Gene by Environment Interactions reveal new regulatory aspects of signaling network plasticity

Phenotypes can change during exposure to different environments through the regulation of signaling pathways that operate in integrated networks. How signaling networks produce different phenotypes in different settings is not fully understood. Here, Gene by Environment Interactions (GEIs) were used to explore the regulatory network that controls filamentous/invasive growth in the yeast Saccharomyces cerevisiae. GEI analysis revealed that the regulation of invasive growth is decentralized and varies extensively across environments. Different regulatory pathways were critical or dispensable depending on the environment, microenvironment, or time point tested, and the pathway that made the strongest contribution changed depending on the environment. Some regulators even showed conditional role reversals. Ranking pathways’ roles across environments revealed an under-appreciated pathway (OPI1) as the single strongest regulator among the major pathways tested (RAS, RIM101, and MAPK). One mechanism that may explain the high degree of regulatory plasticity observed was conditional pathway interactions, such as conditional redundancy and conditional cross-pathway regulation. Another mechanism was that different pathways conditionally and differentially regulated gene expression, such as target genes that control separate cell adhesion mechanisms (FLO11 and SFG1). An exception to decentralized regulation of invasive growth was that morphogenetic changes (cell elongation and budding pattern) were primarily regulated by one pathway (MAPK). GEI analysis also uncovered a round-cell invasion phenotype. Our work suggests that GEI analysis is a simple and powerful approach to define the regulatory basis of complex phenotypes and may be applicable to many systems.

Prenatal Maternal Stress From a Natural Disaster and Hippocampal Volumes: Gene-by-Environment Interactions in Young Adolescents From Project Ice Storm

Gene-by-environment interactions influence brain development from conception to adulthood. In particular, the prenatal period is a window of vulnerability for the interplay between environmental and genetic factors to influence brain development. Rodent and human research demonstrates that prenatal maternal stress (PNMS) alters hippocampal volumes. Although PNMS affects hippocampal size on average, similar degrees of PNMS lead to different effects in different individuals. This differential susceptibility to the effects of PNMS may be due to genetic variants. Hence, we investigated the role of genetic variants of two SNPs that are candidates to moderate the effects of PNMS on hippocampal volume: COMT (rs4680) and BDNF (rs6265). To investigate this, we assessed 53 children who were in utero during the January 1998 Quebec ice storm. In June 1998 their mothers responded to questionnaires about their objective, cognitive, and subjective levels of stress from the ice storm. When children were 11 1/2 years old, T1-weighted structural magnetic resonance imaging (MRI) scans were obtained using a 3T scanner and analyzed to determine hippocampal volumes. We collected and genotyped the children’s saliva DNA. Moderation analyses were conducted to determine whether either or both of the SNPs moderate the effect of PNMS on hippocampal volumes. We found that objective hardship was associated with right hippocampal volume in girls, and that the BDNF and COMT genotypes were associated with left hippocampal volume in boys and girls. In addition, SNPs located on COMT moderated the effect of maternal objective distress in boys, and subjective distress in girls, on both right hippocampal volume. Thus, we conclude that an individual’s genotype alters their susceptibility to the effects of PNMS.

Strain and sex dependent effects of isolation housing relative to environmental enrichment on operant sensation seeking in mice

Sensation seeking is a multidimensional phenotype that predicts the development of drug addiction in humans and addiction-like drug seeking in rodents. Several lines of evidence suggest that chronic stress increases sensation seeking and addiction-like drug seeking through common genetic mechanisms. Discovery and characterization of these mechanisms would reveal how chronic stress interacts with the genome to influence sensation seeking and how drugs of abuse hijack these fundamental reward mechanisms to drive addiction. To this end, we tested the hypothesis that chronic isolation housing stress (relative to environmental enrichment) influences operant sensation seeking as a function of strain, sex, or their interaction. To determine if the BXD recombinant inbred panel could be used to identify genetic and epigenetic mechanisms underlying any identified gene-by-environment interactions, we used mice from the two BXD founder strains. Following 10 weeks of differential housing, we assessed operant sensation seeking using several reinforcement schedules. The primary finding from this study was that DBA/2J but not C57BL/6J mice were significantly vulnerable to an isolation-induced increase (relative to environmental enrichment) in sensation seeking during extinction when the sensory reward was no longer available; this effect was significantly more robust in females. These data reveal a previously unknown isolation-induced effect on extinction of operant sensation seeking that is sex-dependent, addiction-relevant, and that can be dissected using the BXD recombinant inbred panel.

Estimating the Additive Heritability of Historiometric Eminence in a Super-Pedigree Comprised of Four Prominent Families

By merging analytical approaches from the fields of historiometrics and behavior genetics, a social pedigree-based estimate of the heritability of eminence is generated. Eminent individuals are identified using the Pantheon dataset. A single super-pedigree, comprised of four prominent and interrelated families (including the Wedgwood–Darwin, Arnold–Huxley, Keynes-Baha’u’lláh, and Benn-Rutherford pedigrees) is assembled, containing 30 eminent individuals out of 301 in total. Each eminent individual in the super-pedigree is assigned a relative measure of historical eminence (scaled from 1 to 100) with noneminent individuals assigned a score of 0. Utilizing a Bayesian pedigree-based heritability estimation procedure employing an informed prior, an additive heritability of eminence of .507 (95% CI [.434, .578]) was found. The finding that eminence is additively heritable is consistent with expectations from behavior-genetic studies of factors that are thought to underlie extraordinary accomplishment, which indicate that they are substantially additively heritable. Owing to the limited types of intermarriage present in the data, it was not possible to estimate the impact of nonadditive genetic contributions to heritability. Gene-by-environment interactions could not be estimated in the present analysis either; therefore, the finding that eminence is simply a function of additive genetic and nonshared environmental variance should be interpreted cautiously.

Old data and friends improve with age: Advancements with the updated tools of GeneNetwork

Understanding gene-by-environment interactions is important across biology, particularly behaviour. Families of isogenic strains are excellently placed, as the same genome can be tested in multiple environments. The BXD's recent expansion to 140 strains makes them the largest family of murine isogenic genomes, and therefore give great power to detect QTL. Indefinite reproducible genometypes can be leveraged; old data can be reanalysed with emerging tools to produce novel biological insights. To highlight the importance of reanalyses, we obtained drug- and behavioural-phenotypes from Philip et al. 2010, and reanalysed their data with new genotypes from sequencing, and new models (GEMMA and R/qtl2). We discover QTL on chromosomes 3, 5, 9, 11, and 14, not found in the original study. We narrowed down the candidate genes based on their ability to alter gene expression and/or protein function, using cis-eQTL analysis, and variants predicted to be deleterious. Co-expression analysis ('gene friends') and human PheWAS were used to further narrow candidates. Prominent candidate genes include: Slitrk6 in a Chr 14 QTL for locomotion in the center of an open field, we show to be part of a coexpression network involved in voluntary movement, and association with neuropsychiatric phenotypes in PheWAS; and Cdk14, one of only 3 genes in a Chr 5 QTL for handling induced convulsions after ethanol treatment, that is regulated by the anticonvulsant drug valproic acid. By using families of isogenic strains, we can reuse and reanalyse data to discover novel and highly plausible candidate genes involved in response to the environment.

MeSCoT: The tool for quantitative trait simulation through the mechanistic modelling of genes’ regulatory interactions

This work represents a novel mechanistic approach to simulate and study genomic networks with accompanying regulatory interactions and complex mechanisms of quantitative trait formation. The approach implemented in MeSCoT software is conceptually based on the omnigenic genetic model of quantitative (complex) trait, and closely imitates the basic in vivo mechanisms of quantitative trait realization. The software provides a framework to study molecular mechanisms of gene-by-gene and gene-by-environment interactions underlying quantitative trait’s realization and allows detailed mechanistic studies of impact of genetic and phenotypic variance on gene regulation. MeSCoT performs a detailed simulation of genes’ regulatory interactions for variable genomic architectures, and generates complete set of transcriptional and translational data together with simulated quantitative trait values. Such data provide opportunities to study, for example, verification of novel statistical methods aiming to integrate intermediate phenotypes together with final phenotype in quantitative genetic analyses, or to investigate novel approaches for exploiting gene-by-gene and gene-by-environment interactions.

A reaction norm perspective on reproducibility

Reproducibility in biomedical research, and more specifically in preclinical animal research, has been seriously questioned. Several cases of spectacular failures to replicate findings published in the primary scientific literature have led to a perceived reproducibility crisis. Diverse threats to reproducibility have been proposed, including lack of scientific rigour, low statistical power, publication bias, analytical flexibility and fraud. An important aspect that is generally overlooked is the lack of external validity caused by rigorous standardization of both the animals and the environment. Here, we argue that a reaction norm approach to phenotypic variation, acknowledging gene-by-environment interactions, can help us seeing reproducibility of animal experiments in a new light. We illustrate how dominating environmental effects can affect inference and effect size estimates of studies and how elimination of dominant factors through standardization affects the nature of the expected phenotype variation through the reaction norms of small effect. Finally, we discuss the consequences of reaction norms of small effect for statistical analysis, specifically for random effect latent variable models and the random lab model.

Characterizing gene expression responses to biomechanical strain in an in vitro model of osteoarthritis

Osteoarthritis (OA) is a common chronic degenerative joint disease affecting articular cartilage and underlying bone. Both genetic and environmental factors appear to contribute to the development of this disease. Specifically, pathological levels of biomechanical stress on joints play a notable role in disease initiation and progression. Population-level gene expression studies of cartilage cells experiencing biomechanical stress may uncover gene-by-environment interactions relevant to OA and human joint health. To build a foundation for such studies, we applied differentiation protocols to develop an in vitro system of chondrogenic cell lines (iPSC-chondrocytes). We characterized gene regulatory responses of three human iPSC-chondrocyte lines to cyclic tensile strain treatment. We measured the contribution of biological and technical factors to gene expression variation in this system and, even in this small sample, found several genes that exhibit inter-individual expression differences in response to mechanical strain, including genes previously implicated in OA. Expanding this system to include iPSC-chondrocytes from a larger number of individuals will allow us to characterize and better understand gene-by-environment interactions related to OA and joint health.

Integrative phenotypic and genomic analyses reveal strain-dependent responses to acute ozone exposure and their associations with airway macrophage transcriptional activity

Acute ozone (O3) exposure is associated with multiple adverse cardiorespiratory outcomes, the severity of which varies across human populations and rodent models from diverse genetic backgrounds. However, molecular determinants of response, including biomarkers that distinguish which individuals will develop more severe injury and inflammation (i.e., high responders), are poorly characterized. Here, we exposed adult, female and male mice from 6 strains, including 5 Collaborative Cross (CC) strains, to filtered air (FA) or 2 ppm O3 for 3 hours, and measured several inflammatory and injury parameters 21 hours later. Additionally, we collected airway macrophages and performed RNA-seq analysis to investigate influences of strain, treatment, and strain-by-treatment interactions on gene expression as well as transcriptional correlates of lung phenotypes. Animals exposed to O3 developed airway neutrophilia and lung injury, with varying degrees of severity. We identified many genes that were altered by O3 exposure across all strains, and examination of genes whose expression was influenced by strain-by-treatment interactions revealed prominent differences in response between the CC017/Unc and CC003/Unc strains, which were low- and high-responders, respectively (as measured by cellular inflammation and injury). Further investigation of this contrast indicated that baseline gene expression differences likely contribute to their divergent post-O3 exposure transcriptional responses. We also observed alterations in chromatin accessibility that differed by strain and with strain-by-treatment interactions, lending further plausibility that baseline differences can modulate post-exposure responses. Together, these results suggest that aspects of the respiratory response to O3 exposure may be mediated through altered airway macrophage transcriptional signatures, and further confirms the importance of gene-by-environment interactions in mediating differential responsiveness to environmental agents.