A molecular mechanism for environmental sex determination.

Daphnia produce genetically identical males and females; their sex is determined by environmental conditions. Recently, Kato et al. identified isoform switching events in Daphnia as a gene regulatory mechanism for sex-specific development. This finding uncovers the impact of alternative usage of gene isoforms on this extreme phenotypic plasticity trait.

Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay.

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).

Multi-omics bioactivity profile-based chemical grouping and read-across: a case study with Daphnia magna and azo dyes.

Grouping/read-across is widely used for predicting the toxicity of data-poor target substance(s) using data-rich source substance(s). While the chemical industry and the regulators recognise its benefits, registration dossiers are often rejected due to weak analogue/category justifications based largely on the structural similarity of source and target substances. Here we demonstrate how multi-omics measurements can improve confidence in grouping via a statistical assessment of the similarity of molecular effects. Six azo dyes provided a pool of potential source substances to predict long-term toxicity to aquatic invertebrates (Daphnia magna) for the dye Disperse Yellow 3 (DY3) as the target substance. First, we assessed the structural similarities of the dyes, generating a grouping hypothesis with DY3 and two Sudan dyes within one group. Daphnia magna were exposed acutely to equi-effective doses of all seven dyes (each at 3 doses and 3 time points), transcriptomics and metabolomics data were generated from 760 samples. Multi-omics bioactivity profile-based grouping uniquely revealed that Sudan 1 (S1) is the most suitable analogue for read-across to DY3. Mapping ToxPrint structural fingerprints of the dyes onto the bioactivity profile-based grouping indicated an aromatic alcohol moiety could be responsible for this bioactivity similarity. The long-term reproductive toxicity to aquatic invertebrates of DY3 was predicted from S1 (21-day NOEC, 40 µg/L). This prediction was confirmed experimentally by measuring the toxicity of DY3 in D. magna. While limitations of this 'omics approach are identified, the study illustrates an effective statistical approach for building chemical groups.

New approach methods to assess developmental and adult neurotoxicity for regulatory use: a PARC work package 5 project.

In the European regulatory context, rodent in vivo studies are the predominant source of neurotoxicity information. Although they form a cornerstone of neurotoxicological assessments, they are costly and the topic of ethical debate. While the public expects chemicals and products to be safe for the developing and mature nervous systems, considerable numbers of chemicals in commerce have not, or only to a limited extent, been assessed for their potential to cause neurotoxicity. As such, there is a societal push toward the replacement of animal models with in vitro or alternative methods. New approach methods (NAMs) can contribute to the regulatory knowledge base, increase chemical safety, and modernize chemical hazard and risk assessment. Provided they reach an acceptable level of regulatory relevance and reliability, NAMs may be considered as replacements for specific in vivo studies. The European Partnership for the Assessment of Risks from Chemicals (PARC) addresses challenges to the development and implementation of NAMs in chemical risk assessment. In collaboration with regulatory agencies, Project 5.2.1e (Neurotoxicity) aims to develop and evaluate NAMs for developmental neurotoxicity (DNT) and adult neurotoxicity (ANT) and to understand the applicability domain of specific NAMs for the detection of endocrine disruption and epigenetic perturbation. To speed up assay time and reduce costs, we identify early indicators of later-onset effects. Ultimately, we will assemble second-generation developmental neurotoxicity and first-generation adult neurotoxicity test batteries, both of which aim to provide regulatory hazard and risk assessors and industry stakeholders with robust, speedy, lower-cost, and informative next-generation hazard and risk assessment tools.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling.

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System.

We developed a simple screening system for the evaluation of neuromuscular and general toxicity in zebrafish embryos. The modular system consists of electrodynamic transducers above which tissue culture dishes with embryos can be placed. Multiple such loudspeaker-tissue culture dish pairs can be combined. Vibrational stimuli generated by the electrodynamic transducers induce a characteristic startle and escape response in the embryos. A belt-driven linear drive sequentially positions a camera above each loudspeaker to record the movement of the embryos. In this way, alterations to the startle response due to lethality or neuromuscular toxicity of chemical compounds can be visualized and quantified. We present an example of the workflow for chemical compound screening using this system, including the preparation of embryos and treatment solutions, operation of the recording system, and data analysis to calculate benchmark concentration values of compounds active in the assay. The modular assembly based on commercially available simple components makes this system both economical and flexibly adaptable to the needs of particular laboratory setups and screening purposes.

100 years of anthropogenic impact causes changes in freshwater functional biodiversity.

Despite efforts from scientists and regulators, biodiversity is declining at an alarming rate. Unless we find transformative solutions to preserve biodiversity, future generations may not be able to enjoy nature's services. We have developed a conceptual framework that establishes the links between biodiversity dynamics and abiotic change through time and space using artificial intelligence. Here, we apply this framework to a freshwater ecosystem with a known history of human impact and study 100 years of community-level biodiversity, climate change and chemical pollution trends. We apply explainable network models with multimodal learning to community-level functional biodiversity measured with multilocus metabarcoding, to establish correlations with biocides and climate change records. We observed that the freshwater community assemblage and functionality changed over time without returning to its original state, even if the lake partially recovered in recent times. Insecticides and fungicides, combined with extreme temperature events and precipitation, explained up to 90% of the functional biodiversity changes. The community-level biodiversity approach used here reliably explained freshwater ecosystem shifts. These shifts were not observed when using traditional quality indices (e.g. Trophic Diatom Index). Our study advocates the use of high-throughput systemic approaches on long-term trends over species-focused ecological surveys to identify the environmental factors that cause loss of biodiversity and disrupt ecosystem functions.

Over long periods of time, environmental changes ­ such as chemical pollution and climate change ­ affect the diversity of organisms that live in an ecosystem, known as 'biodiversity'. Understanding the impact of these changes is challenging because they can happen slowly, their effect is only measurable after years, and historical records are limited. This can make it difficult to determine when specific changes happened, what might have driven them and what impact they might be having. One way to measure changes in biodiversity over time is by analysing traces of DNA shed by organisms. Plants, animals, and bacteria living in lakes leave behind genetic material that gets trapped and buried in the sediment at the bottom of lakes. Similarly, biocides ­ substances used to kill or control populations of living organisms ­ that run-off into lakes leach into the sediment and can be measured years later. Therefore, this sediment holds a record of life and environmental impacts in the lake over past centuries. Eastwood, Zhou et al. wanted to understand the relationship between environmental changes (such as the use of biocides and climate change) and shifts in lake biodiversity. To do so, the researchers studied a lake community that had experienced major environmental impacts over the last century (including nutrient pollution, chemical pollution and climate change), but which appeared to improve over the last few years of the 20^th century. Using machine learning to find connections over time between biodiversity and non-living environmental changes, Eastwood, Zhou et al. showed that, despite apparent recovery in water quality, the biodiversity of the lake was not restored to its original state. A combination of climate factors (such as rainfall levels and extreme temperatures) and biocide application (particularly insecticides and fungicides) explained up to 90% of the biodiversity changes that occurred in the lake. These changes had not been identified before using traditional techniques. The functional roles microorganisms played in the ecosystem (such as degradation and nitrogen metabolism) were also altered, suggesting that loss of biodiversity may lead to loss of ecosystem functions. The findings described by Eastwood, Zhou et al. can be used by environmental regulators to identify species or ecosystems at risk from environmental change and prioritise them for intervention. The approach can also be used to identify which chemicals pose the greatest threat to biodiversity. Additionally, the use of environmental DNA from sediment can provide rich historical biodiversity data, which can be used to train artificial intelligence-based models to improve predictions of how ecosystems will respond to complex environmental changes.

The hologenome of Daphnia magna reveals possible DNA methylation and microbiome-mediated evolution of the host genome.

Properties that make organisms ideal laboratory models in developmental and medical research are often the ones that also make them less representative of wild relatives. The waterflea Daphnia magna is an exception, by both sharing many properties with established laboratory models and being a keystone species, a sentinel species for assessing water quality, an indicator of environmental change and an established ecotoxicology model. Yet, Daphnia's full potential has not been fully exploited because of the challenges associated with assembling and annotating its gene-rich genome. Here, we present the first hologenome of Daphnia magna, consisting of a chromosomal-level assembly of the D. magna genome and the draft assembly of its metagenome. By sequencing and mapping transcriptomes from exposures to environmental conditions and from developmental morphological landmarks, we expand the previously annotates gene set for this species. We also provide evidence for the potential role of gene-body DNA-methylation as a mutagen mediating genome evolution. For the first time, our study shows that the gut microbes provide resistance to commonly used antibiotics and virulence factors, potentially mediating Daphnia's environmental-driven rapid evolution. Key findings in this study improve our understanding of the contribution of DNA methylation and gut microbiota to genome evolution in response to rapidly changing environments.

Assessment of Chemical Toxicity in Adult Drosophila Melanogaster.

Human industries generate hundreds of thousands of chemicals, many of which have not been adequately studied for environmental safety or effects on human health. This deficit of chemical safety information is exacerbated by current testing methods in mammals that are expensive, labor-intensive, and time-consuming. Recently, scientists and regulators have been working to develop new approach methodologies (NAMs) for chemical safety testing that are cheaper, more rapid, and reduce animal suffering. One of the key NAMs to emerge is the use of invertebrate organisms as replacements for mammalian models to elucidate conserved chemical modes of action across distantly related species, including humans. To advance these efforts, here, we describe a method that uses the fruit fly, Drosophila melanogaster, to assess chemical safety. The protocol describes a simple, rapid, and inexpensive procedure to measure the viability and feeding behavior of exposed adult flies. In addition, the protocol can be easily adapted to generate samples for genomic and metabolomic approaches. Overall, the protocol represents an important step forward in establishing Drosophila as a standard model for use in precision toxicology.

Modernizing persistence-bioaccumulation-toxicity (PBT) assessment with high throughput animal-free methods.

The assessment of persistence (P), bioaccumulation (B), and toxicity (T) of a chemical is a crucial first step at ensuring chemical safety and is a cornerstone of the European Union's chemicals regulation REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals). Existing methods for PBT assessment are overly complex and cumbersome, have produced incorrect conclusions, and rely heavily on animal-intensive testing. We explore how new-approach methodologies (NAMs) can overcome the limitations of current PBT assessment. We propose two innovative hazard indicators, termed cumulative toxicity equivalents (CTE) and persistent toxicity equivalents (PTE). Together they are intended to replace existing PBT indicators and can also accommodate the emerging concept of PMT (where M stands for mobility). The proposed "toxicity equivalents" can be measured with high throughput in vitro bioassays. CTE refers to the toxic effects measured directly in any given sample, including single chemicals, substitution products, or mixtures. PTE is the equivalent measure of cumulative toxicity equivalents measured after simulated environmental degradation of the sample. With an appropriate panel of animal-free or alternative in vitro bioassays, CTE and PTE comprise key environmental and human health hazard indicators. CTE and PTE do not require analytical identification of transformation products and mixture components but instead prompt two key questions: is the chemical or mixture toxic, and is this toxicity persistent or can it be attenuated by environmental degradation? Taken together, the proposed hazard indicators CTE and PTE have the potential to integrate P, B/M and T assessment into one high-throughput experimental workflow that sidesteps the need for analytical measurements and will support the Chemicals Strategy for Sustainability of the European Union.

Daphnia as a Sentinel Species for Environmental Health Protection: A Perspective on Biomonitoring and Bioremediation of Chemical Pollution.

Despite available technology and the knowledge that chemical pollution damages human and ecosystem health, chemical pollution remains rampant, ineffectively monitored, rarely prevented, and only occasionally mitigated. We present a framework that helps address current major challenges in the monitoring and assessment of chemical pollution by broadening the use of the sentinel species Daphnia as a diagnostic agent of water pollution. And where prevention has failed, we propose the application of Daphnia as a bioremediation agent to help reduce hazards from chemical mixtures in the environment. By applying "omics" technologies to Daphnia exposed to real-world ambient chemical mixtures, we show improvements at detecting bioactive components of chemical mixtures, determining the potential effects of untested chemicals within mixtures, and identifying targets of toxicity. We also show that using Daphnia strains that naturally adapted to chemical pollution as removal agents of ambient chemical mixtures can sustainably improve environmental health protection. Expanding the use of Daphnia beyond its current applications in regulatory toxicology has the potential to improve both the assessment and the remediation of environmental pollution.

Combined exome and transcriptome sequencing of non-muscle-invasive bladder cancer: associations between genomic changes, expression subtypes, and clinical outcomes.

BACKGROUND: Three-quarters of bladder cancer patients present with early-stage disease (non-muscle-invasive bladder cancer, NMIBC, UICC TNM stages Ta, T1 and Tis); however, most next-generation sequencing studies to date have concentrated on later-stage disease (muscle-invasive BC, stages T2+). We used exome and transcriptome sequencing to comprehensively characterise NMIBCs of all grades and stages to identify prognostic genes and pathways that could facilitate treatment decisions. Tumour grading is based upon microscopy and cellular appearances (grade 1 BCs are less aggressive, and grade 3 BCs are most aggressive), and we chose to also focus on the most clinically complex NMIBC subgroup, those patients with grade 3 pathological stage T1 (G3 pT1) disease. METHODS: Whole-exome and RNA sequencing were performed in total on 96 primary NMIBCs including 22 G1 pTa, 14 G3 pTa and 53 G3 pT1s, with both exome and RNA sequencing data generated from 75 of these individual samples. Associations between genomic alterations, expression profiles and progression-free survival (PFS) were investigated. RESULTS: NMIBCs clustered into 3 expression subtypes with different somatic alteration characteristics. Amplifications of ARNT and ERBB2 were significant indicators of worse PFS across all NMIBCs. High APOBEC mutagenesis and high tumour mutation burden were both potential indicators of better PFS in G3pT1 NMIBCs. The expression of individual genes was not prognostic in BCG-treated G3pT1 NMIBCs; however, downregulated interferon-alpha and gamma response pathways were significantly associated with worse PFS (adjusted p-value < 0.005). CONCLUSIONS: Multi-omic data may facilitate better prognostication and selection of therapeutic interventions in patients with G3pT1 NMIBC. These findings demonstrate the potential for improving the management of high-risk NMIBC patients and warrant further prospective validation.

Knowledge-Driven Approaches to Create the MTox700+ Metabolite Panel for Predicting Toxicity.

Endogenous metabolite levels describe the molecular phenotype that is most downstream from chemical exposure. Consequently, quantitative changes in metabolite levels have the potential to predict mode-of-action and adversity, with regulatory toxicology predicated on the latter. However, toxicity-related metabolic biomarker resources remain highly fragmented and incomplete. Although development of the S1500+ gene biomarker panel has accelerated the application of transcriptomics to toxicology, a similar initiative for metabolic biomarkers is lacking. Our aim was to define a publicly available metabolic biomarker panel, equivalent to S1500+, capable of predicting pathway perturbations and/or adverse outcomes. We conducted a systematic review of multiple toxicological resources, yielding 189 proposed metabolic biomarkers from existing assays (BASF, Bowes-44, and Tox21), 342 biomarkers from databases (Adverse Outcome Pathway Wiki, Comparative Toxicogenomics Database, QIAGEN Ingenuity Pathway Analysis, and Toxin and Toxin-Target Database), and 435 biomarkers from the literature. Evidence mapping across all 8 resources generated a panel of 722 metabolic biomarkers for toxicology (MTox700+), of which 462 (64%) are associated with molecular pathways and 575 (80%) with adverse outcomes. Comparing MTox700+ and S1500+ revealed that 418 (58%) metabolic biomarkers associate with pathways shared across both panels, with further metabolites mapping to unique pathways. Metabolite reference standards are commercially available for 646 (90%) of the panel metabolites, and assays exist for 578 (80%) of these biomarkers. This study has generated a publicly available metabolic biomarker panel for toxicology, which through its future laboratory deployment, is intended to help build foundational knowledge to support the generation of molecular mechanistic data for chemical hazard assessment.

Refining the evolutionary time machine: An assessment of whole genome amplification using single historical Daphnia eggs.

Whole genome sequencing is instrumental for the study of genome variation in natural populations, delivering important knowledge on genomic modifications and potential targets of natural selection at the population level. Large dormant eggbanks of aquatic invertebrates such as the keystone herbivore Daphnia, a microcrustacean widespread in freshwater ecosystems, provide detailed sedimentary archives to study genomic processes over centuries. To overcome the problem of limited DNA amounts in single Daphnia dormant eggs, we developed an optimized workflow for whole genome amplification (WGA), yielding sufficient amounts of DNA for downstream whole genome sequencing of individual historical eggs, including polyploid lineages. We compare two WGA kits, applied to recently produced Daphnia magna dormant eggs from laboratory cultures, and to historical dormant eggs of Daphnia pulicaria collected from Arctic lake sediment between 10 and 300 years old. Resulting genome coverage breadth in most samples was ~70%, including those from >100-year-old isolates. Sequence read distribution was highly correlated among samples amplified with the same kit, but less correlated between kits. Despite this, a high percentage of genomic positions with single nucleotide polymorphisms in one or more samples (maximum of 74% between kits, and 97% within kits) were recovered at a depth required for genotyping. As a by-product of sequencing we obtained 100% coverage of the mitochondrial genomes even from the oldest isolates (~300 years). The mitochondrial DNA provides an additional source for evolutionary studies of these populations. We provide an optimized workflow for WGA followed by whole genome sequencing including steps to minimize exogenous DNA.

Toxicity by descent: A comparative approach for chemical hazard assessment.

Toxicology is traditionally divided between human and eco-toxicology. In the shared pursuit of environmental health, this separation does not account for discoveries made in the comparative studies of animal genomes. Here, we provide evidence on the feasibility of understanding the health impact of chemicals on all animals, including ecological keystone species and humans, based on a significant number of conserved genes and their functional associations to health-related outcomes across much of animal diversity. We test four conditions to understand the value of comparative genomics data to inform mechanism-based human and environmental hazard assessment: (1) genes that are most fundamental for health evolved early during animal evolution; (2) the molecular functions of pathways are better conserved among distantly related species than the individual genes that are members of these pathways; (3) the most conserved pathways among animals are those that cause adverse health outcomes when disrupted; (4) gene sets that serve as molecular signatures of biological processes or disease-states are largely enriched by evolutionarily conserved genes across the animal phylogeny. The concept of homology is applied in a comparative analysis of gene families and pathways among invertebrate and vertebrate species compared with humans. Results show that over 70% of gene families associated with disease are shared among the greatest variety of animal species through evolution. Pathway conservation between invertebrates and humans is based on the degree of conservation within vertebrates and the number of interacting genes within the human network. Human gene sets that already serve as biomarkers are enriched by evolutionarily conserved genes across the animal phylogeny. By implementing a comparative method for chemical hazard assessment, human and eco-toxicology converge towards a more holistic and mechanistic understanding of toxicity disrupting biological processes that are important for health and shared among animals (including humans).

Extensive standing genetic variation from a small number of founders enables rapid adaptation in Daphnia.

We lack a thorough understanding of the origin and maintenance of standing genetic variation that enables rapid evolutionary responses of natural populations. Whole genome sequencing of a resurrected Daphnia population shows that standing genetic variation in over 500 genes follows an evolutionary trajectory that parallels the pronounced and rapid adaptive evolution of multiple traits in response to predator-driven natural selection and its subsequent relaxation. Genetic variation carried by only five founding individuals from the regional genotype pool is shown to suffice at enabling the observed evolution. Our results provide insight on how natural populations can acquire the genomic variation, through colonization by a few regional genotypes, that fuels rapid evolution in response to strong selection pressures. While these evolutionary responses in our study population involved hundreds of genes, we observed no evidence of genetic erosion.

Spatio-temporal processes drive fine-scale genetic structure in an otherwise panmictic seabird population.

When and where animals breed can shape the genetic structure and diversity of animal populations. The importance of drivers of genetic diversity is amplified in island populations that tend to have more delineated gene pools compared to continental populations. Studies of relatedness as a function of the spatial distribution of individuals have demonstrated the importance of spatial organisation for individual fitness with outcomes that are conditional on the overall genetic diversity of the population. However, few studies have investigated the impact of breeding timing on genetic structure. We characterise the fine-scale genetic structure of a geographically-isolated population of seabirds. Microsatellite markers provide evidence for largely transient within-breeding season temporal processes and limited spatial processes, affecting genetic structure in an otherwise panmictic population of sooty terns Onychoprion fuscatus. Earliest breeders had significantly different genetic structure from the latest breeders. Limited evidence was found for localised spatial structure, with a small number of individuals being more related to their nearest neighbours than the rest of the population. Therefore, population genetic structure is shaped by heterogeneities in collective movement in time and to a lesser extent space, that result in low levels of spatio-temporal genetic structure and the maintenance of genetic diversity.

Broccoli: Combining Phylogenetic and Network Analyses for Orthology Assignment.

Orthology assignment is a key step of comparative genomic studies, for which many bioinformatic tools have been developed. However, all gene clustering pipelines are based on the analysis of protein distances, which are subject to many artifacts. In this article, we introduce Broccoli, a user-friendly pipeline designed to infer, with high precision, orthologous groups, and pairs of proteins using a phylogeny-based approach. Briefly, Broccoli performs ultrafast phylogenetic analyses on most proteins and builds a network of orthologous relationships. Orthologous groups are then identified from the network using a parameter-free machine learning algorithm. Broccoli is also able to detect chimeric proteins resulting from gene-fusion events and to assign these proteins to the corresponding orthologous groups. Tested on two benchmark data sets, Broccoli outperforms current orthology pipelines. In addition, Broccoli is scalable, with runtimes similar to those of recent distance-based pipelines. Given its high level of performance and efficiency, this new pipeline represents a suitable choice for comparative genomic studies. Broccoli is freely available at https://github.com/rderelle/Broccoli.

Sex biased expression and co-expression networks in development, using the hymenopteran Nasonia vitripennis.

Sexual dimorphism requires regulation of gene expression in developing organisms. These developmental differences are caused by differential expression of genes and isoforms. The effect of expressing a gene is also influenced by which other genes are simultaneously expressed (functional interactions). However, few studies have described how these processes change across development. We compare the dynamics of differential expression, isoform switching and functional interactions in the sexual development of the model parasitoid wasp Nasonia vitripennis, a system that permits genome wide analysis of sex bias from early embryos to adults. We find relatively little sex-bias in embryos and larvae at the gene level, but several sub-networks show sex-biased functional interactions in early developmental stages. These networks provide new candidates for hymenopteran sex determination, including histone modification. In contrast, sex-bias in pupae and adults is driven by the differential expression of genes. We observe sex-biased isoform switching consistently across development, but mostly in genes that are already differentially expressed. Finally, we discover that sex-biased networks are enriched by genes specific to the Nasonia clade, and that those genes possess the topological properties of key regulators. These findings suggest that regulators in sex-biased networks evolve more rapidly than regulators of other developmental networks.