Environmental exposures and gene regulation in disease etiology

Health or disease is shaped for all individuals by interactions between their genes and environment. Exactly how the environment changes gene expression and how this can lead to disease are being explored in a fruitful new approach to environmental health research, representative studies of which are reviewed here. We searched Web of Science and references of relevant publications to understand the diversity of gene regulatory mechanisms affected by environmental exposures with disease implications. Pharmaceuticals, pesticides, air pollutants, industrial chemicals, heavy metals, hormones, nutrition, and behavior can change gene expression through a broad array of gene regulatory mechanisms. Furthermore, chemically induced changes in gene regulation are associated with serious and complex human diseases, including cancer, diabetes and obesity, infertility, respiratory diseases, allergies, and neurodegenerative disorders such as Parkinson and Alzheimer diseases. The reviewed studies indicate that genetic predisposition for disease is best predicted in the context of environmental exposures. And the genetic mechanisms investigated in these studies offer new avenues for risk assessment research. Finally, we are likely to witness dramatic improvements in human health, and reductions in medical costs, if environmental pollution is decreased.

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3. How behaviour develops

10.1093/actrade/9780198712152.003.0003 ◽

2017 ◽

Author(s):

Tristram D. Wyatt

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Natural Selection ◽

Phenotypic Plasticity ◽

Mate Choice ◽

Social Influences ◽

Future Generations ◽

Gene Frequencies ◽

Brain Gene Expression ◽

Genes And Environment

Behaviours evolve by natural selection. As genes influence how behaviours develop, selection on behaviour will alter gene frequencies in subsequent generations: genes that lead to successful behaviours in foraging, parental care, or mate choice, for example, will be represented in more individuals in future generations. If conditions change, then mutations of the genes that give rise to advantageous behaviours will be favoured by selection. ‘How behaviour develops’ explains that the environment is equally important: both genes and environment are intimately and interactively involved in behaviour development. Behavioural imprinting is also discussed along with co-opting genes, gene regulation, social influences on brain gene expression, phenotypic plasticity, and play.

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Gene Regulatory Mechanisms Underlying the Spatial and Temporal Regulation of Target-Dependent Gene Expression in Drosophila Neurons

PLoS Genetics ◽

10.1371/journal.pgen.1005754 ◽

2015 ◽

Vol 11 (12) ◽

pp. e1005754 ◽

Cited By ~ 4

Author(s):

Anthony J. E. Berndt ◽

Jonathan C. Y. Tang ◽

Marc S. Ridyard ◽

Tianshun Lian ◽

Kathleen Keatings ◽

...

Keyword(s):

Gene Expression ◽

Regulatory Mechanisms ◽

Temporal Regulation ◽

Gene Regulatory

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Regulation of spatial and temporal gene expression in an animal germline

10.1101/348425 ◽

2018 ◽

Cited By ~ 1

Author(s):

Asija Diag ◽

Marcel Schilling ◽

Filippos Klironomos ◽

Salah Ayoub ◽

Nikolaus Rajewsky

Keyword(s):

Gene Expression ◽

Regulatory Mechanisms ◽

Rna Expression ◽

Temporal Expression ◽

Temporal Gene Expression ◽

Cell Proliferation And Differentiation ◽

Proliferation And Differentiation ◽

Gene Regulatory ◽

Spatio Temporal

SUMMARYIn animal germlines, regulation of cell proliferation and differentiation is particularly important but poorly understood. Here, using a cryo-cut approach, we mapped RNA expression along the Caenorhabditis elegans germline and, using mutants, dissected gene regulatory mechanisms that control spatio-temporal expression. We detected, at near single-cell resolution, > 10,000 mRNAs, > 300 miRNAs and numerous novel miRNAs. Most RNAs were organized in distinct spatial patterns. Germline-specific miRNAs and their targets were co-localized. Moreover, we observed differential 3’ UTR isoform usage for hundreds of mRNAs. In tumorous gld-2 gld-1 mutants, gene expression was strongly perturbed. In particular, differential 3’ UTR usage was significantly impaired. We propose that PIE-1, a transcriptional repressor, functions to maintain spatial gene expression. Our data also suggest that cpsf-4 and fipp-1 control differential 3’ UTR usage for hundreds of genes. Finally, we constructed a “virtual gonad” enabling “virtual in situ hybridizations” and access to all data (https://shiny.mdc-berlin.de/spacegerm/).

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Predicting genotype-specific gene regulatory networks

10.1101/2021.01.18.427134 ◽

2021 ◽

Author(s):

Deborah Weighill ◽

Marouen Ben Guebila ◽

Kimberly Glass ◽

John Quackenbush ◽

John Platig

Keyword(s):

Gene Expression ◽

Gene Regulatory Network ◽

Gene Regulatory Networks ◽

Genetic Variants ◽

Regulatory Network ◽

Regulatory Networks ◽

Specific Gene ◽

Disease Etiology ◽

Gene Regulatory ◽

The Impact

AbstractThe majority of disease-associated genetic variants are thought to have regulatory effects, including the disruption of transcription factor (TF) binding and the alteration of downstream gene expression. Identifying how a person’s genotype affects their individual gene regulatory network has the potential to provide important insights into disease etiology and to enable improved genotype-specific disease risk assessments and treatments. However, the impact of genetic variants is generally not considered when constructing gene regulatory networks. To address this unmet need, we developed EGRET (Estimating the Genetic Regulatory Effect on TFs), which infers a genotype-specific gene regulatory network (GRN) for each individual in a study population by using message passing to integrate genotype-informed TF motif predictions - derived from individual genotype data, the predicted effects of variants on TF binding and gene expression, and TF motif predictions - with TF protein-protein interactions and gene expression. Comparing EGRET networks for two blood-derived cell lines identified genotype-associated cell-line specific regulatory differences which were subsequently validated using allele-specific expression, chromatin accessibility QTLs, and differential TF binding from ChIP-seq. In addition, EGRET GRNs for three cell types across 119 individuals captured regulatory differences associated with disease in a cell-type-specific manner. Our analyses demonstrate that EGRET networks can capture the impact of genetic variants on complex phenotypes, supporting a novel fine-scale stratification of individuals based on their genetic background. EGRET is available through the Network Zoo R package (netZooR v0.9; netzoo.github.io).

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An information theoretic treatment of sequence-to-expression modeling

10.1101/316752 ◽

2018 ◽

Author(s):

Farzaneh Khajouei ◽

Saurabh Sinha

Keyword(s):

Gene Regulation ◽

Transcription Factor ◽

Probability Distribution ◽

Experiment Design ◽

Regulatory Mechanisms ◽

Information Theoretic ◽

Novel Approach ◽

Reporter Assays ◽

Gene Regulatory ◽

Site Mutagenesis

AbstractStudying a gene’s regulatory mechanisms is a tedious process that involves identification of candidate regulators by transcription factor (TF) knockout or over-expression experiments, delineation of enhancers by reporter assays, and demonstration of direct TF influence by site mutagenesis, among other approaches. Such experiments are often chosen based on the biologist’s intuition, from several testable hypotheses. We pursue the goal of making this process systematic by using ideas from information theory to reason about experiments in gene regulation, in the hope of ultimately enabling rigorous experiment design strategies. For this, we make use of a state-of-the-art mathematical model of gene expression, which provides a way to formalize our current knowledge of cis- as well as trans-regulatory mechanisms of a gene. Ambiguities in such knowledge can be expressed as uncertainties in the model, which we capture formally by building an ensemble of plausible models that fit the existing data and defining a probability distribution over the ensemble. We then characterize the impact of a new experiment on our understanding of the gene’s regulation based on how the ensemble of plausible models and its probability distribution changes when challenged with results from that experiment. This allows us to assess the ‘value’ of the experiment retroactively as the reduction in entropy of the distribution (information gain) resulting from the experiment’s results. We fully formalize this novel approach to reasoning about gene regulation experiments and use it to evaluate a variety of perturbation experiments on two developmental genes of D. melanogaster. We also provide objective and ‘biologist-friendly’ descriptions of the information gained from each such experiment. The rigorously defined information theoretic approaches presented here can be used in the future to formulate systematic strategies for experiment design pertaining to studies of gene regulatory mechanisms.Author summaryIn-depth studies of gene regulatory mechanisms employ a variety of experimental approaches such as identifying a gene’s enhancer(s) and testing its variants through reporter assays, followed by transcription factor mis-expression or knockouts, site mutagenesis, etc. The biologist is often faced with the challenging problem of selecting the ideal next experiment to perform so that its results provide novel mechanistic insights, and has to rely on their intuition about what is currently known on the topic and which experiments may add to that knowledge. We seek to make this intuition-based process more systematic, by borrowing ideas from the mature statistical field of experiment design. Towards this goal, we use the language of mathematical models to formally describe what is known about a gene’s regulatory mechanisms, and how an experiment’s results enhance that knowledge. We use information theoretic ideas to assign a ‘value’ to an experiment as well as explain objectively what is learned from that experiment. We demonstrate use of this novel approach on two extensively studied developmental genes in fruitfly. We expect our work to lead to systematic strategies for selecting the most informative experiments in a study of gene regulation.

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Genome edited colorectal cancer organoid models reveal distinct microRNA activity patterns across different mutation profiles

10.1101/2021.12.13.472432 ◽

2021 ◽

Author(s):

Jonathan W Villanueva ◽

Lawrence Kwong ◽

Teng Han ◽

Salvador Alonso Martinez ◽

Fong Cheng Pan ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Genetically Modified ◽

Activity Patterns ◽

Expression Patterns ◽

Regulatory Mechanisms ◽

Oncogenic Mutations ◽

Gene Regulatory ◽

Insight Into

Somatic mutations drive colorectal cancer (CRC) by disrupting gene regulatory mechanisms. Distinct combinations of mutations can result in unique changes to regulatory mechanisms leading to variability in the efficacy of therapeutics. MicroRNAs are important regulators of gene expression, and their activity can be altered by oncogenic mutations. However, it is unknown how distinct combinations of CRC-risk mutations differentially affect microRNAs. Here, using genetically-modified mouse intestinal organoid (enteroid) models, we identify ten different modules of microRNA expression patterns across distinct combinations of mutations common in CRC. We also show that miR-24-3p, which is aberrant in genetically-modified mouse enteroids and human colonoids irrespective of mutational context, is a master regulator of gene expression in CRC. In follow-up experiments, we also demonstrate that miR-24 promotes CRC cell survival. These findings offer insight into the mechanisms that drive inter-tumor heterogeneity and highlight candidate microRNA therapeutic targets for the advancement of precision medicine for CRC.

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Epigenetic Mechanisms of HIV-1 Persistence

Vaccines ◽

10.3390/vaccines9050514 ◽

2021 ◽

Vol 9 (5) ◽

pp. 514

Author(s):

Roxane Verdikt ◽

Olivier Hernalsteens ◽

Carine Van Lint

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Rational Design ◽

Therapeutic Interventions ◽

Regulatory Mechanisms ◽

Viral Reservoir ◽

Epigenetic Mechanisms ◽

Latently Infected ◽

Hiv 1

Eradicating HIV-1 in infected individuals will not be possible without addressing the persistence of the virus in its multiple reservoirs. In this context, the molecular characterization of HIV-1 persistence is key for the development of rationalized therapeutic interventions. HIV-1 gene expression relies on the redundant and cooperative recruitment of cellular epigenetic machineries to cis-regulatory proviral regions. Furthermore, the complex repertoire of HIV-1 repression mechanisms varies depending on the nature of the viral reservoir, although, so far, few studies have addressed the specific regulatory mechanisms of HIV-1 persistence in other reservoirs than the well-studied latently infected CD4+ T cells. Here, we present an exhaustive and updated picture of the heterochromatinization of the HIV-1 promoter in its different reservoirs. We highlight the complexity, heterogeneity and dynamics of the epigenetic mechanisms of HIV-1 persistence, while discussing the importance of further understanding HIV-1 gene regulation for the rational design of novel HIV-1 cure strategies.

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Gene expression variability in human and chimpanzee populations share common determinants

10.1101/2020.06.11.146142 ◽

2020 ◽

Author(s):

Benjamin J. Fair ◽

Lauren E. Blake ◽

Abhishek Sarkar ◽

Bryan J. Pavlovic ◽

Claudia Cuevas ◽

...

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Comparative Analysis ◽

Individual Variation ◽

Disease Susceptibility ◽

Expression Data ◽

Cell Type ◽

Orthologous Genes ◽

Expression Variability ◽

Gene Regulatory

AbstractInter-individual variation in gene expression has been shown to be heritable and it is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

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Detecting shifts in gene regulatory networks during time-course experiments at single-time-point temporal resolution

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720015430027 ◽

2015 ◽

Vol 13 (05) ◽

pp. 1543002 ◽

Cited By ~ 3

Author(s):

Yoichi Takenaka ◽

Shigeto Seno ◽

Hideo Matsuda

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Time Course ◽

Diauxic Shift ◽

Gene Regulatory ◽

Gene Regulations ◽

Single Time Point ◽

Time Point

Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments.

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Mechanism of Gene Regulation by a Staphylococcus aureus Toxin

mBio ◽

10.1128/mbio.01579-16 ◽

2016 ◽

Vol 7 (5) ◽

Cited By ~ 14

Author(s):

Hwang-Soo Joo ◽

Som S. Chatterjee ◽

Amer E. Villaruz ◽

Seth W. Dickey ◽

Vee Y. Tan ◽

...

Keyword(s):

Gene Expression ◽

Staphylococcus Aureus ◽

Gene Regulation ◽

Toxin Production ◽

Bacterial Toxin ◽

Human Pathogen ◽

Bacterial Physiology ◽

Functional Specification ◽

Gene Regulatory ◽

Regulatory Functions

ABSTRACT The virulence of many bacterial pathogens, including the important human pathogen Staphylococcus aureus , depends on the secretion of frequently large amounts of toxins. Toxin production involves the need for the bacteria to make physiological adjustments for energy conservation. While toxins are primarily targets of gene regulation, such changes may be accomplished by regulatory functions of the toxins themselves. However, mechanisms by which toxins regulate gene expression have remained poorly understood. We show here that the staphylococcal phenol-soluble modulin (PSM) toxins have gene regulatory functions that, in particular, include inducing expression of their own transport system by direct interference with a GntR-type repressor protein. This capacity was most pronounced in PSMs with low cytolytic capacity, demonstrating functional specification among closely related members of that toxin family during evolution. Our study presents a molecular mechanism of gene regulation by a bacterial toxin that adapts bacterial physiology to enhanced toxin production. IMPORTANCE Toxins play a major role in many bacterial diseases. When toxins are produced during infection, the bacteria need to balance this energy-consuming task with other physiological processes. However, it has remained poorly understood how toxins can impact gene expression to trigger such adaptations. We found that specific members of a toxin family in the major human pathogen Staphylococcus aureus have evolved for gene regulatory purposes. These specific toxins interact with a DNA-binding regulator protein to enable production of the toxin export machinery and ascertain that the machinery is not expressed when toxins are not made and it is not needed. Our study gives mechanistic insight into how toxins may directly adjust bacterial physiology to times of toxin production during infection.

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