Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

Gene-environment interactions within a precision environmental health framework

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

Investigation of Peroxisome Proliferator-Activated Receptor Genes as Requirements for Visual Startle Response Hyperactivity in Larval Zebrafish Exposed to Structurally Similar Per- and Polyfluoroalkyl Substances (PFAS)

BACKGROUND

Per- and polyfluoroalkyl Substances (PFAS) are synthetic chemicals widely detected in humans and the environment. Exposure to perfluorooctanesulfonic acid (PFOS) or perfluorohexanesulfonic acid (PFHxS) was previously shown to cause dark-phase hyperactivity in larval zebrafish.

OBJECTIVES

The objective of this study was to elucidate the mechanism by which PFOS or PFHxS exposure caused hyperactivity in larval zebrafish.

METHODS

Swimming behavior was assessed in 5-d postfertilization (dpf) larvae following developmental (1-4 dpf) or acute (5 dpf) exposure to 0.43 - 7.86 μ M PFOS, 7.87 - 120 μ M PFHxS, or 0.4% dimethyl sulfoxide (DMSO). After developmental exposure and chemical washout at 4 dpf, behavior was also assessed at 5-8 dpf. RNA sequencing was used to identify differences in global gene expression to perform transcriptomic benchmark concentration-response (BMC T ) modeling, and predict upstream regulators in PFOS- or PFHxS-exposed larvae. CRISPR/Cas9-based gene editing was used to knockdown peroxisome proliferator-activated receptors (ppars) pparaa/ab, pparda/db, or pparg at day 0. Knockdown crispants were exposed to 7.86 μ M PFOS or 0.4% DMSO from 1-4 dpf and behavior was assessed at 5 dpf. Coexposure with the ppard antagonist GSK3787 and PFOS was also performed.

RESULTS

Transient dark-phase hyperactivity occurred following developmental or acute exposure to PFOS or PFHxS, relative to the DMSO control. In contrast, visual startle response (VSR) hyperactivity only occurred following developmental exposure and was irreversible up to 8 dpf. Similar global transcriptomic profiles, BMC T estimates, and enriched functions were observed in PFOS- and PFHxS-exposed larvae, and ppars were identified as putative upstream regulators. Knockdown of pparda/db, but not pparaa/ab or pparg, blunted PFOS-dependent VSR hyperactivity to control levels. This finding was confirmed via antagonism of ppard in PFOS-exposed larvae.

DISCUSSION

This work identifies a novel adverse outcome pathway for VSR hyperactivity in larval zebrafish. We demonstrate that developmental, but not acute, exposure to PFOS triggered persistent VSR hyperactivity that required ppard function. https://doi.org/10.1289/EHP13667.

Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies

Zebrafish have become an essential tool in screening for developmental neurotoxic chemicals and their molecular targets. The success of zebrafish as a screening model is partially due to their physical characteristics including their relatively simple nervous system, rapid development, experimental tractability, and genetic diversity combined with technical advantages that allow for the generation of large amounts of high-dimensional behavioral data. These data are complex and require advanced machine learning and statistical techniques to comprehensively analyze and capture spatiotemporal responses. To accomplish this goal, we have trained semi-supervised deep autoencoders using behavior data from unexposed larval zebrafish to extract quintessential "normal" behavior. Following training, our network was evaluated using data from larvae shown to have significant changes in behavior (using a traditional statistical framework) following exposure to toxicants that include nanomaterials, aromatics, per- and polyfluoroalkyl substances (PFAS), and other environmental contaminants. Further, our model identified new chemicals (Perfluoro-n-octadecanoic acid, 8-Chloroperfluorooctylphosphonic acid, and Nonafluoropentanamide) as capable of inducing abnormal behavior at multiple chemical-concentrations pairs not captured using distance moved alone. Leveraging this deep learning model will allow for better characterization of the different exposure-induced behavioral phenotypes, facilitate improved genetic and neurobehavioral analysis in mechanistic determination studies and provide a robust framework for analyzing complex behaviors found in higher-order model systems.

Exposomics as a tool to investigate differences in health and disease by sex and gender

The health and disease of an individual is mediated by their genetics, a lifetime of environmental exposures, and interactions between the two. Genetic or biological sex, including chromosome composition and hormone expression, may influence both the types and frequency of environmental exposures an individual experiences, as well as the biological responses an individual has to those exposures. Gender identity, which can be associated with social behaviors such as expressions of self, may also mediate the types and frequency of exposures an individual experiences. Recent advances in exposome-level analysis have progressed our understanding of how environmental factors affect health outcomes; however, the relationship between environmental exposures and sex- and gender-specific health remains underexplored. The comprehensive, non-targeted, and unbiased nature of exposomic research provides a unique opportunity to systematically evaluate how environmental exposures interact with biological sex and gender identity to influence health. In this forward-looking narrative review, we provide examples of how biological sex and gender identity influence environmental exposures, discuss how environmental factors may interact with biological processes, and highlight how an intersectional approach to exposomics can provide critical insights for sex- and gender-specific health sciences.

Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure

Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical's potential to elicit GxE is often not considered during risk assessment. Previously, we've leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE.

Paraben exposures and their interactions with ESR1/2 genetic polymorphisms on hypertension

The widely used paraben preservatives have been frequently detected in human urine, and shown to disrupt the endocrine system. Recently, several epidemiologic studies have investigated the associations between paraben exposures and hypertension risk, but findings are inconsistent. Genetic susceptibility variation may contribute to the conflicting results. This study aimed to explore the associations of paraben exposures and their interactions with estrogen receptor genes 1 and 2 (ESR1 and ESR2) polymorphisms with hypertension. We conducted a hospital-based case-control study involving 396 hypertension cases and 396 controls in Wuhan, China. The urinary paraben concentrations were determined using a liquid chromatography-quadrupole time of flight mass spectrometer. The genotyping of ESR1 and ESR2 was performed using the Applied Biosystems 3730 XL sequencer. Multivariable logistic regression models were applied to examine the associations between urinary paraben concentrations and hypertension risk. Gene-environment interactions were estimated on both multiplicative and additive scales. The results showed that urinary ethylparaben (EtP), propylparaben (PrP), and ∑parabens (∑PBs) levels were positively associated with the risk of hypertension (P_trend<0.05). Compared with their reference groups, subjects in the highest tertile of EtP, PrP, and ∑PBs had a 4.05-fold (95% CI: 2.56, 6.41), 2.72-fold (95% CI: 1.76, 4.20), and 1.60-fold (95% CI: 1.08, 2.36) increased risk of hypertension, respectively. When stratified by sex, the hypertensive effect of EtP was more pronounced in males (P_interaction = 0.012). Furthermore, interaction analysis showed that PrP exposure interacted with ESR1 rs2234693 polymorphism on hypertension risk, with the significance of multiplicative (P_interaction = 0.043) and additive (RERI = 1.27, AP = 0.52). Our results suggested that paraben exposure was positively related to hypertension risk, and that ESR1 rs2234693 polymorphism might modify the parabens exposure-related hypertensive effect.

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health.

Leveraging a High-Throughput Screening Method to Identify Mechanisms of Individual Susceptibility Differences in a Genetically Diverse Zebrafish Model

Understanding the mechanisms behind chemical susceptibility differences is key to protecting sensitive populations. However, elucidating gene-environment interactions (GxE) presents a daunting challenge. While mammalian models have proven useful, problems with scalability to an enormous chemical exposome and clinical translation faced by all models remain; therefore, alternatives are needed. Zebrafish (Danio rerio) have emerged as an excellent model for investigating GxE. This study used a combined bioinformatic and experimental approach to probe the mechanisms underlying chemical susceptibility differences in a genetically diverse zebrafish population. Starting from high-throughput screening (HTS) data, a genome-wide association study (GWAS) using embryonic fish exposed to 0.6 μM Abamectin revealed significantly different effects between individuals. A hypervariable region with two distinct alleles–one with G at the SNP locus (GG) and one with a T and the 16 bp deletion (TT)–associated with differential susceptibility was found. Sensitive fish had significantly lower sox7 expression. Due to their location and the observed expression differences, we hypothesized that these sequences differentially regulate sox7. A luciferase reporter gene assay was used to test if these sequences, alone, could lead to expression differences. The TT allele showed significantly lower expression than the GG allele in MCF-7 cells. To better understand the mechanism behind these expression differences, predicted transcription factor binding differences between individuals were compared in silico, and several putative binding differences were identified. EMSA was used to test for binding differences in whole embryo protein lysate to investigate these TF binding predictions. We confirmed that the GG sequence is bound to protein in zebrafish. Through a competition EMSA using an untagged oligo titration, we confirmed that the GG oligo had a higher binding affinity than the TT oligo, explaining the observed expression differences. This study identified differential susceptibility to chemical exposure in a genetically diverse population, then identified a plausible mechanism behind those differences from a genetic to molecular level. Thus, an HTS-compatible zebrafish model is valuable and adaptable in identifying GxE mechanisms behind susceptibility differences to chemical exposure.

Analysis of Gene-Environment Interactions Related to Developmental Disorders

Various genetic and environmental factors are associated with developmental disorders (DDs). It has been suggested that interaction between genetic and environmental factors (G × E) is involved in the etiology of DDs. There are two major approaches to analyze the interaction: genome-wide and candidate gene-based approaches. In this mini-review, we demonstrate how these approaches can be applied to reveal the G × E related to DDs focusing on zebrafish and mouse models. We also discuss novel approaches to analyze the G × E associated with DDs.

CRISPR approach in environmental chemical screening focusing on population variability

A significant barrier to include population variability in risk assessment is our incomplete understanding of inter-individual variability and the differential susceptibility to environmental exposures induced adverse outcomes. By combining genome editing tools with the population diversity model, this article intended to highlight a potential strategy to identify and characterize the inter-individual variability factors, the determinant gene anchoring to a particular phenotype. The goal could be achieved by integrating the perturbed CRISPR-based unbiased functional genomics screening, genome-wide or a focused subset of genes, in a population-based in vitro model system (such as the lymphoblastoid cell lines, LCL, available from HapMap and 1000 Genomes project). Then data can be translated to genetic variability and individual (or subpopulation) susceptibility by incorporating ethnicity and corresponding genome-wide association studies (GWAS) with functional genomics screening results. This approach can provide complementary data for next-generation risk assessment, in particular, for environmental stressors. The current paper outlined the previous work conducted with a population-based in vitro model system, perturbed CRISPR-based functional toxicogenomic screening of environmental chemicals, and finally, the potential strategies to combine these two platforms with their opportunities and challenges to achieve a mechanistic understanding of population variability.

Commentary: Novel strategies and new tools to curtail the health effects of pesticides

BACKGROUND

Flaws in the science supporting pesticide risk assessment and regulation stand in the way of progress in mitigating the human health impacts of pesticides. Critical problems include the scope of regulatory testing protocols, the near-total focus on pure active ingredients rather than formulated products, lack of publicly accessible information on co-formulants, excessive reliance on industry-supported studies coupled with reticence to incorporate published results in the risk assessment process, and failure to take advantage of new scientific opportunities and advances, e.g. biomonitoring and "omics" technologies.

RECOMMENDED ACTIONS

Problems in pesticide risk assessment are identified and linked to study design, data, and methodological shortcomings. Steps and strategies are presented that have potential to deepen scientific knowledge of pesticide toxicity, exposures, and risks. We propose four solutions: (1) End near-sole reliance in regulatory decision-making on industry-supported studies by supporting and relying more heavily on independent science, especially for core toxicology studies. The cost of conducting core toxicology studies at labs not affiliated with or funded directly by pesticide registrants should be covered via fees paid by manufacturers to public agencies. (2) Regulators should place more weight on mechanistic data and low-dose studies within the range of contemporary exposures. (3) Regulators, public health agencies, and funders should increase the share of exposure-assessment resources that produce direct measures of concentrations in bodily fluids and tissues. Human biomonitoring is vital in order to quickly identify rising exposures among vulnerable populations including applicators, pregnant women, and children. (4) Scientific tools across disciplines can accelerate progress in risk assessments if integrated more effectively. New genetic and metabolomic markers of adverse health impacts and heritable epigenetic impacts are emerging and should be included more routinely in risk assessment to effectively prevent disease.

CONCLUSIONS

Preventing adverse public health outcomes triggered or made worse by exposure to pesticides will require changes in policy and risk assessment procedures, more science free of industry influence, and innovative strategies that blend traditional methods with new tools and mechanistic insights.

Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery

BACKGROUND

Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.

OBJECTIVES

We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.

DISCUSSION

The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome-the totality of the biologically active exposures relevant to disease development-through coupling biochemical receptor-binding assays with affinity purification-mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.

CONCLUSIONS

Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327.

In vivo assessment of respiratory burst inhibition by xenobiotic exposure using larval zebrafish

Currently, assessment of the potential immunotoxicity of a given agent involves a tiered approach for hazard identification and mechanistic studies, including observational studies, evaluation of immune function, and measurement of susceptibility to infectious and neoplastic diseases. These studies generally use costly low-throughput mammalian models. Zebrafish, however, offer an excellent alternative due to their rapid development, ease of maintenance, and homology to mammalian immune system function and development. Larval zebrafish also are a convenient model to study the innate immune system with no interference from the adaptive immune system. In this study, a respiratory burst assay (RBA) was utilized to measure reactive oxygen species (ROS) production after developmental xenobiotic exposure. Embryos were exposed to non-teratogenic doses of chemicals and at 96 h post-fertilization, the ability to produce ROS was measured. Using the RBA, 12 compounds with varying immune-suppressive properties were screened. Seven compounds neither suppressed nor enhanced the respiratory burst; five reproducibly suppressed global ROS production, but with varying potencies: benzo[a]pyrene, 17β-estradiol, lead acetate, methoxychlor, and phenanthrene. These five compounds have all previously been reported as immunosuppressive in mammalian innate immunity assays. To evaluate whether the suppression of ROS by these compounds was a result of decreased immune cell numbers, flow cytometry with transgenic zebrafish larvae was used to count the numbers of neutrophils and macrophages after chemical exposure. With this assay, benzo[a]pyrene was found to be the only chemical that induced a change in the number of immune cells by increasing macrophage but not neutrophil numbers. Taken together, this work demonstrates the utility of zebrafish larvae as a vertebrate model for identifying compounds that impact innate immune function at non-teratogenic levels and validates measuring ROS production and phagocyte numbers as metrics for monitoring how xenobiotic exposure alters the innate immune system.

Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility through Gene-Environment Interactions

Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, characterized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and even behavior across the entire body. The mechanisms of endocrine disruption involve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin by summarizing how the biology of EDCs has implications for genetically diverse populations. We then describe how gene-environment interactions (GxE) across the complex pathways of endocrine signaling could lead to differences in susceptibility. We survey examples in the literature of individual susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding the exceedingly complex thyroid pathway. Following a discussion of experimental designs to better identify and study GxE across EDCs, we present a case study of a high-throughput screening signal of putative GxE within known endocrine disruptors. We conclude with a call for further, deeper analysis of the EDCs, particularly the thyroid disruptors, to identify if these chemicals participate in GxE leading to differences in susceptibility.

Shedding new light on early sex determination in zebrafish

In contrast to established zebrafish gene annotations, the question of sex determination has still not been conclusively clarified for developing zebrafish, Danio rerio, larvae, 28 dpf or earlier. Recent studies indicate polygenic sex determination (PSD), with the genes being distributed throughout the genome. Early genetic markers of sex in zebrafish help unravel co-founding sex-related differences to apply to human health and environmental toxicity studies. A qPCR-based method was developed for six genes: cytochrome P450, family 17, subfamily A, polypeptide 1 (cyp17a1); cytochrome P450, family 19, subfamily A, polypeptide 1a (cyp19a1a); cytochrome P450, family 19, subfamily A, polypeptides 1b (cyp19a1b); vitellogenin 1 (vtg1); nuclear receptor subfamily 0, group B, member 1 (nr0b1), sry (sex-determining region Y)-box 9b (sox9b) and actin, beta 1 (actb1), the reference gene. Sry-box 9a (Sox9a), insulin-like growth factor 3 (igf3) and double sex and mab-3 related transcription factor 1 (dmrt1), which are also known to be associated with sex determination, were used in gene expression tests. Additionally, Next-Generation-Sequencing (NGS) sequenced the genome of two adult female and male and two juveniles. PCR analysis of adult zebrafish revealed sex-specific expression of cyp17a1, cyp19a1a, vtg1, igf3 and dmrt1, the first four strongly expressed in female zebrafish and the last one highly expressed in male conspecifics. From NGS, nine female and four male-fated genes were selected as novel for assessing zebrafish sex, 28 dpf. Differences in transcriptomes allowed allocation of sex-specific genes also expressed in juvenile zebrafish.

Gene-environment interactions: aligning birth defects research with complex etiology

Developmental biologists rely on genetics-based approaches to understand the origins of congenital abnormalities. Recent advancements in genomics have made it easier than ever to investigate the relationship between genes and disease. However, nonsyndromic birth defects often exhibit non-Mendelian inheritance, incomplete penetrance or variable expressivity. The discordance between genotype and phenotype indicates that extrinsic factors frequently impact the severity of genetic disorders and vice versa. Overlooking gene-environment interactions in birth defect etiology limits our ability to identify and eliminate avoidable risks. We present mouse models of sonic hedgehog signaling and craniofacial malformations to illustrate both the importance of and current challenges in resolving gene-environment interactions in birth defects. We then prescribe approaches for overcoming these challenges, including use of genetically tractable and environmentally responsive in vitro systems. Combining emerging technologies with molecular genetics and traditional animal models promises to advance our understanding of birth defect etiology and improve the identification and protection of vulnerable populations.

Casting a wide net: use of diverse model organisms to advance toxicology

Toxicology - the study of how chemicals interact with biological systems - has clear relevance to human health and disease. Persistent exposure to natural and synthetic chemicals is an unavoidable part of living on our planet; yet, we understand very little about the effects of exposure to the vast majority of chemicals. While epidemiological studies can provide strong statistical inference linking chemical exposure to disease, research in model systems is essential to elucidate the mechanisms of action and to predict outcomes. Most research in toxicology utilizes a handful of mammalian models that represent a few distinct branches of the evolutionary tree. This narrow focus constrains the understanding of chemical-induced disease processes and systems that have evolved in response to exposures. We advocate for casting a wider net in environmental toxicology research to utilize diverse model systems, including zebrafish, and perform more mechanistic studies of cellular responses to chemical exposures to shift the perception of toxicology as an applied science to that of a basic science. This more-inclusive perspective will enrich the field and should remain central to research on chemical-induced disease.

Potential Health Risks Linked to Emerging Contaminants in Major Rivers and Treated Waters

The presence of endocrine-disrupting chemicals (EDCs) in our local waterways is becoming an increasing threat to the surrounding population. These compounds and their degradation products (found in pesticides, herbicides, and plastic waste) are known to interfere with a range of biological functions from reproduction to differentiation. To better understand these effects, we used an in silico ontological pathway analysis to identify the genes affected by the most commonly detected EDCs in large river water supplies, which we grouped together based on four common functions: Organismal injuries, cell death, cancer, and behavior. In addition to EDCs, we included the opioid buprenorphine in our study, as this similar ecological threat has become increasingly detected in river water supplies. Through the identification of the pleiotropic biological effects associated with both the acute and chronic exposure to EDCs and opioids in local water supplies, our results highlight a serious health threat worthy of additional investigations with a potential emphasis on the effects linked to increased DNA damage.

Development of a Zebrafish S1500+ Sentinel Gene Set for High-Throughput Transcriptomics

Sentinel gene sets have been developed with the purpose of maximizing the information from targeted transcriptomic platforms. We recently described the development of an S1500+ sentinel gene set, which was built for the human transcriptome, utilizing a data- and knowledge-driven hybrid approach to select a small subset of genes that optimally capture transcriptional diversity, correlation with other genes based on large-scale expression profiling, and known pathway annotation within the human genome. While this detailed bioinformatics approach for gene selection can in principle be applied to other species, the reliability of the resulting gene set depends on availability of a large body of transcriptomics data. For the model organism zebrafish, we aimed to create a similar sentinel gene set (Zf S1500+ gene set); however, there is insufficient standardized expression data in the public domain to train the gene correlation model. Therefore, our strategy was to use human-zebrafish ortholog mapping of the human S1500+ genes and nominations from experts in the zebrafish scientific community. In this study, we present the bioinformatics curation and refinement process to produce the final Zf S1500+ gene set, explore whole transcriptome extrapolation using this gene set, and assess pathway-level inference. This gene set will add value to targeted high-throughput transcriptomics in zebrafish for toxicogenomic screening and other research domains.

Taking a closer look at whole organisms

By enabling researchers to image whole zebrafish with cellular resolution, X-ray histotomography will improve our understanding of the biological differences between individuals of the same species.

Use of Genome Editing Tools in Environmental Health Research

The nature and types of genome editing tools are rapidly expanding and becoming increasingly incorporated into research efforts aimed at understanding human disease. The majority of research involving genome editing has been driven by medical research, with a limited but increasing number of studies currently published in the field of environmental health and toxicology. This review aims to address this research gap by providing a high-level summary of current genome editing techniques and presenting examples of how some of these techniques have been used toxicologically to evaluate environmental exposure-induced disease. Specific strategies surrounding the evaluation of hazardous chemicals, chemical mechanism of action / adverse outcome pathways, and inter-individual response variability are also discussed to aid in the translation of genome editing methods towards toxicological and environmental health research.

Fishing forward and reverse: Advances in zebrafish phenomics

Understanding how the genome instructs the phenotypic characteristics of an organism is one of the major scientific endeavors of our time. Advances in genetics have progressively deciphered the inheritance, identity and biological relevance of genetically encoded information, contributing to the rise of several, complementary omic disciplines. One of them is phenomics, an emergent area of biology dedicated to the systematic multi-scale analysis of phenotypic traits. This discipline provides valuable gene function information to the rapidly evolving field of genetics. Current molecular tools enable genome-wide analyses that link gene sequence to function in multi-cellular organisms, illuminating the genome-phenome relationship. Among vertebrates, zebrafish has emerged as an outstanding model organism for high-throughput phenotyping and modeling of human disorders. Advances in both systematic mutagenesis and phenotypic analyses of embryonic and post-embryonic stages in zebrafish have revealed the function of a valuable collection of genes and the general structure of several complex traits. In this review, we summarize multiple large-scale genetic efforts addressing parental, embryonic, and adult phenotyping in the zebrafish. The genetic and quantitative tools available in the zebrafish model, coupled with the broad spectrum of phenotypes that can be assayed, make it a powerful model for phenomics, well suited for the dissection of genotype-phenotype associations in development, physiology, health and disease.

Characterizing sources of variability in zebrafish embryo screening protocols

There is a need for fast, efficient, and cost-effective hazard identification and characterization of chemical hazards. This need is generating increased interest in the use of zebrafish embryos as both a screening tool and an alternative to mammalian test methods. A Collaborative Workshop on Aquatic Models and 21st Century Toxicology identified the lack of appropriate and consistent testing protocols as a challenge to the broader application of the zebrafish embryo model. The National Toxicology Program established the Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) initiative to address the lack of consistent testing guidelines and identify sources of variability for zebrafish-based assays. This report summarizes initial SEAZIT information-gathering efforts. Investigators in academic, government, and industry laboratories that routinely use zebrafish embryos for chemical toxicity testing were asked about their husbandry practices and standard protocols. Information was collected about protocol components including zebrafish strains, feed, system water, disease surveillance, embryo exposure conditions, and endpoints. Literature was reviewed to assess issues raised by the investigators. Interviews revealed substantial variability across design parameters, data collected, and analysis procedures. The presence of the chorion and renewal of exposure media (static versus static-renewal) were identified as design parameters that could potentially influence study outcomes and should be investigated further with studies to determine chemical uptake from treatment solution into embryos. The information gathered in this effort provides a basis for future SEAZIT activities to promote more consistent practices among researchers using zebrafish embryos for toxicity evaluation.