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To test the impact of genetic heterogeneity on cis- and trans-mediated mechanisms of gene expression regulation, we profiled the transcriptome of adipose tissue in 20 inbred congenic strains derived from diabetic Goto–Kakizaki (GK) rats and Brown–Norway (BN) controls, which contain well-defined blocks (1–183 Mb) of genetic polymorphisms, and in 123 genetically heterogeneous rats of an (GK × BN)F2 offspring. Within each congenic we identified 73–1351 differentially expressed genes (DEGs), only 7.7% of which mapped within the congenic blocks, and which may be regulated in cis. The remainder localized outside the blocks, and therefore must be regulated in trans. Most trans-regulated genes exhibited approximately twofold expression changes, consistent with monoallelic expression. Altered biological pathways were replicated between congenic strains sharing blocks of genetic polymorphisms, but polymorphisms at different loci also had redundant effects on transcription of common distant genes and pathways. We mapped 2735 expression quantitative trait loci (eQTL) in the F2 cross, including 26% predominantly cis-regulated genes, which validated DEGs in congenic strains. A hotspot of >300 eQTL in a 10 cM region of chromosome 1 was enriched in DEGs in a congenic strain. However, many DEGs among GK, BN and congenic strains did not replicate as eQTL in F2 hybrids, demonstrating distinct mechanisms of gene expression when alleles segregate in an outbred population or are fixed homozygous across the entire genome or in short genomic regions. Our analysis provides conceptual advances in our understanding of the complex architecture of genome expression and pathway regulation, and suggests a prominent impact of epistasis and monoallelic expression on gene transcription.

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. © 2011 American Chemical Society.

Aims/hypothesis MicroRNAs 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. Methods Using 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. Results We found 29 significantly differentiated microRNAs (padjusted

Characterizing the relationships between genomic and phenotypic variation is essential to understanding disease etiology. Information-dense data sets derived from pathophysiological1, proteomic2,3 and transcriptomic4 profiling have been applied to map quantitative trait loci (QTLs). Metabolic traits, already used in QTL studies in plants5, 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 analysis6 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 genome7 (microbiome) perturbations that affect disease processes through transgenomic effects8 may influence QTL detection.

AIMS/HYPOTHESIS: Dyslipidaemia 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 METHODS: Plasma 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. RESULTS: We 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/INTERPRETATION: We established that several genetic loci control the quantitative variations of plasma lipid variables in a GKxBN 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.

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 F(2) 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 x BN F(2) cross. Segregating GK alleles in the QTLSCS F(2) 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 x BN F(2) 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.

While mutations in genes that function in the core molecular clock may disrupt circadian periodicity , their relevance to diurnal variation in metabolic, cardiovascular, and respiratory function is unknown. The circadian Clock gene product is an essential regulator of central and peripheral circadian rhythms in mammals. We have elucidated the complete exon–intron organization of the Clock gene in rat and have carried out an extensive search for single nucleotide polymorphisms (SNPs) in a panel of 12 inbred rat strains that exhibit diversity in studies of central and peripheral organ function and disease. The rat Clock gene consists of 23 exons spanning approximately 75 kb. Comparative sequence analysis identified 33 novel SNPs, including 32 that distinguish the Brown Norway (BN) rat from the other strains studied. Most notable were two novel mutations in the BN sequence at exon 8, Ile131Val and Ile132Val, occurring in a segment of the highly conserved PAS-A domain of the protein. These results afford the opportunity to assess the impact of genetic variation in Clock on central and peripheral functions subject to the core molecular clock and to test the importance of Clock variants in explaining diversity among rat strains in the expression of phenotypes, such as blood pressure, subject to circadian oscillation.

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.

Background Microarray 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. Results We 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. Conclusion This 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.

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.

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 studies in human populations and rodent models have identified regions of human chromosome 1q21–25 and rat chromosome 2 showing evidence of significant and replicated linkage to diabetes-related phenotypes. To investigate the relationship between the human and rat diabetes loci, we fine mapped the rat locus Nidd/ gk2 linked to hyperinsulinemia in an F2 cross derived from the diabetic (type 2) Goto-Kakizaki (GK) rat and the Brown Norway (BN) control rat, and carried out its genetic and pathophysiological characterization in BN.GK congenic strains. Evidence of glucose intolerance and enhanced insulin secretion in a congenic strain allowed us to localize the underlying diabetes gene(s) in a rat chromosomal interval of ∼3–6 cM conserved with an 11-Mb region of human 1q21–23. Positional diabetes candidate genes were tested for transcriptional changes between congenics and controls and sequence variations in a panel of inbred rat strains. Congenic strains of the GK rats represent powerful novel models for accurately defining the pathophysiological impact of diabetes gene(s) at the locus Nidd/ gk2 and improving functional annotations of diabetes candidates in human 1q21–23.

AIMS/HYPOTHESIS: Genetic 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. METHODS: Genetic 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. RESULTS: Results 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/INTERPRETATION: We 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.

Inbred strains of the laboratory rat are widely used for identifying genetic regions involved in the control of complex quantitative phenotypes of biomedical importance. The draft genomic sequence of the rat now provides essential information for annotating rat quantitative trait locus (QTL) maps. Following the survey of unique rat microsatellite (11,585 including 1648 new markers) and EST (10,067) markers currently available, we have incorporated a selection of 7952 rat EST sequences in an improved version of the integrated linkage-radiation hybrid map of the rat containing 2058 microsatellite markers which provided over 10,000 potential anchor points between rat QTL and the genomic sequence of the rat. A total of 996 genetic positions were resolved (avg. spacing 1.77 cM) in a single large intercross and anchored in the rat genomic sequence (avg. spacing 1.62 Mb). Comparative genome maps between rat and mouse were constructed by successful computational alignment of 6108 mapped rat ESTs in the mouse genome. The integration of rat linkage maps in the draft genomic sequence of the rat and that of other species represents an essential step for translating rat QTL intervals into human chromosomal targets. © 2004 by Cold Spring Harbor Laboratory Press.

Introduction Les variations communes de sequence d’ADN existantes chez l’Homme modifient l’expression des genes et contribuent a la susceptibilite aux maladies complexes. Notre objectif est d’etablir la relation entre le controle transcriptionel du tissu adipeux blanc et la susceptibilite a l’adiposite et au diabete mis en evidence chez le rat spontanement diabetique de la souche Goto-Kakizaki (GK). Materiels et methodes En utilisant des puces a ADN Illumina, nous avons analyse l’expression d’environ 20,000 genes dans le tissu adipeux blanc d’une population F2 (n = 138) derivee du GK et du rat controle Brown-Norway (BN) et d’une lignee congenique portant sur un fond genetique BN, les alleles GK a un locus genetique (QTL) lie a l’adiposite. Les loci lies a l’expression des genes (eQTL) ont ete identifies dans la population F2 en utilisant R/QTL, valides dans la lignee congenique par qRT-PCR, et analyses en relation avec la sequence genomique du GK produite au laboratoire. Resultats Nous avons identifie sur le genome entier, 585 eQTLs statistiquement significatifs (LOD > 9). La region 1q33 (8,3Mb), qui cosegrege avec un QTL d’adiposite, contient 172 genes candidats positionnels, parmi lesquels 44 correspondent a un eQTL. Nous avons valide l’expression differentielle de 27 de ces 44 genes dans la lignee congenique, qui montrent pour 48 % d’entre eux un effet de regulation transcriptionnelle en cis. L’analyse de 20,000 polymorphismes SNPs presents dans la region 1q33 nous a permis d’eliminer les eQTLs faux positifs et d’entreprendre l’analyse fonctionnelle de polymorphismes localises sur les genes candidats positionnels du QTL lie a l’adiposite, parmi lesquels le facteur de transcription ASCL3 (LOD > 43). Conclusion L’utilisation combinee de donnees du transcriptome et de sequencage nous a permis d’elucider le controle transcriptionnel du tissu adipeux blanc chez un modele de diabete et d’identifier des genes candidats fonctionnels et positionnels au locus1q33 associe a l’adiposite chez le rat GK. P

Background Hyperglycaemia 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. Methods Both 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]). Results Different 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. Conclusion Combining 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.

Insulin resistance and altered endocrine pancreas function are central pathophysiological features of type 2 diabetes mellitus (T2DM). The Goto-Kakizaki (GK) rat is a model of spontaneous T2DM characterised by reduced beta cell mass and genetically determined glucose intolerance and altered insulin secretion. To identify genetic determinants of endocrine pancreas histopathology, we carried out quantitative trait locus (QTL) mapping of histological phenotypes (beta cell mass -BCM and insulin-positive cell area -IPCA) and plasma concentration of hormones and growth factors in a F2 cohort derived from GK and normoglycemic Brown Norway rats. Although IPCA and BCM in the duodenal region of the pancreas were highly positively correlated (P 4) to growth hormome (GH) on chromosome 6 and prolactin on chromosome 17. These data suggest independent genetic control of the structure and function of ontologically different regions of the endocrine pancreas. Novel QTLs for corticosterone, prolactin and GH may contribute to diabetes in the GK. The QTLs that we have identified in this, and previous genetic studies collectively underline the complex and multiple mechanisms involved in diabetes in the GK strain. Electronic supplementary material The online version of this article (doi:10.1007/s00335-010-9285-3) contains supplementary material, which is available to authorized users.