diversity between L. decemlineata individuals is enough to distinguish between populations, with more TEs found in beetles collected in Mexico than in the United States. Transposable element diversity does not appear to differ between beetles found on different host plants, or relate to different levels of insecticide resistance.

The development and internal evaluation of a predictive model to identify for whom Mindfulness-Based Cognitive Therapy (MBCT) offers superior relapse prevention for recurrent depression versus maintenance antidepressant medication.

Depression is highly recurrent, even following successful pharmacological and/or psychological intervention. We aimed to develop clinical prediction models to inform adults with recurrent depression choosing between antidepressant medication (ADM) maintenance or switching to Mindfulness-Based Cognitive Therapy (MBCT). Using data from the PREVENT trial (N=424), we constructed prognostic models using elastic net regression that combined demographic, clinical and psychological factors to predict relapse at 24 months under ADM or MBCT. Only the ADM model (discrimination performance: AUC=.68) predicted relapse better than baseline depression severity (AUC=.54; one-tailed DeLong's test: z=2.8, p=.003). Individuals with the poorest ADM prognoses who switched to MBCT had better outcomes compared to those who maintained ADM (48% vs. 70% relapse, respectively; superior survival times [z=-2.7, p=.008]). For individuals with moderate-to-good ADM prognosis, both treatments resulted in similar likelihood of relapse. If replicated, the results suggest that predictive modeling can inform clinical decision-making around relapse prevention in recurrent depression.

The role of structural variants in pest adaptation and genome evolution of the Colorado potato beetle, Leptinotarsa decemlineata (Say).

Structural variation has been associated with genetic diversity and adaptation. Despite these observations, it is not clear what their relative importance is for evolution, especially in rapidly adapting species. Here, we examine the significance of structural polymorphisms in pesticide resistance evolution of the agricultural super-pest, the Colorado potato beetle, Leptinotarsa decemlineata. By employing a parent offspring trio sequencing procedure, we develop highly contiguous reference genomes to characterize structural variation. These updated assemblies represent >100-fold improvement of contiguity and include derived pest and ancestral nonpest individuals. We identify >200,000 structural variations, which appear to be nonrandomly distributed across the genome as they co-occur with transposable elements and genes. Structural variations intersect with exons in a large proportion of gene annotations (~20%) that are associated with insecticide resistance (including cytochrome P450s), development, and transcription. To understand the role structural variations play in adaptation, we measure their allele frequencies among an additional 57 individuals using whole genome resequencing data, which represents pest and nonpest populations of North America. Incorporating multiple independent tests to detect the signature of natural selection using SNP data, we identify 14 genes that are probably under positive selection, include structural variations, and SNPs of elevated frequency within the pest lineages. Among these, three are associated with insecticide resistance based on previous research. One of these genes, CYP4g15, is coinduced during insecticide exposure with glycosyltransferase-13, which is a duplicated gene enclosed within a structural variant adjacent to the CYP4g15 genic region. These results demonstrate the significance of structural variations as a genomic feature to describe species history, genetic diversity, and adaptation.

Rapid evolution of insecticide resistance in the Colorado potato beetle, Leptinotarsa decemlineata.

Despite considerable research, efforts to manage insecticide resistance continue to fail. The Colorado potato beetle (CPB), Leptinotarsa decemlineata Say (Coleoptera: Chrysomelidae), epitomizes this problem, as it has repeatedly and rapidly evolved resistance to>50 insecticides. The patterns of resistance evolution are intriguing, as they defy models where resistance evolves from rare mutations. Here, we synthesize recent research on insecticide resistance in CPB showing that polygenic resistance drawn from standing genetic diversity explains genomic patterns of insecticide resistance evolution. However, rapid gene regulatory evolution suggests that other mechanisms might also facilitate adaptive change. We explore the hypothesis that sublethal stress from insecticide exposure could alter heritable epigenetic modifications, and discuss the range of experimental approaches needed to fully understand insecticide resistance evolution in this super pest.

Museum Genomics of an Agricultural Super-Pest, the Colorado Potato Beetle, Leptinotarsa decemlineata (Chrysomelidae), Provides Evidence of Adaptation from Standing Variation.

Despite extensive research on agricultural pests, our knowledge about their evolutionary history is often limited. A mechanistic understanding of the demographic changes and modes of adaptation remains an important goal, as it improves our understanding of organismal responses to environmental change and our ability to sustainably manage pest populations. Emerging genomic datasets now allow for characterization of demographic and adaptive processes, but face limits when they are drawn from contemporary samples, especially in the context of strong demographic change, repeated selection, or adaptation involving modest shifts in allele frequency at many loci. Temporal sampling, however, can improve our ability to reconstruct evolutionary events. Here, we leverage museum samples to examine whether population genomic diversity and structure has changed over time, and to identify genomic regions that appear to be under selection. We focus on the Colorado potato beetle (CPB), Leptinotarsa decemlineata (Say 1824; Coleoptera: Chrysomelidae), which is widely regarded as a super-pest due to its rapid, and repeated, evolution to insecticides. By combining whole genome resequencing data from 78 museum samples with modern sampling, we demonstrate that CPB expanded rapidly in the 19th century, leading to a reduction in diversity and limited genetic structure from the Midwest to Northeast United States. Temporal genome scans provide extensive evidence for selection acting in resistant field populations in Wisconsin and New York, including numerous known insecticide resistance genes. We also validate these results by showing that known selective sweeps in modern populations are identified by our genome scan. Perhaps most importantly, temporal analysis indicates selection on standing genetic variation, as we find evidence for parallel evolution in the two geographical regions. Parallel evolution involves a range of phenotypic traits not previously identified as under selection in CPB, such as reproductive and morphological functional pathways that might be important for adaptation to agricultural habitats.

Genome Resequencing Reveals Rapid, Repeated Evolution in the Colorado Potato Beetle.

Insecticide resistance and rapid pest evolution threatens food security and the development of sustainable agricultural practices, yet the evolutionary mechanisms that allow pests to rapidly adapt to control tactics remains unclear. Here, we examine how a global super-pest, the Colorado potato beetle (CPB), Leptinotarsa decemlineata, rapidly evolves resistance to insecticides. Using whole-genome resequencing and transcriptomic data focused on its ancestral and pest range in North America, we assess evidence for three, nonmutually exclusive models of rapid evolution: pervasive selection on novel mutations, rapid regulatory evolution, and repeated selection on standing genetic variation. Population genomic analysis demonstrates that CPB is geographically structured, even among recently established pest populations. Pest populations exhibit similar levels of nucleotide diversity, relative to nonpest populations, and show evidence of recent expansion. Genome scans provide clear signatures of repeated adaptation across CPB populations, with especially strong evidence of selection on insecticide resistance genes in different populations. Analyses of gene expression show that constitutive upregulation of candidate insecticide resistance genes drives distinctive population patterns. CPB evolves insecticide resistance repeatedly across agricultural regions, leveraging similar genetic pathways but different genes, demonstrating a polygenic trait architecture for insecticide resistance that can evolve from standing genetic variation. Despite expectations, we do not find support for strong selection on novel mutations, or rapid evolution from selection on regulatory genes. These results suggest that integrated pest management practices must mitigate the evolution of polygenic resistance phenotypes among local pest populations, in order to maintain the efficacy and sustainability of novel control techniques.

Stratified Care vs Stepped Care for Depression: A Cluster Randomized Clinical Trial.

Importance: Depression is a major cause of disability worldwide. Although empirically supported treatments are available, there is scarce evidence on how to effectively personalize psychological treatment selection. Objective: To compare the clinical effectiveness and cost-effectiveness of 2 treatment selection strategies: stepped care and stratified care. Design, Setting, and Participants: This multisite, cluster randomized clinical trial recruited participants from the English National Health Service from July 5, 2018, to February 1, 2019. Thirty clinicians working across 4 psychological therapy services were randomly assigned to provide stratified (n = 15) or stepped (n = 15) care. In stepped care, patients sequentially access low-intensity guided self-help followed by high-intensity psychotherapy. In stratified care, patients are matched with either low- or high-intensity treatments at initial assessment. Data were analyzed from May 18, 2020, to October 13, 2021, using intention-to-treat principles. Interventions: All clinicians used the same interview schedule to conduct initial assessments with patients seeking psychological treatment for common mental disorders, but those in the stratified care group received a personalized treatment recommendation for each patient generated by a machine learning algorithm. Eligible patients received either stratified or stepped care (ie, treatment as usual). Main Outcomes and Measures: The preregistered outcome was posttreatment reliable and clinically significant improvement (RCSI) of depression symptoms (measured using the 9-item Patient Health Questionnaire). The RCSI outcome was compared between groups using logistic regression adjusted for baseline severity. Cost-effectiveness analyses compared incremental costs and health outcomes of the 2 treatment pathways. Results: A total of 951 patients were included (618 women among 950 with data available [65.1%]; mean [SD] age, 38.27 [14.53] years). The proportion of cases of RCSI was significantly higher in the stratified care arm compared with the stepped care arm (264 of 505 [52.3%] vs 134 of 297 [45.1%]; odds ratio, 1.40 [95% CI, 1.04-1.87]; P = .03). Stratified care was associated with a higher mean additional cost per patient (£104.5 [95% CI, £67.5-£141.6] [$139.83 (95% CI, $90.32-$189.48)]; P < .001) because more patients accessed high-intensity treatments (332 of 583 [56.9%] vs 107 of 368 [29.1%]; χ2 = 70.51; P < .001), but this additional cost resulted in an approximately 7% increase in the probability of RCSI. Conclusions and Relevance: In this cluster randomized clinical trial of adults with common mental disorders, stratified care was efficacious and cost-effective for the treatment of depression symptoms compared with stepped care. Stratified care can improve depression treatment outcomes at a modest additional cost. Trial Registration: isrctn.org Identifier: ISRCTN11106183.

Evaluating the Effectiveness of Personalized Medicine With Software.

We present methodological advances in understanding the effectiveness of personalized medicine models and supply easy-to-use open-source software. Personalized medicine involves the systematic use of individual patient characteristics to determine which treatment option is most likely to result in a better average outcome for the patient. Why is personalized medicine not done more in practice? One of many reasons is because practitioners do not have any easy way to holistically evaluate whether their personalization procedure does better than the standard of care, termed improvement. Our software, "Personalized Treatment Evaluator" (the R package PTE), provides inference for improvement out-of-sample in many clinical scenarios. We also extend current methodology by allowing evaluation of improvement in the case where the endpoint is binary or survival. In the software, the practitioner inputs 1) data from a single-stage randomized trial with one continuous, incidence or survival endpoint and 2) an educated guess of a functional form of a model for the endpoint constructed from domain knowledge. The bootstrap is then employed on data unseen during model fitting to provide confidence intervals for the improvement for the average future patient (assuming future patients are similar to the patients in the trial). One may also test against a null scenario where the hypothesized personalization are not more useful than a standard of care. We demonstrate our method's promise on simulated data as well as on data from a randomized comparative trial investigating two treatments for depression.

Elevated rates of positive selection drive the evolution of pestiferousness in the Colorado potato beetle (Leptinotarsa decemlineata, Say).

Contextualizing evolutionary history and identifying genomic features of an insect that might contribute to its pest status is important in developing early detection and control tactics. In order to understand the evolution of pestiferousness, which we define as the accumulation of traits that contribute to an insect population's success in an agroecosystem, we tested the importance of known genomic properties associated with rapid adaptation in the Colorado potato beetle (CPB), Leptinotarsa decemlineata Say. Within the leaf beetle genus Leptinotarsa, only CPB, and a few populations therein, has risen to pest status on cultivated nightshades, Solanum. Using whole genomes from ten closely related Leptinotarsa species native to the United States, we reconstructed a high-quality species tree and used this phylogenetic framework to assess evolutionary patterns in four genomic features of rapid adaptation: standing genetic variation, gene family expansion and contraction, transposable element abundance and location, and positive selection at protein-coding genes. Throughout approximately 20 million years of history, Leptinotarsa species show little evidence of gene family turnover and transposable element variation. However, there is a clear pattern of CPB experiencing higher rates of positive selection on protein-coding genes. We determine that these rates are associated with greater standing genetic variation due to larger effective population size, which supports the theory that the demographic history contributes to rates of protein evolution. Furthermore, we identify a suite of coding genes under positive selection that are putatively associated with pestiferousness in the Colorado potato beetle lineage. They are involved in the biological processes of xenobiotic detoxification, chemosensation and hormone function.