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Animals that accurately model human disease are invaluable in medical research, allowing a critical understanding of disease mechanisms, and the opportunity to evaluate the effect of therapeutic compounds in pre-clinical studies. Many types of animal models are used world-wide, with the most common being small laboratory animals, such as mice. However, rodents often do not faithfully replicate human disease, despite their predominant use in research. This discordancy is due in part to physiological differences, such as body size and longevity. In contrast, large animal models, including sheep, provide an alternative to mice for biomedical research due to their greater physiological parallels with humans. Completion of the full genome sequences of many species, and the advent of Next Generation Sequencing (NGS) technologies, means it is now feasible to screen large populations of domesticated animals for genetic variants that resemble human genetic diseases, and generate models that more accurately model rare human pathologies. In this review, we discuss the notion of using sheep as large animal models, and their advantages in modelling human genetic disease. We exemplify several existing naturally occurring ovine variants in genes that are orthologous to human disease genes, such as the Cln6 sheep model for Batten disease. These, and other sheep models, have contributed significantly to our understanding of the relevant human disease process, in addition to providing opportunities to trial new therapies in animals with similar body and organ size to humans. Therefore sheep are a significant species with respect to the modelling of rare genetic human disease, which we summarize in this review.
Arrhythmogenic cardiomyopathy has been clinically defined since the 1980s and causes right or biventricular cardiomyopathy associated with ventricular arrhythmia. Although it is a rare cardiac disease, it is responsible for a significant proportion of sudden cardiac deaths, especially in athletes. The majority of patients with arrhythmogenic cardiomyopathy carry one or more genetic variants in desmosomal genes. In the 1990s, several knockout mouse models of genes encoding for desmosomal proteins involved in cell-cell adhesion revealed for the first time embryonic lethality due to cardiac defects. Influenced by these initial discoveries in mice, arrhythmogenic cardiomyopathy received an increasing interest in human cardiovascular genetics, leading to the discovery of mutations initially in desmosomal genes and later on in more than 25 different genes. Of note, even in the clinic, routine genetic diagnostics are important for risk prediction of patients and their relatives with arrhythmogenic cardiomyopathy. Based on improvements in genetic animal engineering, different transgenic, knock-in, or cardiac-specific knockout animal models for desmosomal and nondesmosomal proteins have been generated, leading to important discoveries in this field. Here, we present an overview about the existing animal models of arrhythmogenic cardiomyopathy with a focus on the underlying pathomechanism and its importance for understanding of this disease. Prospectively, novel mechanistic insights gained from the whole animal, organ, tissue, cellular, and molecular levels will lead to the development of efficient personalized therapies for treatment of arrhythmogenic cardiomyopathy.
Gene targeting in cultured embryonic stem cells permits the generation of mice with a desired alteration in a chosen target gene. Application of this procedure to create mouse models of human diseases is revealing the innate complexity of diseases normally ascribed to single gene defects. Modeling human diseases that are known to be multigenic in origin and are markedly influenced by environmental factors is potentially even more revealing.
Experimental animal models are extremely valuable for the study of human diseases, especially those with underlying genetic components. The exploitation of various animal models, from fruitflies to mice, has led to major advances in our understanding of the etiologies of many diseases, including cancer. Cutaneous malignant melanoma is a form of cancer for which both environmental insult (i.e., UV) and hereditary predisposition are major causative factors. Fish melanoma models have been used in studies of both spontaneous and induced melanoma formation. Genetic hybrids between platyfish and swordtails, different species of the genus Xiphophorus, have been studied since the 1920s to identify genetic determinants of pigmentation and melanoma formation. Recently, transgenesis has been used to develop zebrafish and medaka models for melanoma research. This review will provide a historical perspective on the use of fish models in melanoma research, and an updated summary of current and prospective studies using these unique experimental systems.
Hypertension is a complex trait that has been studied extensively for genetic contributions of the nuclear genome. We examined mitochondrial genomes of the hypertensive strains: the Dahl Salt-Sensitive (S) rat, the Spontaneously Hypertensive Rat (SHR), and the Albino Surgery (AS) rat, and the relatively normotensive strains: the Dahl Salt-Resistant (R) rat, the Milan Normotensive Strain (MNS), and the Lewis rat (LEW). These strains were used previously for linkage analysis for blood pressure (BP) in our laboratory. The results provide evidence to suggest that variations in the mitochondrial genome do not account for observed differences in blood pressure between the S and R rats. However, variants were detected among the mitochondrial genomes of the various hypertensive strains, S, SHR, and AS, and also among the normotensive strains R, MNS, and LEW. A total of 115, 114, 106, 106, and 16 variations in mtDNA were observed between the comparisons S versus LEW, S versus MNS, S versus SHR, S versus AS, and SHR versus AS, respectively. Among the 13 genes coding for proteins of the electron transport chain, 8 genes had nonsynonymous variations between S, LEW, MNS, SHR, and AS. The lack of any sequence variants between the mitochondrial genomes of S and R rats provides conclusive evidence that divergence in blood pressure between these two inbred strains is exclusively programmed through their nuclear genomes. The variations detected among the various hypertensive strains provides the basis to construct conplastic strains and further evaluate the effects of these variants on hypertension and associated phenotypes.
Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.
The Cancer Genome Atlas (TCGA) provides a rich resource that can be used to understand how genes interact in cancer cells and has collected RNA-Seq gene expression data for many types of human cancer. However, mining the data to uncover the hidden gene-interaction patterns remains a challenge. Gaussian graphical model (GGM) is often used to learn genetic networks because it defines an undirected graphical structure, revealing the conditional dependences of genes. In this study, we focus on inferring gene interactions in 15 specific types of human cancer using RNA-Seq expression data and GGM with graphical lasso. We take advantage of the corresponding Kyoto Encyclopedia of Genes and Genomes pathway maps to define the subsets of related genes. RNA-Seq expression levels of the subsets of genes in solid cancerous tumor and normal tissues were extracted from TCGA. The gene expression data sets were cleaned and formatted, and the genetic network corresponding to each cancer type was then inferred using GGM with graphical lasso. The inferred networks reveal stable conditional dependences among the genes at the expression level and confirm the essential roles played by the genes that encode proteins involved in the two key signaling pathway phosphoinositide 3-kinase (PI3K)/AKT/mTOR and Ras/Raf/MEK/ERK in human carcinogenesis. These stable dependences elucidate the expression level interactions among the genes that are implicated in many different human cancers. The inferred genetic networks were examined to further identify and characterize a collection of gene interactions that are unique to cancer. The cross-cancer genetic interactions revealed from our study provide another set of knowledge for cancer biologists to propose strong hypotheses, so further biological investigations can be conducted effectively.
Murine models for multiple myeloma (MM) are often used to investigate pathobiology of multiple myeloma and disease progression. Unlike transgenic mice models, where it is known which oncogene is driving MM disease, the somatic aberrations of spontaneous syngeneic 5T models of MM have not yet been reported. Here, we analyzed the copy-number alterations (CNA) and mutational landscape of 5T2, 5T33vv and 5TGM1 murine MM models using whole-genome and whole-exome sequencing. Forty four percent of the genome of 5T2 cells is affected by CNAs while this was only 11% and 17% for 5T33vv and 5TGM1 cells, respectively. We found that up to 69% of the genes linked to gain of 1q or deletion of 13q in MM patients are present as respectively gains in 5T2 cells or deletions in 5T33 and 5TGM1 cells. Exome sequencing furthermore revealed mutations of genes involved in RAS/MAPK, PI3K/AKT1 and JAK/STAT signaling, DNA damage response, cell cycle, epigenetic regulation and extracellular matrix organization. We observed a statistically significant overlap of genes mutated in the 5T models and MM patients. Overall, the genetic landscape of the 5T models is heterogeneous with a high number of aberrations involving genes in various multiple myeloma-related pathways.
Obesity has been recognized as one of the most important risk factors for a variety of chronic diseases, such as diabetes, hypertension/cardiovascular diseases, steatosis/hepatitis, and cancer. Keishibukuryogan (KBG, Gui Zhi Fu Ling Wan in Chinese) is a traditional Chinese/Japanese (Kampo) medicine that has been known to improve blood circulation and is also known for its anti-inflammatory or scavenging effect. In this study, we evaluated the effect of KBG in two distinct rodent models of obesity driven by either a genetic (SHR/NDmcr-cp rat model) or dietary (high-fat diet-induced mouse obesity model) mechanism. Although there was no significant effect on the body composition in either the SHR rat or the DIO mouse models, KBG treatment significantly decreased the serum level of leptin and liver TG level in the DIO mouse, but not in the SHR rat model. Furthermore, a lower fat deposition in liver and a smaller size of adipocytes in white adipose tissue were observed in the DIO mice treated with KBG. Importantly, we further found downregulation of genes involved in lipid metabolism in the KBG-treated liver, along with decreased liver TG and cholesterol level. Our present data experimentally support in fact that KBG can be an attractive Kampo medicine to improve obese status through a regulation of systemic leptin level and/or lipid metabolism.
Fishes of the genus Xiphophorus (platyfishes and swordtails) are small, internally fertilizing, livebearing, and derived from freshwater habitats in Mexico, Guatemala, Belize, and Honduras. Scientists have used these fishes in cancer research studies for more than 70 yr. The genus is presently composed of 22 species that are quite divergent in their external morphology. Most cancer studies using Xiphophorus use hybrids, which can be easily produced by artificial insemination. Phenotypic traits, such as macromelanophore pigment patterns, are often drastically altered as a result of lack of gene regulation within hybrid fishes. These fish can develop large exophytic melanomas as a result of upregulated expression of these pigment patterns. Because backcross hybrid fish are susceptible to the development of melanoma and other neoplasms, they can be subjected to potentially deleterious chemical and physical agents. It is thus possible to use gene mapping and cloning methodologies to identify and characterize oncogenes and tumor suppressors implicated in spontaneous or induced neoplasia. This article reviews the history of cancer research using Xiphophorus and recent developments regarding DNA repair capabilities, mapping, and cloning of candidate genes involved in neoplastic phenotypes. The particular genetic complexity of melanoma in these fishes is analyzed and reviewed.
Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies' distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene flow among populations at a regional scale (<0.01), except for the Yucatan Peninsula, and the northern portion of the Pacific Coast. Our analyses suggested that the Isthmus of Tehuantepec is an effective barrier isolating southern populations. Our SDM results indicate that environmental characteristics in the Balsas-Jalisco region, a potential center of domestication, were suitable for the presence of sororia during the Holocene.
Autosomal dominant sleep-related hypermotor epilepsy (ADSHE; previously autosomal dominant nocturnal frontal lobe epilepsy, ADNFLE), originally reported in 1994, was the first distinct genetic epilepsy shown to be caused by CHNRA4 mutation. In the past two decades, we have identified several functional abnormalities of mutant ion channels and their associated transmissions using several experiments involving single-cell and genetic animal (rodent) models. Currently, epileptologists understand that functional abnormalities underlying epileptogenesis/ictogenesis in humans and rodents are more complicated than previously believed and that the function of mutant molecules alone cannot contribute to the development of epileptogenesis/ictogenesis but play important roles in the development of epileptogenesis/ictogenesis through formation of abnormalities in various other transmission systems before epilepsy onset. Based on our recent findings using genetic rat ADSHE models, harbouring Chrna4 mutant, corresponding to human S284L-mutant CRHNA4, this review proposes a hypothesis associated with tripartite synaptic transmission in ADSHE pathomechanisms induced by mutant ACh receptors. LINKED ARTICLES: This article is part of a themed issue on Building Bridges in Neuropharmacology. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.8/issuetoc.
Tauopathy refers to a group of progressive neurodegenerative diseases, including frontotemporal lobar degeneration and Alzheimer's disease, which correlate with the malfunction of microtubule-associated protein Tau (MAPT) due to abnormal hyperphosphorylation, leading to the formation of intracellular aggregates in the brain. Despite extensive efforts to understand tauopathy and develop an efficient therapy, our knowledge is still far from complete. To find a solution for this group of devastating diseases, several animal models that mimic diverse disease phenotypes of tauopathy have been developed. Rodents are the dominating tauopathy models because of their similarity to humans and established disease lines, as well as experimental approaches. However, powerful genetic animal models using Drosophila, zebrafish, and C. elegans have also been developed for modeling tauopathy and have contributed to understanding the pathophysiology of tauopathy. The success of these models stems from the short lifespans, versatile genetic tools, real-time in-vivo imaging, low maintenance costs, and the capability for high-throughput screening. In this review, we summarize the main findings on mechanisms of tauopathy and discuss the current tauopathy models of these non-rodent genetic animals, highlighting their key advantages and limitations in tauopathy research.
One of the most important criteria for major depressive disorder in adults and in children and adolescents as well, is the loss of interest in or pleasure from typically enjoyable experiences or activities: anhedonia. Anxiety is frequently co-morbid with depression. We examined reward and anxiety in genetic animal models of childhood depression. Two different "depressed" lines were studied: the Flinders Sensitive Line (FSL) and their controls, Sprague-Dawley (SD) rats and the Wistar Kyoto (WKY) line and their controls, Wistar rats. Recently, we found that prepubertal rats (about 35 days old) from these lines exhibited increased immobility in the swim test, and abnormal social play observed after 24-h isolation. We hypothesized that FSL and WKY prepubertal rats will further show anhedonia in two different behavioral assays: the conditioned place preference test (CPP), examining the rewarding aspect of social interaction and the saccharin preference test. Behavior in the open field paradigm and freezing behavior in the CPP apparatus were also used as measures of anxiety. WKY, but not FSL prepubertal rats, consumed less of the saccharin solution compared to their control line. FSL, and WKY prepubertal rats found social interaction to be rewarding to a similar extent as their control lines, in the CPP test. Only the WKY rats showed anxiety in behavior in the open field and freezing behavior in the CPP paradigm. The results suggest that WKY prepubertal rats are anxious and sensitive to stress-induced anhedonia, while FSL prepubertal rats exhibit none of these symptoms.
Cancer complexity relies on the intracellular pleiotropy of oncogenes/tumor suppressors and in the strong interplay between tumors and micro- and macro-environments. Here we followed a reductionist approach, by analyzing the transcriptional adaptations induced by three oncogenes (RAS, MYC, and HDAC4) in an isogenic transformation process. Common pathways, in place of common genes became dysregulated. From our analysis it emerges that, during the process of transformation, tumor cells cultured in vitro prime some signaling pathways suitable for coping with the blood supply restriction, metabolic adaptations, infiltration of immune cells, and for acquiring the morphological plasticity needed during the metastatic phase. Finally, we identified two signatures of genes commonly regulated by the three oncogenes that successfully predict the outcome of patients affected by different cancer types. These results emphasize that, in spite of the heterogeneous mutational burden among different cancers and even within the same tumor, some common hubs do exist. Their location, at the intersection of the various signaling pathways, makes a therapeutic approach exploitable.
Copper is an essential cofactor of cytochrome c oxidase (CcO), the terminal enzyme of the mitochondrial respiratory chain. Inherited loss-of-function mutations in several genes encoding proteins required for copper delivery to CcO result in diminished CcO activity and severe pathologic conditions in affected infants. Copper supplementation restores CcO function in patient cells with mutations in two of these genes, COA6 and SCO2, suggesting a potential therapeutic approach. However, direct copper supplementation has not been therapeutically effective in human patients, underscoring the need to identify highly efficient copper transporting pharmacological agents. By using a candidate-based approach, we identified an investigational anticancer drug, elesclomol (ES), that rescues respiratory defects of COA6-deficient yeast cells by increasing mitochondrial copper content and restoring CcO activity. ES also rescues respiratory defects in other yeast mutants of copper metabolism, suggesting a broader applicability. Low nanomolar concentrations of ES reinstate copper-containing subunits of CcO in a zebrafish model of copper deficiency and in a series of copper-deficient mammalian cells, including those derived from a patient with SCO2 mutations. These findings reveal that ES can restore intracellular copper homeostasis by mimicking the function of missing transporters and chaperones of copper, and may have potential in treating human disorders of copper metabolism.
A major goal of population genetics is to quantitatively understand variation of genetic polymorphisms among individuals. The aggregated number of genotyped humans is currently on the order of millions of individuals, and existing methods do not scale to data of this size. To solve this problem, we developed TeraStructure, an algorithm to fit Bayesian models of genetic variation in structured human populations on tera-sample-sized data sets (1012 observed genotypes; for example, 1 million individuals at 1 million SNPs). TeraStructure is a scalable approach to Bayesian inference in which subsamples of markers are used to update an estimate of the latent population structure among individuals. We demonstrate that TeraStructure performs as well as existing methods on current globally sampled data, and we show using simulations that TeraStructure continues to be accurate and is the only method that can scale to tera-sample sizes.
Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.
We present a novel modification of genetic algorithm (GA) which determines personalized parameters of cardiomyocyte electrophysiology model based on set of experimental human action potential (AP) recorded at different heart rates. In order to find the steady state solution, the optimized algorithm performs simultaneous search in the parametric and slow variables spaces. We demonstrate that several GA modifications are required for effective convergence. Firstly, we used Cauchy mutation along a random direction in the parametric space. Secondly, relatively large number of elite organisms (6-10% of the population passed on to new generation) was required for effective convergence. Test runs with synthetic AP as input data indicate that algorithm error is low for high amplitude ionic currents (1.6±1.6% for IKr, 3.2±3.5% for IK1, 3.9±3.5% for INa, 8.2±6.3% for ICaL). Experimental signal-to-noise ratio above 28 dB was required for high quality GA performance. GA was validated against optical mapping recordings of human ventricular AP and mRNA expression profile of donor hearts. In particular, GA output parameters were rescaled proportionally to mRNA levels ratio between patients. We have demonstrated that mRNA-based models predict the AP waveform dependence on heart rate with high precision. The latter also provides a novel technique of model personalization that makes it possible to map gene expression profile to cardiac function.
Pre-clinical research and development relies heavily upon translationally valid models of disease. A major difficulty in understanding the biology of, and developing treatments for, rare disease is the lack of animal models. It is important that these models not only recapitulate the presentation of the disease in humans, but also that they share functionally equivalent underlying genetic causes. Nonhuman primates share physiological, anatomical, and behavioral similarities with humans resulting from close evolutionary relationships and high genetic homology. As the post-genomic era develops and next generation sequencing allows for the resequencing and screening of large populations of research animals, naturally occurring genetic variation in nonhuman primates with clinically relevant phenotypes is regularly emerging. Here we review nonhuman primate models of multiple rare genetic diseases with a focus on the similarities and differences in manifestation and etiologies across species. We discuss how these models are being developed and how they can offer new tools and opportunities for researchers interested in exploring novel therapeutics for these and other genetic diseases. Modeling human genetic diseases in translationally relevant nonhuman primates presents new prospects for development of therapeutics and a better understanding of rare diseases. The post-genomic era offers the opportunity for the discovery and further development of more models like those discussed here.
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