Karène Argoud

Global microRNA expression profiles in insulin target tissues in a spontaneous rat model of type 2 diabetes

Aims/hypothesisMicroRNAs regulate a broad range of biological mechanisms. To investigate the relationship between microRNA expression and type 2 diabetes, we compared global microRNA expression in insulin target tissues from three inbred rat strains that differ in diabetes susceptibility.MethodsUsing microarrays, we measured the expression of 283 microRNAs in adipose, liver and muscle tissue from hyperglycaemic (Goto–Kakizaki), intermediate glycaemic (Wistar Kyoto) and normoglycaemic (Brown Norway) rats (n = 5 for each strain). Expression was compared across strains and validated using quantitative RT-PCR. Furthermore, microRNA expression variation in adipose tissue was investigated in 3T3-L1 adipocytes exposed to hyperglycaemic conditions.ResultsWe found 29 significantly differentiated microRNAs (padjusted < 0.05): nine in adipose tissue, 18 in liver and two in muscle. Of these, five microRNAs had expression patterns that correlated with the strain-specific glycaemic phenotype. MiR-222 (padjusted = 0.0005) and miR-27a (padjusted = 0.006) were upregulated in adipose tissue; miR-195 (padjusted = 0.006) and miR-103 (padjusted = 0.04) were upregulated in liver; and miR-10b (padjusted = 0.004) was downregulated in muscle. Exposure of 3T3-L1 adipocytes to increased glucose concentration upregulated the expression of miR-222 (p = 0.008), miR-27a (p = 0.02) and the previously reported miR-29a (p = 0.02). Predicted target genes of these differentially expressed microRNAs are involved in pathways relevant to type 2 diabetes.ConclusionThe expression patterns of miR-222, miR-27a, miR-195, miR-103 and miR-10b varied with hyperglycaemia, suggesting a role for these microRNAs in the pathophysiology of type 2 diabetes, as modelled by the Gyoto–Kakizaki rat. We observed similar patterns of expression of miR-222, miR-27a and miR-29a in adipocytes as a response to increased glucose levels, which supports our hypothesis that altered expression of microRNAs accompanies primary events related to the pathogenesis of type 2 diabetes.

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.

A modified RNA-Seq approach for whole genome sequencing of RNA viruses from faecal and blood samples

To date, very large scale sequencing of many clinically important RNA viruses has been complicated by their high population molecular variation, which creates challenges for polymerase chain reaction and sequencing primer design. Many RNA viruses are also difficult or currently not possible to culture, severely limiting the amount and purity of available starting material. Here, we describe a simple, novel, high-throughput approach to Norovirus and Hepatitis C virus whole genome sequence determination based on RNA shotgun sequencing (also known as RNA-Seq). We demonstrate the effectiveness of this method by sequencing three Norovirus samples from faeces and two Hepatitis C virus samples from blood, on an Illumina MiSeq benchtop sequencer. More than 97% of reference genomes were recovered. Compared with Sanger sequencing, our method had no nucleotide differences in 14,019 nucleotides (nt) for Noroviruses (from a total of 2 Norovirus genomes obtained with Sanger sequencing), and 8 variants in 9,542 nt for Hepatitis C virus (1 variant per 1,193 nt). The three Norovirus samples had 2, 3, and 2 distinct positions called as heterozygous, while the two Hepatitis C virus samples had 117 and 131 positions called as heterozygous. To confirm that our sample and library preparation could be scaled to true high-throughput, we prepared and sequenced an additional 77 Norovirus samples in a single batch on an Illumina HiSeq 2000 sequencer, recovering >90% of the reference genome in all but one sample. No discrepancies were observed across 118,757 nt compared between Sanger and our custom RNA-Seq method in 16 samples. By generating viral genomic sequences that are not biased by primer-specific amplification or enrichment, this method offers the prospect of large-scale, affordable studies of RNA viruses which could be adapted to routine diagnostic laboratory workflows in the near future, with the potential to directly characterize within-host viral diversity.

Enhanced insulin secretion and cholesterol metabolism in congenic strains of the spontaneously diabetic (Type 2) Goto Kakizaki rat are controlled by independent genetic loci in rat chromosome 8

Aims/hypothesisGenetic investigations in the spontaneously diabetic (Type 2) Goto Kakizaki (GK) rat have identified quantitative trait loci (QTL) for diabetes-related phenotypes. The aims of this study were to refine the chromosomal mapping of a QTL (Nidd/gk5) identified in chromosome 8 of the GK rat and to define a pathophysiological profile of GK gene variants underlying the QTL effects in congenics.MethodsGenetic linkage analysis was carried out with chromosome 8 markers genotyped in a GKxBN F2 intercross previously used to map diabetes QTL. Two congenic strains were designed to contain GK haplotypes in the region of Nidd/gk5 transferred onto a Brown Norway (BN) genetic background, and a broad spectrum of diabetes phenotypes were characterised in the animals.ResultsResults from QTL mapping suggest that variations in glucose-stimulated insulin secretion in vivo, and in body weight are controlled by different chromosome 8 loci (LOD3.53; p=0.0004 and LOD4.19; p=0.00007, respectively). Extensive physiological screening in male and female congenics at 12 and 24 weeks revealed the existence of GK variants at the locus Nidd/gk5, independently responsible for significantly enhanced insulin secretion and increased levels of plasma triglycerides, phospholipids and HDL, LDL and total cholesterol. Sequence polymorphisms detected between the BN and GK strains in genes encoding ApoAI, AIV, CIII and Lipc do not account for these effects.Conclusions/interpretationWe refined the localisation of the QTL Nidd/gk5 and its pathophysiological characteristics in congenic strains derived for the locus. These congenic strains provide novel models for testing the contribution of a subset of GK alleles on diabetes phenotypes and for identifying diabetes susceptibility genes.

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.

Untargeted Metabolome Quantitative Trait Locus Mapping Associates Variation in Urine Glycerate to Mutant Glycerate Kinase

With successes of genome-wide association studies, molecular phenotyping systems are developed to identify genetically determined disease-associated biomarkers. Genetic studies of the human metabolome are emerging but exclusively apply targeted approaches, which restricts the analysis to a limited number of well-known metabolites. We have developed novel technical and statistical methods for systematic and automated quantification of untargeted NMR spectral data designed to perform robust and accurate quantitative trait locus (QTL) mapping of known and previously unreported molecular compounds of the metabolome. For each spectral peak, six summary statistics were calculated and independently tested for evidence of genetic linkage in a cohort of F2 (129S6xBALB/c) mice. The most significant evidence of linkages were obtained with NMR signals characterizing the glycerate (LOD10-42) at the mutant glycerate kinase locus, which demonstrate the power of metabolomics in quantitative genetics to identify the biological function of genetic variants. These results provide new insights into the resolution of the complex nature of metabolic regulations and novel analytical techniques that maximize the full utilization of metabolomic spectra in human genetics to discover mappable disease-associated biomarkers.

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.

Mapping diabetes QTL in an intercross derived from a congenic strain of the Brown Norway and Goto-Kakizaki rats

Genetic studies in experimental crosses derived from the inbred Goto-Kakizaki (GK) rat model of spontaneous diabetes mellitus have identified quantitative trait loci (QTL) for diabetes phenotypes in a large region of rat Chromosome (RNO) 1. To test the impact of GK variants on QTL statistical and biological features, we combined genetic and physiologic studies in a cohort of F2 hybrids derived from a QTL substitution congenic strain (QTLSCS) carrying a 110-cM GK haplotype of RNO1 introgressed onto the genetic background of the Brown Norway (BN) strain. Glucose intolerance and altered insulin secretion in QTLSCS rats when compared with BN controls were consistent with original QTL features in a GK × BN F2 cross. Segregating GK alleles in the QTLSCS F2 cross account for most of these phenotypic differences between QTLSCS and BN rats. However, significant QTL for diabetes traits in both the QTLSCS and GK × BN F2 cohorts account for a similar small proportion of their variance. Comparing results from these experimental systems provides indirect estimates of the contribution of genetic interactions and environmental factors to QTL architecture as well as locus and biological targets for future post-QTL mapping studies in congenic substrains.

Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus

BackgroundHyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci.MethodsBoth Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]).ResultsDifferent patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations.ConclusionCombining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.