Gene content evolution in the arthropods

Background: Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Results: Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. Conclusions: These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity

Lucilia cuprina genome unlocks parasitic fly biology to underpin future interventions

Lucilia cuprina is a parasitic fly of major economic importance worldwide. Larvae of this fly invade their animal host, feed on tissues and excretions and progressively cause severe skin disease (myiasis). Here we report the sequence and annotation of the 458-megabase draft genome of Lucilia cuprina. Analyses of this genome and the 14,544 predicted protein-encoding genes provide unique insights into the fly's molecular biology, interactions with the host animal and insecticide resistance. These insights have broad implications for designing new methods for the prevention and control of myiasis

Macrotermes natalensis manual gene annotations

Manual gene annotation in gff3 format for the termite Macrotermes natalensis. Part of the manuscript "Hemimetabolous genomes reveal molecular basis of termite eusociality.

The Toxicogenome of <i>Hyalella azteca</i>: A Model for Sediment Ecotoxicology and Evolutionary Toxicology

<i>Hyalella azteca</i> is a cryptic species complex of epibenthic amphipods of interest to ecotoxicology and evolutionary biology. It is the primary crustacean used in North America for sediment toxicity testing and an emerging model for molecular ecotoxicology. To provide molecular resources for sediment quality assessments and evolutionary studies, we sequenced, assembled, and annotated the genome of the <i>H. azteca</i> U.S. Lab Strain. The genome quality and completeness is comparable with other ecotoxicological model species. Through targeted investigation and use of gene expression data sets of <i>H. azteca</i> exposed to pesticides, metals, and other emerging contaminants, we annotated and characterized the major gene families involved in sequestration, detoxification, oxidative stress, and toxicant response. Our results revealed gene loss related to light sensing, but a large expansion in chemoreceptors, likely underlying sensory shifts necessary in their low light habitats. Gene family expansions were also noted for cytochrome P450 genes, cuticle proteins, ion transporters, and include recent gene duplications in the metal sequestration protein, metallothionein. Mapping of differentially expressed transcripts to the genome significantly increased the ability to functionally annotate toxicant responsive genes. The <i>H. azteca</i> genome will greatly facilitate development of genomic tools for environmental assessments and promote an understanding of how evolution shapes toxicological pathways with implications for environmental and human health

Multiscale modeling by time-evolving measures

This chapter is devoted to a multiscale approach to the modeling of crowd dynamics, which is the core topic of the book. We begin by presenting, in Sect. 5.1, a general measure-based modeling framework suitable to include the basic features of pedestrian kinematics at any scale. Specifically, we assume that pedestrian motion results from the interplay between the individual will to follow a preferred travel program and the necessity to face the rest of the crowd. We discuss in Sect. 5.2 how to properly model these behavioral aspects. In Sect. 5.3 we show how discrete (microscopic) and continuous (macroscopic) models can be obtained in the proposed framework, before focusing, in Sect. 5.4, on multiscale modeling issues. We also propose a detailed dimensional analysis, which highlights the role of a few significant parameters, and a numerical scheme for the approximate solution of the equations. The scheme is obtained in two steps in Sect. 5.5. First we derive a discrete-in-time model; next we discretize the space variable as well, obtaining an algorithm (cf. Appendix B) which can be implemented on a computer to produce simulations (cf. Chap.  2). Finally, in Sect. 5.6 we extend the previous modeling structures to the case of two interacting crowds