Genetic contributions to body weight in mice: relationship of exploratory behavior to weight

Genetics of behavioural evolution in giant mice from Gough Island

The evolution of behaviour on islands is a pervasive phenomenon that contributed to Darwin's theory of natural selection. Island populations frequently show increased boldness and exploration compared with their mainland counterparts. Despite the generality of this pattern, the genetic basis of island-associated behaviours remains a mystery. To address this gap in knowledge, we genetically dissected behaviour in 613 F2s generated by crossing inbred mouse strains from Gough Island (where they live without predators or human commensals) and a mainland conspecific. We used open field and light/dark box tests to measure seven behaviours related to boldness and exploration in juveniles and adults. Across all assays, we identified a total of 41 quantitative trait loci (QTL) influencing boldness and exploration. QTL have moderate effects and are often unique to specific behaviours or ages. Function-valued trait mapping revealed changes in estimated effects of QTL during assays, providing a rare dynamic window into the genetics of behaviour often missed by standard approaches. The genomic locations of QTL are distinct from those found in laboratory strains of mice, indicating different genetic paths to the evolution of similar behaviours. We combine our mapping results with extensive phenotypic and genetic information available for laboratory mice to nominate candidate genes for the evolution of behaviour on islands.

Genetic linkage of oxidative stress with cardiometabolic traits in an intercross derived from hyperlipidemic mouse strains

BACKGROUND AND AIMS

Oxidative stress is associated with cardiometabolic traits in observational studies, yet the underlying causal relationship remains unclear. Apolipoprotein E-deficient (Apoe^-/-) mice develop significant hyperlipidemia and hyperglycemia on a Western diet. Here we conducted linkage analysis to investigate genetic connections between cardiometabolic traits and oxidative stress.

METHODS

266 female F2 mice were generated from an intercross between C57BL/6 (B6) and BALB/c (BALB) Apoe^-/- mice and fed 12 weeks of Western diet. Plasma levels of HDL, LDL cholesterol, triglycerides, glucose and malondialdehyde (MDA) and atherosclerosis in aortic root and left carotid artery were measured. 127 microsatellite markers across the genome were genotyped.

RESULTS

One significant locus at 78.3 cM on chromosome (Chr) 1 (LOD score: 3.85), named Mda1, and two suggestive loci near 60.3 cM on Chr1 (LOD score: 2.32, named Mda2 due to replication in a separate cross) and 19.6 cM on Chr4 (LOD score: 2.34) were identified for MDA levels. Mda1 coincided precisely with loci for LDL, triglyceride, glucose, and body weight and overlapped with a locus for atherosclerosis in the aortic root. Plasma LDL, triglyceride, and glucose explained 25.5, 19.2, and 24.2% of the variation in MDA levels of F2 mice, respectively. After correction for triglyceride or LDL, QTLs for MDA on Chr1 and Chr4 disappeared. QTLs on Chr1 disappeared, remained on Chr4, and additional QTLs on Chr12 and Chr13 were detected after correction for glucose. The QTL on Chr12, named Mda3, had a significant LOD score of 8.034 and peaked 62.22 at cM.

CONCLUSIONS

We demonstrated a causative role for cardiometabolic traits in oxidative stress and identified hyperlipidemia and hyperglycemia as a major driver of oxidative stress.

Dietary composition affects the development of cognitive deficits in WT and Tg AD model mice

Clinical and epidemiological evidence suggests that lifestyle factors, including nutrition, may influence the chances of developing of Alzheimer's disease (AD), and also likely affect the aging process. Whereas it is clear that high-fat diets are increasing both body weight and the risk of developing Alzheimer's disease, to date, there have been very few studies comparing diets high with different sources of calories (i.e., high fat versus high protein versus high carbohydrates) to determine whether dietary composition has importance beyond the known effect of high caloric intake to increase body weight, AD pathology and cognitive deficits. In the current study we examined the effects that different diets high in carbohydrate, protein or fat content, but similar in caloric value, have on the development of cognitive impairment and brain pathology in wild-type and Tg AD model mice. The results demonstrate that long term feeding with balanced diets similar in caloric content but with significant changes in the source of calories, all negatively influence cognition compared to the control diet, and that this effect is more pronounced in Tg animals with AD pathology.

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

The Human Obesity Gene Map: The 2003 Update

This is the tenth update of the human obesity gene map, incorporating published results up to the end of October 2003 and continuing the previous format. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTLs) from human genome-wide scans and animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. Transgenic and knockout murine models relevant to obesity are also incorporated (N = 55). As of October 2003, 41 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. QTLs reported from animal models currently number 183. There are 208 human QTLs for obesity phenotypes from genome-wide scans and candidate regions in targeted studies. A total of 35 genomic regions harbor QTLs replicated among two to five studies. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 272 studies reporting positive associations with 90 candidate genes. Fifteen such candidate genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, more than 430 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful sites can be found at http://obesitygene.pbrc.edu.

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.

Genetic analysis of atherosclerosis and glucose homeostasis in an intercross between C57BL/6 and BALB/cJ apolipoprotein E-deficient mice

BACKGROUND

Diabetic patients have an increased risk of developing atherosclerosis and related complications compared with nondiabetic individuals. The increased cardiovascular risk associated with diabetes is due in part to genetic variations that influence both glucose homeostasis and atherosclerotic lesion growth. Mouse strains C57BL/6J (B6) and BALB/cJ (BALB) exhibit distinct differences in fasting plasma glucose and atherosclerotic lesion size when deficient in apolipoprotein E (Apoe(-/-)). Quantitative trait locus (QTL) analysis was performed to determine genetic factors influencing the 2 phenotypes.

METHODS AND RESULTS

Female F(2) mice (n=266) were generated from an intercross between B6.Apoe(-/-) and BALB.Apoe(-/-) mice and fed a Western diet for 12 weeks. Atherosclerotic lesions in the aortic root, fasting plasma glucose, and body weight were measured. 130 microsatellite markers across the entire genome were genotyped. Four significant QTLs, Ath1 on chromosome (Chr) 1, Ath41 on Chr2, Ath42 on Chr5, and Ath29 on Chr9, and 1 suggestive QTL on Chr4, were identified for atherosclerotic lesion size. Four significant QTLs, Bglu3 and Bglu12 on Chr1, Bglu13 on Chr5, Bglu15 on Chr12, and 2 suggestive QTLs on Chr9 and Chr15 were identified for fasting glucose levels on the chow diet. Two significant QTLs, Bglu3 and Bglu13, and 1 suggestive locus on Chr8 were identified for fasting glucose on the Western diet. One significant locus on Chr1 and 2 suggestive loci on Chr9 and Chr19 were identified for body weight. Ath1 and Ath42 coincided with Bglu3 and Bglu13, respectively, in the confidence interval.

CONCLUSIONS

We have identified novel QTLs that have major influences on atherosclerotic lesion size and glucose homeostasis. The colocalization of QTLs for atherosclerosis and diabetes suggests possible genetic connections between the 2 diseases.

Forward genetic approaches to understanding complex behaviors

Assigning function to genes has long been a focus of biomedical research.Even with complete knowledge of the genomic sequences of humans, mice and other experimental organisms, there is still much to be learned about gene function and control. Ablation or overexpression of single genes using knockout or transgenic technologies has provided functional annotation for many genes, but these technologies do not capture the extensive genetic variation present in existing experimental mouse populations. Researchers have only recently begun to truly appreciate naturally occurring genetic variation resulting from single nucleotide substitutions,insertions, deletions, copy number variation, epigenetic changes (DNA methylation,histone modifications, etc.) and gene expression differences and how this variation contributes to complex phenotypes. In this chapter, we will discuss the benefits and limitations of different forward genetic approaches that capture the genetic variation present in inbred mouse strains and present the utility of these approaches for mapping QTL that influence complex behavioral phenotypes.

Identification of genes and networks driving cardiovascular and metabolic phenotypes in a mouse F2 intercross

To identify the genes and pathways that underlie cardiovascular and metabolic phenotypes we performed an integrated analysis of a mouse C57BL/6JxA/J F2 (B6AF2) cross by relating genome-wide gene expression data from adipose, kidney, and liver tissues to physiological endpoints measured in the population. We have identified a large number of trait QTLs including loci driving variation in cardiac function on chromosomes 2 and 6 and a hotspot for adiposity, energy metabolism, and glucose traits on chromosome 8. Integration of adipose gene expression data identified a core set of genes that drive the chromosome 8 adiposity QTL. This chromosome 8 trans eQTL signature contains genes associated with mitochondrial function and oxidative phosphorylation and maps to a subnetwork with conserved function in humans that was previously implicated in human obesity. In addition, human eSNPs corresponding to orthologous genes from the signature show enrichment for association to type II diabetes in the DIAGRAM cohort, supporting the idea that the chromosome 8 locus perturbs a molecular network that in humans senses variations in DNA and in turn affects metabolic disease risk. We functionally validate predictions from this approach by demonstrating metabolic phenotypes in knockout mice for three genes from the trans eQTL signature, Akr1b8, Emr1, and Rgs2. In addition we show that the transcriptional signatures for knockout of two of these genes, Akr1b8 and Rgs2, map to the F2 network modules associated with the chromosome 8 trans eQTL signature and that these modules are in turn very significantly correlated with adiposity in the F2 population. Overall this study demonstrates how integrating gene expression data with QTL analysis in a network-based framework can aid in the elucidation of the molecular drivers of disease that can be translated from mice to humans.

Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

Discovery of genes that confer resistance to diseases such as diet-induced obesity could have tremendous therapeutic impact. We previously demonstrated that the C57BL/6J-Chr(A/J)/NaJ panel of chromosome substitution strains (CSSs) is a unique model for studying resistance to diet-induced obesity. In the present study, three replicate CSS surveys showed remarkable consistency, with 13 A/J-derived chromosomes reproducibly conferring resistance to high-fat-diet-induced obesity. Twenty CSS intercrosses, one derived from each of the 19 autosomes and chromosome X, were used to determine the number and location of quantitative trait loci (QTLs) on individual chromosomes and localized six QTLs. However, analyses of mean body weight in intercross progeny versus C57BL/6J provided strong evidence that many QTLs discovered in the CSS surveys eluded detection in these CSS intercrosses. Studies of the temporal effects of these QTLs suggest that obesity resistance was dynamic, with QTLs acting at different ages or after different durations of diet exposure. Thus, these studies provide insight into the genetic architecture of complex traits such as resistance to diet-induced obesity in the C57BL/6J-Chr(A/J)/NaJ CSSs. Because some of the QTLs detected in the CSS intercrosses were not detected using a traditional C57BL/6J x A/J intercross, our results demonstrate that surveys of CSSs and congenic strains derived from them are useful complementary tools for analyzing complex traits.

Bone microstructure and its associated genetic variability in 12 inbred mouse strains: microCT study and in silico genome scan

MicroCT analysis of 12 inbred strains of mice identified 5 novel chromosomal regions influencing skeletal phenotype. Bone morphology varied in a compartment- and site-specific fashion across strains and genetic influences contributed to the morphometric similarities observed in femoral and vertebral bone within the trabecular bone compartment.

INTRODUCTION

Skeletal development is known to be regulated by both heritable and environmental factors, but whether genetic influence on peak bone mass is site- or compartment-specific is unknown. This study examined the genetic variation of cortical and trabecular bone microarchitecture across 12 strains of mice.

MATERIALS AND METHODS

MicroCT scanning was used to measure trabecular and cortical bone morphometry in the femur and vertebra of 12 strains of 4-month-old inbred male mice. A computational genome mapping technique was used to identify chromosomal intervals associated with skeletal traits.

RESULTS

Skeletal microarchitecture varied in a compartment- and site-specific fashion across strains. Genome mapping identified 13 chromosomal intervals associated with skeletal traits and 5 of these intervals were novel. Trabecular microarchitecture in different bone sites correlated across strains and most of the chromosomal intervals associated with these trabecular traits were shared between skeletal sites. Conversely, no chromosomal intervals were shared between the trabecular and cortical bone compartments in the femur, even though there was a strong correlation for these different bone compartments across strains, suggesting site-specific regulation by environmental or intrinsic factors.

CONCLUSION

In summary, these data confirm that there are distinct genetic determinants that define the skeletal phenotype at the time when peak bone mass is being acquired, and that genomic regulation of bone morphology is specific for skeletal compartment.

Genetic regulation of hypothalamic cocaine and amphetamine-regulated transcript (CART) in BxD inbred mice

Cocaine and Amphetamine-Regulated Transcript (CART) peptides are implicated in a wide range of behaviors including in the reinforcing properties of psychostimulants, feeding and energy balance and stress and anxiety responses. We conducted a complex trait analysis to examine natural variation in the regulation of CART transcript abundance (CARTta) in the hypothalamus. CART transcript abundance was measured in total hypothalamic RNA from 26 BxD recombinant inbred (RI) mouse strains and in the C57BL/6 (B6) and DBA/2J (D2) progenitor strains. The strain distribution pattern for CARTta was continuous across the RI panel, which is consistent with this being a quantitative trait. Marker regression and interval mapping revealed significant quantitative trait loci (QTL) on mouse chromosome 4 (around 58.2 cM) and chromosome 11 (between 20-36 cM) that influence CARTta and account for 31% of the between strain variance in this phenotype. There are numerous candidate genes and QTL in these chromosomal regions that may indicate shared genetic regulation between CART expression and other neurobiological processes referable to known actions of this neuropeptide.

Incorporating genome-scale tools for studying energy homeostasis

Mammals have evolved complex regulatory systems that enable them to maintain energy homeostasis despite constant environmental challenges that limit the availability of energy inputs and their composition. Biological control relies upon intricate systems composed of multiple organs and specialized cell types that regulate energy up-take, storage, and expenditure. Because these systems simultaneously perform diverse functions and are highly integrated, they are extremely difficult to understand in terms of their individual component contributions to energy homeostasis. In order to provide improved treatments and clinical options, it is important to identify the principle genetic and molecular components, as well as the systemic features of regulation. To begin, many of these features can be discovered by integrating experimental technologies with advanced methods of analysis. This review focuses on the analysis of transcriptional data derived from microarrays and how it can complement other experimental techniques to study energy homeostasis.

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

OBJECTIVE

Cross-breeding experiments with different mouse strains have successfully been used by many groups to identify genetic loci that predispose for obesity. In order to provide a statistical assessment of these quantitative trait loci (QTL) as a basis for a systematic investigation of candidate genes, we have performed a meta-analysis of genome-wide linkage scans for body weight and body fat.

DATA

From a total of 34 published mouse cross-breeding experiments, we compiled a list of 162 non-redundant QTL for body weight and 117 QTL for fat weight and body fat percentage. Collectively, these studies include data from 42 different parental mouse strains and >14,500 individual mice.

METHODS

The results of the studies were analyzed using the truncated product method (TPM).

RESULTS

The analysis revealed significant evidence (logarithm of odds (LOD) score >4.3) for linkage of body weight and adiposity to 49 different segments of the mouse genome. The most prominent regions with linkage for body weight and body fat (LOD scores 14.8-21.8) on chromosomes 1, 2, 7, 11, 15, and 17 contain a total of 58 QTL for body weight and body fat. At least 34 candidate genes and genetic loci, which have been implicated in regulation of body weight and body composition in rodents and/or humans, are found in these regions, including CCAAT/enhancer-binding protein alpha (C/EBPA), sterol regulatory element-binding transcription factor 1 (SREBP-1), peroxisome proliferator activator receptor delta (PPARD), and hydroxysteroid 11-beta dehydrogenase 1 (HSD11B1). Our results demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control body weight and body composition. An interactive physical map of the QTL is available online at (http://www.obesitygenes.org).

Obesity and its therapy: from genes to community action

Like many diseases, the causes of obesity are complex, and their investigation requires novel approaches. Given the many contributors to our weight status, as well as the dynamic nature, genomic tools must be applied in an ecological model. Evaluating disparate factors can be difficult, such as feeding behavior, nutritional genomics, and gene-environment interaction. Many of these behaviors are being evaluated in animal models and hold great promise for targeted interventions in the future.

Genetic linkage of hyperglycemia, body weight and serum amyloid-P in an intercross between C57BL/6 and C3H apolipoprotein E-deficient mice

Dyslipidemia and hyperglycemia are integral components of the metabolic perturbations in type 2 diabetes. Apolipoprotein E-deficient (apoE(-/-)) mice develop severe hyperlipidemia and significant hyperglycemia when fed a western diet containing 21% fat (w/w), 0.15% cholesterol and 19.5% casein. Using an intercross between C57BL/6J (B6) and C3H/HeJ (C3H) apoE(-/-) mice, we performed quantitative trait locus (QTL) analysis to identify loci contributing to hyperglycemia and associated traits. Fasting plasma levels of glucose, insulin and serum amyloid-P (SAP) and body weight in 234 female F2 mice were measured after being fed the western diet for 12 weeks. QTL analysis revealed one significant QTL, named Bglu3 [95.8 cM, logarithm of odds ratio (OR)(LOD) 4.1], on chromosome 1 and a suggestive QTL on chromosome 9 (38 cM, LOD 2.3) that influenced plasma glucose levels. Bglu3 coincided with loci on distal chromosomal 1 that had a major influence on plasma SAP levels and body weight. Significant correlations between plasma glucose, SAP and body weight were observed in F2 mice. Thus, these results demonstrate genetic linkages of hyperglycemia and body weight with SAP, a marker of the acute-phase response, in hyperlipidemic apoE(-/-) mice and suggest a probability for the Sap gene to be a positional candidate of Bglu3.

The human obesity gene map: the 2005 update

This paper presents the 12th update of the human obesity gene map, which incorporates published results up to the end of October 2005. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTL) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2005, 176 human obesity cases due to single-gene mutations in 11 different genes have been reported, 50 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 244 genes that, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 408. The number of human obesity QTLs derived from genome scans continues to grow, and we now have 253 QTLs for obesity-related phenotypes from 61 genome-wide scans. A total of 52 genomic regions harbor QTLs supported by two or more studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably, with 426 findings of positive associations with 127 candidate genes. A promising observation is that 22 genes are each supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. The electronic version of the map with links to useful publications and relevant sites can be found at http://obesitygene.pbrc.edu.

Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE^−/−) background. This BXH.ApoE^−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.

Although their genomes are nearly identical, the males and females of a species exhibit striking differences in many traits, including complex traits such as obesity. This study combines genetic and genomic tools to identify in parallel quantitative trait loci (QTLs) for a measure of gonadal fat mass and for expression of transcripts in the liver. The results are used to explore the relationship between genetic variation, sexual differentiation, and obesity in the mouse model. Using over 300 intercross progeny of two inbred mouse strains, five loci in the genome were found to be highly correlated with abdominal fat mass. Four of the five loci exhibited opposite effects on obesity in the two sexes, a phenomenon known as sexual antagonism. To identify candidate genes that may be involved in obesity through their expression in the liver, global gene expression analysis was employed using microarrays. Many of these expression QTLs also show sex-specific effects on transcription. A hotspot for trans-acting QTLs regulating the expression of transcripts whose abundance is correlated with gonadal fat mass was identified on Chromosome 19. This region of the genome colocalizes with a clinical QTL for gonadal fat mass, suggesting that it harbors a good candidate gene for obesity.

Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci

Obesity is a highly heritable and genetically complex trait with hundreds of potential loci identified. An intercross of 513 F2 progeny between the SM/J x NZB/BINJ inbred mouse strains was generated to identify quantitative trait loci (QTL) that are involved in the weight of four fat pads: mesenteric, inguinal, gonadal, and retroperitoneal. Sex and lean body weight were treated as covariates in the analysis of these fat pads. This analysis uncoupled genetic effects related to overall body size from those influencing the adiposity of a mouse. We identified multiple significant QTL. QTL alleles associated with increased lean body weight and individual fat pad weights are contributed by the NZB background. Adiposity loci are distinct from these body size QTLs and high-adiposity alleles are contributed by the SM background. An extended network of epistatic QTL is also observed. A QTL on Chr 19 is the center of a network of eight interacting QTL, Chr 4 is the center of six, and Chr 17 the center of four interacting QTL. We conclude that interacting networks of multiple genes characterize the regulation of fat pad depots and body weight. Haplotype patterns and a literature-driven approach were used to generate hypotheses regarding the identity of the genes and pathways underlying the QTL.

Quantitative trait locus analysis of atherosclerosis in an intercross between C57BL/6 and C3H mice carrying the mutant apolipoprotein E gene

Inbred mouse strains C57BL/6J (B6) and C3H/HeJ (C3H) differ significantly in atherosclerosis susceptibility and plasma lipid levels on the apolipoprotein E-deficient (apoE-/-) background when fed a Western diet. To determine genetic factors contributing to the variations in these phenotypes, we performed quantitative trait locus (QTL) analysis using an intercross between the two strains carrying the apoE-/- gene. Atherosclerotic lesions at the aortic root and plasma lipid levels of 234 female F2 mice were analyzed after being fed a Western diet for 12 weeks. QTL analysis revealed one significant QTL, named Ath22 (42 cM, LOD 4.1), on chromosome 9 and a suggestive QTL near D11mit236 (20 cM, LOD 2.4) on chromosome 11 that influenced atherosclerotic lesion size. One significant QTL on distal chromosome 1, which accounted for major variations in plasma LDL/VLDL cholesterol and triglyceride levels, coincided with a QTL having strong effects on body weight. Plasma LDL/VLDL cholesterol or triglyceride levels of F2 mice were significantly correlated with body weight, but they were not correlated with atherosclerotic lesion sizes. These data indicate that atherosclerosis susceptibility and plasma cholesterol levels are controlled by separate genetic factors in the B6 and C3H mouse model and that genetic linkages exist between body weight and lipoprotein metabolism.

Genetic analysis of the hypothalamic corticotropin-releasing factor system

The goal of this study was to use BxD recombinant inbred mice to search for genes that control the hypothalamic corticotrophin-releasing factor (CRF) system. The specific phenotype that was measured was abundance of transcripts that encode CRF, CRF receptor (Crf-R1), CRF binding protein, and arginine vasopressin (AVP) in total hypothalamic RNA. The strain distribution patterns for the transcript abundances for each target were continuously distributed, consistent with these being quantitative traits. Marker regression and interval mapping revealed associations with quantitative trait loci (QTL) for CRF transcript abundance on chromosome 1 (at 89.2 cM), chromosome 12 (between 54-58 cM), and chromosome 13 (between 26-30 cM); for Crf-R1 transcript abundance on chromosome 7 (at 1.5 cM), chromosome 12 (at 37 cM), and chromosome X (at 30 cM); for CRF binding protein transcript abundance on chromosome 7 (at 48.5 cM), chromosome 8 (at 65 cM), and chromosome 12 (at 19 cM); and for AVP transcript abundance on chromosome 7 (at 1 cM), chromosome 12 (at 13 cM), and chromosome 13 (at 45 cM). The transcript abundance QTL were not linked to their respective structural genes. Interval mapping on chromosome 7 reveals substantial overlap between QTL that control AVP and Crf-R1 transcript abundance and on chromosome 12 for QTL that control CRF and Crf-R1, which may indicate loci that coordinate regulation of the CRF system. There are QTL for all four targets on chromosome 12. There are a number of neurodevelopmental genes in very close proximity to the transcript abundance QTL that are potential candidate genes.

Mapping quantitative trait loci for anxiety in chromosome substitution strains of mice

Anxious behavior in the mouse is a complex quantitative phenotype that varies widely among inbred mouse strains. We examined a panel of chromosome substitution strains bearing individual A/J chromosomes in an otherwise C57BL/6J background in open-field and light-dark transition tests. Our results confirmed previous reports of quantitative trait loci (QTL) on chromosomes 1, 4, and 15 and identified novel loci on chromosomes 6 and 17. The studies were replicated in two separate laboratories. Systematic differences in the overall activity level were found between the two facilities, but the presence of the QTL was confirmed in both laboratories. We also identified specific effects on open-field defecation and center avoidance and distinguished them from overall open-field activity.

Genetic dissection of complex traits with chromosome substitution strains of mice

Chromosome substitution strains (CSSs) have been proposed as a simple and powerful way to identify quantitative trait loci (QTLs) affecting developmental, physiological, and behavioral processes. Here, we report the construction of a complete CSS panel for a vertebrate species. The CSS panel consists of 22 mouse strains, each of which carries a single chromosome substituted from a donor strain (A/J) onto a common host background (C57BL/6J). A survey of 53 traits revealed evidence for 150 QTLs affecting serum levels of sterols and amino acids, diet-induced obesity, and anxiety. These results demonstrate that CSSs greatly facilitate the detection and identification of genes that control the wide diversity of naturally occurring phenotypic variation in the A/J and C57BL/6J inbred strains.