Steven P. Wilder

Direct quantitative trait locus mapping of mammalian metabolic phenotypes in diabetic and normoglycemic rat models

Characterizing the relationships between genomic and phenotypic variation is essential to understanding disease etiology. Information-dense data sets derived from pathophysiological, proteomic and transcriptomic profiling have been applied to map quantitative trait loci (QTLs). Metabolic traits, already used in QTL studies in plants, are essential phenotypes in mammalian genetics to define disease biomarkers. Using a complex mammalian system, here we show chromosomal mapping of untargeted plasma metabolic fingerprints derived from NMR spectroscopic analysis in a cross between diabetic and control rats. We propose candidate metabolites for the most significant QTLs. Metabolite profiling in congenic strains provided evidence of QTL replication. Linkage to a gut microbial metabolite (benzoate) can be explained by deletion of a uridine diphosphate glucuronosyltransferase. Mapping metabotypic QTLs provides a practical approach to understanding genome-phenotype relationships in mammals and may uncover deeper biological complexity, as extended genome (microbiome) perturbations that affect disease processes through transgenomic effects may influence QTL detection.

Phylometabonomic Patterns of Adaptation to High Fat Diet Feeding in Inbred Mice

Insulin resistance plays a central role in type 2 diabetes and obesity, which develop as a consequence of genetic and environmental factors. Dietary changes including high fat diet (HFD) feeding promotes insulin resistance in rodent models which present useful systems for studying interactions between genetic background and environmental influences contributing to disease susceptibility and progression. We applied a combination of classical physiological, biochemical and hormonal studies and plasma 1H NMR spectroscopy-based metabonomics to characterize the phenotypic and metabotypic consequences of HFD (40%) feeding in inbred mouse strains (C57BL/6, 129S6, BALB/c, DBA/2, C3H) frequently used in genetic studies. We showed the wide range of phenotypic and metabonomic adaptations to HFD across the five strains and the increased nutrigenomic predisposition of 129S6 and C57BL/6 to insulin resistance and obesity relative to the other strains. In contrast mice of the BALB/c and DBA/2 strains showed relative resistance to HFD-induced glucose intolerance and obesity. Hierarchical metabonomic clustering derived from 1H NMR spectral data of the strains provided a phylometabonomic classification of strain-specific metabolic features and differential responses to HFD which closely match SNP-based phylogenetic relationships between strains. Our results support the concept of genomic clustering of functionally related genes and provide important information for defining biological markers predicting spontaneous susceptibility to insulin resistance and pathological adaptations to fat feeding.

Subtle metabolic and liver gene transcriptional changes underlie diet-induced fatty liver susceptibility in insulin-resistant mice

Aims/hypothesisComplex changes in gene expression are associated with insulin resistance and non-alcoholic fatty liver disease (NAFLD) promoted by feeding a high-fat diet (HFD). We used functional genomic technologies to document molecular mechanisms associated with diet-induced NAFLD.Materials and MethodsMale 129S6 mice were fed a diet containing 40% fat (high-fat diet, HFD) for 15xa0weeks. Glucose tolerance, in vivo insulin secretion, plasma lipid profile and adiposity were determined. Plasma metabonomics and liver transcriptomics were used to identify changes in gene expression associated with HFD-induced NAFLD.ResultsIn HFD-fed mice, NAFLD and impaired glucose and lipid homeostasis were associated with increased hepatic transcription of genes involved in fatty acid uptake, intracellular transport, modification and elongation, whilst genes involved in beta-oxidation and lipoprotein secretion were, paradoxically, also upregulated. NAFLD developed despite strong and sustained downregulation of transcription of the gene encoding stearoyl-coenzyme A desaturase 1 (Scd1) and uncoordinated regulation of transcription of Scd1 and the gene encoding sterol regulatory element binding factor 1c (Srebf1c) transcription. Inflammatory mechanisms appeared to be stimulated by HFD.Conclusions/interpretationOur results provide an accurate representation of subtle changes in metabolic and gene expression regulation underlying disease-promoting and compensatory mechanisms, collectively contributing to diet-induced insulin resistance and NAFLD. They suggest that proposed models of NAFLD pathogenesis can be enriched with novel diet-reactive genes and disease mechanisms.

Polygenic Control of Idiopathic Generalized Epilepsy Phenotypes in the Genetic Absence Rats from Strasbourg (GAERS)

Summary:u2003 Purpose: Generalized nonconvulsive absence seizures are characterized by the occurrence of synchronous and bilateral spike‐and‐wave discharges (SWDs) on electroencephalographic recordings, concomitant with behavioral arrest. The GAERS (genetic absence rats from Strasbourg) strain, a well‐characterized inbred model for idiopathic generalized epilepsy, spontaneously develops EEG paroxysms that resemble those of typical absence seizures. The purpose of this study was to investigate the genetic control of SWD variables by using a combination of genetic analyses and electrophysiological measurements in an experimental cross derived from GAERS and Brown Norway (BN) rats.

Chromosomal Mapping of Genetic Loci Controlling Absence Epilepsy Phenotypes in the WAG-Rij Rat

Summary:u2002 Purpose: The WAG/Rij rat is among the most appropriate models for the study of spontaneous childhood absence epilepsy, without complex neurologic disorders that are associated with some mouse models for absence epilepsy. Previous studies have allowed the identification of distinct types of spike–wave discharges (SWDs) characterizing seizures in this strain. The purpose of this study was to investigate the genetic basis of electroencephalographic (EEG) properties of SWDs.

Nutrigenomics of High Fat Diet Induced Obesity in Mice Suggests Relationships between Susceptibility to Fatty Liver Disease and the Proteasome

Nutritional factors play important roles in the etiology of obesity, type 2 diabetes mellitus and their complications through genotype x environment interactions. We have characterised molecular adaptation to high fat diet (HFD) feeding in inbred mouse strains widely used in genetic and physiological studies. We carried out physiological tests, plasma lipid assays, obesity measures, liver histology, hepatic lipid measurements and liver genome-wide gene transcription profiling in C57BL/6J and BALB/c mice fed either a control or a high fat diet. The two strains showed marked susceptibility (C57BL/6J) and relative resistance (BALB/c) to HFD-induced insulin resistance and non alcoholic fatty liver disease (NAFLD). Global gene set enrichment analysis (GSEA) of transcriptome data identified consistent patterns of expression of key genes (Srebf1, Stard4, Pnpla2, Ccnd1) and molecular pathways in the two strains, which may underlie homeostatic adaptations to dietary fat. Differential regulation of pathways, including the proteasome, the ubiquitin mediated proteolysis and PPAR signalling in fat fed C57BL/6J and BALB/c suggests that altered expression of underlying diet-responsive genes may be involved in contrasting nutrigenomic predisposition and resistance to insulin resistance and NAFLD in these models. Collectively, these data, which further demonstrate the impact of gene x environment interactions on gene expression regulations, contribute to improved knowledge of natural and pathogenic adaptive genomic regulations and molecular mechanisms associated with genetically determined susceptibility and resistance to metabolic diseases.

Pathophysiological, genetic and gene expression features of a novel rodent model of the cardio-metabolic syndrome.

Background Complex etiology and pathogenesis of pathophysiological components of the cardio-metabolic syndrome have been demonstrated in humans and animal models. Methodology/Principal Findings We have generated extensive physiological, genetic and genome-wide gene expression profiles in a congenic strain of the spontaneously diabetic Goto-Kakizaki (GK) rat containing a large region (110 cM, 170 Mb) of rat chromosome 1 (RNO1), which covers diabetes and obesity quantitative trait loci (QTL), introgressed onto the genetic background of the normoglycaemic Brown Norway (BN) strain. This novel disease model, which by the length of the congenic region closely mirrors the situation of a chromosome substitution strain, exhibits a wide range of abnormalities directly relevant to components of the cardio-metabolic syndrome and diabetes complications, including hyperglycaemia, hyperinsulinaemia, enhanced insulin secretion both in vivo and in vitro, insulin resistance, hypertriglyceridemia and altered pancreatic and renal histological structures. Gene transcription data in kidney, liver, skeletal muscle and white adipose tissue indicate that a disproportionately high number (43–83%) of genes differentially expressed between congenic and BN rats map to the GK genomic interval targeted in the congenic strain, which represents less than 5% of the total length of the rat genome. Genotype analysis of single nucleotide polymorphisms (SNPs) in strains genetically related to the GK highlights clusters of conserved and strain-specific variants in RNO1 that can assist the identification of naturally occurring variants isolated in diabetic and hypertensive strains when different phenotype selection procedures were applied. Conclusions Our results emphasize the importance of rat congenic models for defining the impact of genetic variants in well-characterised QTL regions on in vivo pathophysiological features and cis-/trans- regulation of gene expression. The congenic strain reported here provides a novel and sustainable model for investigating the pathogenesis and genetic basis of risks factors for the cardio-metabolic syndrome.

Chromosomal Mapping of Quantitative Trait Loci Controlling Elastin Content in Rat Aorta

Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

Genetic control of plasma lipid levels in a cross derived from normoglycaemic Brown Norway and spontaneously diabetic Goto-Kakizaki rats.

Aims/hypothesisDyslipidaemia is a main component of the insulin resistance syndrome. The inbred Goto–Kakizaki (GK) rat is a model of spontaneous type 2 diabetes and insulin resistance, which has been used to identify diabetes-related susceptibility loci in genetic crosses. The objective of our study was to test the genetic control of lipid metabolism in the GK rat and investigate a possible relationship with known genetic loci regulating glucose homeostasis in this strain.Materials and methodsPlasma concentration of triglycerides, phospholipids, total cholesterol, HDL, LDL and VLDL cholesterol were determined in a cohort of 151 hybrids of an F2 cross derived from GK and non-diabetic Brown Norway (BN) rats. Data from the genome-wide scan of the F2 hybrids were used to test for evidence of genetic linkage to the lipid quantitative traits.ResultsWe identified statistically significant quantitative trait loci (QTLs) that control the level of plasma phospholipids and triglycerides (chromosome 1), LDL cholesterol (chromosome 3) and total and HDL cholesterol (chromosomes 1 and 5). These QTLs do not coincide with previously identified diabetes susceptibility loci in a similar cross. The significance of lipid QTLs mapped to chromosomes 1 and 5 is strongly influenced by sex.Conclusion/interpretationWe established that several genetic loci control the quantitative variations of plasma lipid variables in a GK×BN cross. They appear to be distinct from known GK diabetes QTLs, indicating that lipid metabolism and traits directly relevant to glucose and insulin regulation are controlled by different gene variants in this strain combination.

Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes

BackgroundMicroarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms.ResultsWe present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms.ConclusionThis study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.