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Abstract MotivationThe scale and scope of comparative trait data are expanding at unprecedented rates, and recent advances in evolutionary modeling and simulation sometimes struggle to match this pace. Well-organized and flexible applications for conducting large-scale simulations of evolution hold promise in this context for understanding models and more so our ability to confidently estimate them with real trait data sampled from nature. ResultsWe introduce TraitTrainR, an R package designed to facilitate efficient, large-scale simulations under complex models of continuous trait evolution. TraitTrainR employs several output formats, supports popular trait data transformations, accommodates multi-trait evolution, and exhibits flexibility in defining input parameter space and model stacking. Moreover, TraitTrainR permits measurement error, allowing for investigation of its potential impacts on evolutionary inference. We envision a wealth of applications of TraitTrainR, and we demonstrate one such example by examining the problem of evolutionary model selection in three empirical phylogenetic case studies. Collectively, these demonstrations of applying TraitTrainR to explore problems in model selection underscores its utility and broader promise for addressing key questions, including those related to experimental design and statistical power, in comparative biology. Availability and implementationTraitTrainR is developed in R 4.4.0 and is freely available at https://github.com/radamsRHA/TraitTrainR/, which includes detailed documentation, quick-start guides, and a step-by-step tutorial. 

Abstract The common bed bug, Cimex lectularius, is a globally distributed pest insect of medical, veterinary, and economic importance. Previous reference genome assemblies for this species were generated from short read sequencing data, resulting in a ~650 Mb composed of thousands of contigs. Here, we present a haplotype-resolved, chromosome-level reference genome, generated from an adult Harlen strain female specimen. Using PacBio long read and Omni-C proximity sequencing, we generated a 540 Mb genome with 15 chromosomes (13 autosomes and 2 sex chromosomes - X1X2) with an N50 > 30 Mb and BUSCO > 90%. Previous karyotyping efforts indicate an XY sex chromosome system, with 2n=26 and X1X1X2X2 females and X1X2Y males; however significant fragmentation of the X chromosome has also been reported. We further use whole genome resequencing data from males and females to identify the X1 and X2 chromosomes based on sex biases in coverage. This highly contiguous reference genome assembly provides a much-improved resource for identifying chromosomal genome architecture, and for interpreting patterns of urban outbreaks and signatures of selection linked to insecticide resistance. 

Abstract Understanding and predicting the relationships between genotype and phenotype is often challenging, largely due to the complex nature of eukaryotic gene regulation. A step towards this goal is to map how phenotypic diversity evolves through genomic changes that modify gene regulatory interactions. Using the Prairie Rattlesnake (Crotalus viridis) and related species, we integrate mRNA-seq, proteomic, ATAC-seq and whole genome resequencing data to understand how specific evolutionary modifications to gene regulatory network components produce differences in venom gene expression. Through comparisons within and between species, we find a remarkably high degree of gene expression and regulatory network variation across even a shallow level of evolutionary divergence. We use these data to test hypotheses about the roles of specific trans-factors and cis-regulatory elements, how these roles may vary across venom genes and gene families, and how variation in regulatory systems drive diversity in venom phenotypes. Our results illustrate that differences in chromatin and genotype at regulatory elements play major roles in modulating expression. However, we also find that enhancer deletions, differences in transcription-factor expression, and variation in activity of the insulator protein CTCF also likely impact venom phenotypes. Our findings provide insight into the diversity and gene-specificity of gene regulatory features and highlight the value of comparative studies to link gene regulatory network variation to phenotypic variation. 

There are calls for research into the historical evolutionary relationships between humans and their commensals, as it would greatly inform models that predict the spread of pests and diseases under urban population expansion. The earliest civilizations emerged approximately 10 000 years ago and created conditions ideal for the establishment and spread of commensal urban pests. Commensal relations between humans and pests likely emerged with these early civilizations; however, for most species (e.g. German cockroach and black rat), these relationships have formed relatively recently—within the last 5000 years—raising the question of whether others could have emerged earlier. Following comparative whole genome analysis of bed bugs,Cimex lectularius, belonging to two genetically distinct lineages, one associated with bats and the other with humans, coupled with demographic modelling, our findings suggests that while their association with humans dates back potentially hundreds of thousands of years, a dramatic change in the effective population size of the human-associated lineage occurred approximately 13 000 years ago; a pattern not found in the bat-associated lineage. The timing and magnitude of the demographic patterns provide compelling evidence that the human-associated lineage closely tracked the demographic history of modern humans and their movement into the first cities. As such, bed bugs may represent the firsttrueurban pest insect species.