Genetic complexity of an obesity QTL ( Fob3) revealed by detailed genetic mapping

Differential alternative polyadenylation response to high-fat diet between polygenic obese and healthy lean mice

Obesity's complex etiology due to the interplay of environment and genetics makes it a more challenging research and health problem. Some of the contributing genetic factors that have not yet been examined in detail entail mRNA polyadenylation (PA). Genes with multiple PA sites express mRNA isoforms differing in coding sequence or 3'UTR through alternative polyadenylation (APA). Alterations in PA have been associated with various diseases; however, its contribution to obesity is not well-researched. Following an 11-week high-fat diet, the APA sites in the hypothalamus of two unique mouse models for polygenic obesity (Fat line) and healthy leanness (Lean line) were determined using whole transcriptome termini site sequencing (WTTS-seq). We found 17 genes of interest with differentially expressed APA (DE-APA) isoforms, among which seven were previously associated with obesity or obesity-related traits (Pdxdc1, Smyd3, Rpl14, Copg1, Pcna, Ric3, Stx3) but have not yet been studied in the context of APA. The remaining ten genes (Ccdc25, Dtd2, Gm14403, Hlf, Lyrm7, Mrpl3, Pisd-ps3, Sbsn, Slx1b, Spon1) represent novel candidates associated with obesity/adiposity due to variability brought about by differential usage of APA sites. Our results provide insights into the relationship between PA and the hypothalamus in the context of obesity, by being the first study of DE-APA sites and DE-APA isoforms in these mouse models. Future studies are needed further to explore the role of APA isoforms in polygenic obesity by expanding the scope of research to other metabolically important tissues (such as liver and adipose tissues) and investigating the potential for targeting PA as a therapeutic strategy for obesity management.

Protein digestibility and bioavailability in an F2 mouse cross between the selected fat mouse line and an M2 congenic line carrying the anti-obesity and anti-diabetic Tst allele

The study was performed to investigate protein digestibility and utilization in an F2 cross (M2-F2 cross) between the selected Fat (F) line and an M2 congenic line. The congenic M2 line carried the Fob3b2 quantitative trait locus (QTL) from the selected Lean (L) line previously shown to contain the Tst gene with leanness, anti-diabetic and resistance to diet-induced obesity effects. The main objective of the study was to test if some of the effects on leanness and obesity resistance of the L-line Fob3b2 could also be due to the effect of this QTL on nutrient digestibility and bioavailability. The F2 littermates carrying either the Fat line segment within the Fob3b2 region or the L-line were compared when fed the high-fat diet. Eleven mice per genotype were individually housed in metabolic cages. In 5-day experimental period, body mass and diet intake were measured. The part of study was done on the F and L line and tested the difference in apparent protein digestibility on low-fat (LFD) and high-fat (HFD) diet. The nitrogen content was determined in the diet, faeces, and urine based on which, the apparent protein digestibility, apparent protein biological value and apparent net protein utilization were calculated There were no significant differences in any of these parameters on congenic line, confirming that the phenotypic effect on adiposity between the genotypes in the M2-F2 population was not due to the differential effect of the Fob3b2 locus carrying the Tst gene on protein utilization. We conclude that the observed phenotypic effects of this gene region are due to direct metabolic actions rather than the effects on nutrient absorption and nitrogen utilization since there were no differences in apparent protein digestibility between L and F lines, irrespective to HFD or LFD. The age of animals had significant effect on the level of digestibility.

DEPTOR at the Nexus of Cancer, Metabolism, and Immunity

DEP domain-containing mechanistic target of rapamycin (mTOR)-interacting protein (DEPTOR) is an important modulator of mTOR, a kinase at the center of two important protein complexes named mTORC1 and mTORC2. These highly studied complexes play essential roles in regulating growth, metabolism, and immunity in response to mitogens, nutrients, and cytokines. Defects in mTOR signaling have been associated with the development of many diseases, including cancer and diabetes, and approaches aiming at modulating mTOR activity are envisioned as an attractive strategy to improve human health. DEPTOR interaction with mTOR represses its kinase activity and rewires the mTOR signaling pathway. Over the last years, several studies have revealed key roles for DEPTOR in numerous biological and pathological processes. Here, we provide the current state of the knowledge regarding the cellular and physiological functions of DEPTOR by focusing on its impact on the mTOR pathway and its role in promoting health and disease.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Obesity genetics in mouse and human: back and forth, and back again

Obesity is a major public health concern. This condition results from a constant and complex interplay between predisposing genes and environmental stimuli. Current attempts to manage obesity have been moderately effective and a better understanding of the etiology of obesity is required for the development of more successful and personalized prevention and treatment options. To that effect, mouse models have been an essential tool in expanding our understanding of obesity, due to the availability of their complete genome sequence, genetically identified and defined strains, various tools for genetic manipulation and the accessibility of target tissues for obesity that are not easily attainable from humans. Our knowledge of monogenic obesity in humans greatly benefited from the mouse obesity genetics field. Genes underlying highly penetrant forms of monogenic obesity are part of the leptin-melanocortin pathway in the hypothalamus. Recently, hypothesis-generating genome-wide association studies for polygenic obesity traits in humans have led to the identification of 119 common gene variants with modest effect, most of them having an unknown function. These discoveries have led to novel animal models and have illuminated new biologic pathways. Integrated mouse-human genetic approaches have firmly established new obesity candidate genes. Innovative strategies recently developed by scientists are described in this review to accelerate the identification of causal genes and deepen our understanding of obesity etiology. An exhaustive dissection of the molecular roots of obesity may ultimately help to tackle the growing obesity epidemic worldwide.

Fine-mapping QTLs in advanced intercross lines and other outbred populations

Quantitative genetic studies in model organisms, particularly in mice, have been extremely successful in identifying chromosomal regions that are associated with a wide variety of behavioral and other traits. However, it is now widely understood that identification of the underlying genes will be far more challenging. In the last few years, a variety of populations have been utilized in an effort to more finely map these chromosomal regions with the goal of identifying specific genes. The common property of these newer populations is that linkage disequilibrium spans relatively short distances, which permits fine-scale mapping resolution. This review focuses on advanced intercross lines (AILs) which are the simplest such population. As originally proposed in 1995 by Darvasi and Soller, an AIL is the product of intercrossing two inbred strains beyond the F2 generation. Unlike recombinant inbred strains, AILs are maintained as outbred populations; brother-sister matings are specifically avoided. Each generation of intercrossing beyond the F2 further degrades linkage disequilibrium between adjacent makers, which allows for fine-scale mapping of quantitative trait loci (QTLs). Advances in genotyping technology and techniques for the statistical analysis of AILs have permitted rapid advances in the application of AILs. We review some of the analytical issues and available software, including QTLRel, EMMA, EMMAX, GEMMA, TASSEL, GRAMMAR, WOMBAT, Mendel, and others.

Dissecting quantitative traits in mice

Progress in complex trait mapping in mice has been accelerated by the development of new populations suited to high-resolution mapping and by statistical methodologies that control for population structure. When combined with newly acquired catalogs of sequence variation in inbred strains, the genetic architecture of these new populations makes it possible to dissect complex traits down to the level of single variants. These analyses have shown not only that complex traits are caused by multiple contributing loci but also that each locus is likely due to the combined effects of multiple causal DNA variants. In combination with new rapid methods for producing transgenic mice that make it efficient to test candidate genes and variants, these advances significantly enhance the mouse genetics toolbox for dissecting quantitative traits.

Association studies in outbred mice in a new era of full-genome sequencing

Thousands of loci that contribute to quantitative traits in outbred crosses of mice have been reported over the last two decades. In this review we discuss how outbred mouse populations can be used to map and identify the genes and sequence variants that give rise to quantitative variation. We discuss heterogeneous stocks, the diversity outbred, and commercially available outbred populations of mice. All of these populations are descended from a small number of progenitor strains. The availability of the complete sequence of laboratory strains means that in many cases it will be possible to reconstruct the genomes of the outbred animals so that in a genetic association study we can detect the effect of all variants, a situation that has so far eluded studies in completely outbred populations. These resources constitute a major advance and make it possible to progress from a quantitative trait locus to a gene at an unprecedented speed.

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.

DEPTOR cell-autonomously promotes adipogenesis, and its expression is associated with obesity

DEP domain-containing mTOR-interacting protein (DEPTOR) inhibits the mechanistic target of rapamycin (mTOR), but its in vivo functions are unknown. Previous work indicates that Deptor is part of the Fob3a quantitative trait locus (QTL) linked to obesity/leanness in mice, with Deptor expression being elevated in white adipose tissue (WAT) of obese animals. This relation is unexpected, considering the positive role of mTOR in adipogenesis. Here, we dissected the Fob3a QTL and show that Deptor is the highest-priority candidate promoting WAT expansion in this model. Consistently, transgenic mice overexpressing DEPTOR accumulate more WAT. Furthermore, in humans, DEPTOR expression in WAT correlates with the degree of obesity. We show that DEPTOR is induced by glucocorticoids during adipogenesis and that its overexpression promotes, while its suppression blocks, adipogenesis. DEPTOR activates the proadipogenic Akt/PKB-PPAR-γ axis by dampening mTORC1-mediated feedback inhibition of insulin signaling. These results establish DEPTOR as a new regulator of adipogenesis.

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.

A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes

Background

Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain.

Results

To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity.

Conclusions

A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

Nonalcoholic Fatty liver disease: focus on lipoprotein and lipid deregulation

Obesity with associated comorbidities is currently a worldwide epidemic and among the most challenging health conditions in the 21st century. A major metabolic consequence of obesity is insulin resistance which underlies the pathogenesis of the metabolic syndrome. Nonalcoholic fatty liver disease (NAFLD) is the hepatic manifestation of obesity and metabolic syndrome. It comprises a disease spectrum ranging from simple steatosis (fatty liver), through nonalcoholic steatohepatitis (NASH) to fibrosis, and ultimately liver cirrhosis. Abnormality in lipid and lipoprotein metabolism accompanied by chronic inflammation is the central pathway for the development of metabolic syndrome-related diseases, such as atherosclerosis, cardiovascular disease (CVD), and NAFLD. This paper focuses on pathogenic aspect of lipid and lipoprotein metabolism in NAFLD and the relevant mouse models of this complex multifactorial disease.

Obesity resistant mechanisms in the Lean polygenic mouse model as indicated by liver transcriptome and expression of selected genes in skeletal muscle

Background

Divergently selected Lean and Fat mouse lines represent unique models for a polygenic form of resistance and susceptibility to obesity development. Previous research on these lines focused mainly on obesity-susceptible factors in the Fat line. This study aimed to examine the molecular basis of obesity-resistant mechanisms in the Lean line by analyzing various fat depots and organs, the liver transcriptome of selected metabolic pathways, plasma and lipid homeostasis and expression of selected skeletal muscle genes.

Results

Expression profiling using our custom Steroltalk v2 microarray demonstrated that Lean mice exhibit a higher hepatic expression of cholesterol biosynthesis genes compared to the Fat line, although this was not reflected in elevation of total plasma or liver cholesterol. However, FPLC analysis showed that protective HDL cholesterol was elevated in Lean mice. A significant difference between the strains was also found in bile acid metabolism. Lean mice had a higher expression of Cyp8b1, a regulatory enzyme of bile acid synthesis, and the Abcb11 bile acid transporter gene responsible for export of acids to the bile. Additionally, a higher content of blood circulating bile acids was observed in Lean mice. Elevated HDL and upregulation of some bile acids synthesis and transport genes suggests enhanced reverse cholesterol transport in the Lean line - the flux of cholesterol out of the body is higher which is compensated by upregulation of endogenous cholesterol biosynthesis. Increased skeletal muscle Il6 and Dio2 mRNA levels as well as increased activity of muscle succinic acid dehydrogenase (SDH) in the Lean mice demonstrates for the first time that changes in muscle energy metabolism play important role in the Lean line phenotype determination and corroborate our previous findings of increased physical activity and thermogenesis in this line. Finally, differential expression of Abcb11 and Dio2 identifies novel strong positional candidate genes as they map within the quantitative trait loci (QTL) regions detected previously in crosses between the Lean and Fat mice.

Conclusion

We identified novel candidate molecular targets and metabolic changes which can at least in part explain resistance to obesity development in the Lean line. The major difference between the Lean and Fat mice was in increased liver cholesterol biosynthesis gene mRNA expression, bile acid metabolism and changes in selected muscle genes' expression in the Lean line. The liver Abcb11 and muscle Dio2 were identified as novel positional candidate genes to explain part of the phenotypic difference between the Lean and Fat lines.

Mapping quantitative traits and strategies to find quantitative trait genes

In 1999 a meeting took place at the Jackson Laboratory, a large mouse research centre in Bar Harbor, Maine, to consider the value of systematically collecting phenotypes on inbred strains of mice (Paigen and Eppig (2000) [1]). The group concluded that cataloguing the extensive phenotypic diversity present among laboratory mice, and in particular providing the research community with data from cohorts of animals, phenotyped according to standardized protocols, was essential if we were to take advantage of the possibilities of mouse genetics. Beginning with the collection of basic physiological, biochemical and behavioral data on nine commonly used inbred strains, the project has expanded so that by the beginning of 2010 data for 178 strains had been collected, with 105 phenotype projects yielding over 2000 different measurements (Bogue et al. (2007) [2].

Congenic and bioinformatics analyses resolved a major-effect Fob3b QTL on mouse Chr 15 into two closely linked loci

We previously identified a Chr 15 quantitative trait locus (QTL) Fob3b in lines of mice selected for high (Fat line) and low (Lean line) body fat content that represent a unique model of polygenic obesity. Here we genetically dissected the Fob3b interval by analyzing the phenotypes of eight overlapping congenic lines and four F(2) congenic intercrosses and prioritized candidates by bioinformatics approaches. Analyses revealed that the Fob3b QTL consists of at least two separate linked QTLs Fob3b1 and Fob3b2. They exhibit additive inheritance and are linked in coupling with alleles originating from the Lean line, decreasing obesity-related traits. In further analyses, we focused on Fob3b1 because it had a larger effect on obesity-related traits than Fob3b2, e.g., the difference between homozygotes for adiposity index (ADI) percentage was 1.22 and 0.77% for Fob3b1 and Fob3b2, respectively. A set of bioinformatics tools was used to narrow down positional candidates from 85 to 4 high-priority Fob3b1 candidates. A previous single Fob3b QTL was therefore resolved into another two closely linked QTLs, confirming the fractal nature of QTLs mapped at low resolution. The interval of the original Fob3b QTL was narrowed from 22.39 to 4.98 Mbp for Fob3b1 and to 7.68 Mbp for Fob3b2, which excluded the previously assigned candidate squalene epoxidase (Sqle) as the causal gene because it maps proximal to refined Fob3b1 and Fob3b2 intervals. A high-resolution map along with prioritization of Fob3b1 candidates by bioinformatics represents an important step forward to final identification of the Chr 15 obesity QTL.

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F(2) crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F(2) offspring produced by 10 F(1) sires and 85 F(1) dams. AF and BM traits were measured on F(2) animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F(0), F(1) and F(2) birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F(2) design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.

Divergent physical activity and novel alternative responses to high fat feeding in polygenic fat and lean mice

We determined whether altered physical activity levels might underlie the contrasting adiposity of a divergently selected polygenic murine model of metabolic syndrome (Fat; F) and leanness (Lean; L) mice. We measured physical activity with a long term running wheel experiment and performed an additional high fat diet intervention. Further, we measured posture allocation by visual monitoring within the home cage as a non-exercise correlate of 'normal' physical activity. Whilst initially similar, running wheel activity of the F line declined with age, while the activity of the L line increased. Food intake was higher in the L line and increased with wheel exposure. Vertical rearing measured by video quantification in the home cage, without the stimulus of a running wheel was also significantly higher in the L line. The two lines developed novel alternate strategies to defend their body weight when exposed to high fat diets with a running wheel. F mice increased their running wheel activity, and despite unaltered food intake, still gained weight. L mice reduced their food intake and maintained activity levels without a significant change in body weight. Phenotypic selection for divergence in body fat content has co-segregated with a genetic predisposition for divergent physical activity levels and different strategies for coping with exposure to high fat diets that will facilitate the discovery of the genes underlying these important obesity related traits.

Fine mapping of mouse QTLs for fatness using SNP data

Quantitative trait loci (QTLs), as determined in crossbred studies, are a valuable resource to identify genes responsible for the corresponding phenotypic variances. Due to their broad chromosomal extension of some dozens of megabases, further steps are necessary to bring the number of candidate genes that underlie the detected effects to a reasonable order of magnitude. We use a set of 13,370 SNPs to identify informative haplotype blocks in 22 mouse QTLs for fatness. About half of the genes in a typical QTL overlap with haplotype blocks, which are different for the two base mouse lines, and which, thus, qualify for further analysis. For these genes we collect four more pieces of evidence for association with fat accumulation, namely (1) homology to genes identified in a Caenorhabditis elegans knock-out experiment as fat decreasing or fat increasing, (2) the overexpression of the genes in mouse fat, liver, muscle, or hypothalamus tissues, (3) the occurrence of a gene in several independently found QTLs, and (4) the information provided by gene ontology, to achieve a ranked list of 131 candidate genes. Ten genes fulfill three or four of the above sketched criteria and are discussed briefly, 121 further genes fulfilling two criteria are provided as on-line material. Viewing the genomic region of fatness-related QTLs under several different aspects is appropriate to assess the many thousands of genes that reside in such QTLs and to produce lists of more robust candidate genes.

Comparative genomics for detecting human disease genes

Originally, comparative genomics was geared toward defining the synteny of genes between species. As the human genome project accelerated, there was an increase in the number of tools and means to make comparisons culminating in having the genomic sequence for a large number of organisms spanning the evolutionary tree. With this level of resolution and a long history of comparative biology and comparative genetics, it is now possible to use comparative genomics to build or select better animal models and to facilitate gene discovery. Comparative genomics takes advantage of the functional genetic information from other organisms, (vertebrates and invertebrates), to apply it to the study of human physiology and disease. It allows for the identification of genes and regulatory regions, and for acquiring knowledge about gene function. In this chapter, the current state of comparative genomics and the available tools are discussed in the context of developing animal model systems that reflect the clinical picture.

Fine mapping dissects pleiotropic growth quantitative trait locus into linked loci

A recurring issue in studies of quantitative trait loci (QTLs) is whether QTLs that appear to have pleiotropic effects are indeed caused by pleiotropy at single loci or by linked QTLs. Previous work identified a QTL that affected tail length in mice and the lengths of various bones, including the humerus, ulna, femur, tibia, and mandible. The effect of this QTL on tail length has since been found to be due to multiple linked QTLs and so its apparently pleiotropic effects may have been due to linked QTLs with distinct effects. In the present study we examined a line of mice segregating only for a 0.94-Mb chromosomal region known to contain a subset of the QTLs influencing tail length. We measured a number of skeletal dimensions, including the lengths of the skull, mandible, humerus, ulna, femur, tibia, calcaneus, metatarsus, and a tail bone. The QTL region was found to have effects on the size of the mandible and length of the tail bone, with little or no effect on the other traits. Using a randomization approach, we rejected the null hypothesis that the QTL affected all traits equally, thereby demonstrating that the pleiotropic effects reported earlier were due to linked loci with distinct effects. This result underlines the possibility that seemingly pleiotropic effects of QTLs may frequently be due to linked loci and that high-resolution mapping will often be required to distinguish between pleiotropy and linkage.

A growth QTL (Pbwg1) region of mouse chromosome 2 contains closely linked loci affecting growth and body composition

Previous QTL studies have identified 24 QTLs for body weight and growth from 3 to 10 weeks after birth in an intersubspecific backcross mouse population between C57BL/6J and wild Mus musculus castaneus that has 60% of the body size of C57BL/6J. The castaneus allele at the most potent QTL (Pbwg1) on proximal chromosome 2 retards growth. In this study we have developed a congenic strain with a 44.1-Mb interval containing the castaneus allele at Pbwg1 by recurrent backcrossing to C57BL/6J. The congenic mouse developed was characterized by significantly higher body weight gain between 1 and 3 weeks of age and lower weight of white fat pads at 10 weeks of age than C57BL/6J. However, no clear difference in body weight at 1-10 weeks of age was observed between congenic and C57BL/6J strains. QTL analysis with 269 F(2) mice between the two strains did not identify any QTLs for body weight at 1, 3, 6, and 10 weeks of age, but it discovered eight closely linked QTLs affecting body weight gain from 1 to 3 weeks of age, lean body weight, weight of white fat pads, and body length within the Pbwg1 region. The castaneus alleles at all fat pad QTLs reduced the phenotypes, whereas at the remaining growth and body composition QTLs, they increased the trait values. These results illustrate that Pbwg1, which initially appeared to be a single locus, was resolved into several loci with opposite effects on the composition traits of overall body weight. This gives a reason for the loss of the Pbwg1 effect found in the original backcross population.

Mapping of the Plasmodium chabaudi resistance locus char2

Animals congenic for the char2 host response locus to the murine malarial parasite Plasmodium chabaudi have been bred, and they demonstrated a phenotypic difference from the parental lines. These congenic lines have been crossed back to the parental line to generate recombinants across the congenic intervals. The recombinants were inbred, and the subcongenic intervals were fixed. These lines were then challenged with parasites and assessed as being either resistant or susceptible. From the analysis of many subcongenic lines, it has become obvious that there are at least two loci underlying the char2 locus and that both of these mediate resistance when the haplotype derives from the resistant C57BL/6 strain.

Complex genetic architecture revealed by analysis of high-density lipoprotein cholesterol in chromosome substitution strains and F2 crosses

Intercrosses between inbred lines provide a traditional approach to analysis of polygenic inheritance in model organisms. Chromosome substitution strains (CSSs) have been developed as an alternative to accelerate the pace of gene identification in quantitative trait mapping. We compared a classical intercross and three CSS intercrosses to examine the genetic architecture underlying plasma high-density lipoprotein cholesterol (HDL) levels in the C57BL/6J (B) and A/J (A) mouse strains. The B x A intercross revealed significant quantitative trait loci (QTL) for HDL on chromosomes 1, 4, 8, 15, 17, 18, and 19. A CSS survey revealed that many have significantly different HDL levels compared to the background strain B, including chromosomes with no significant QTL in the intercross and, in some cases (CSS-1, CSS-17), effects that are opposite to those observed in the B x A intercross population. Intercrosses between B and three CSSs (CSS-3, CSS-11, and CSS-8) revealed significant QTL but with some unexpected differences from the B x A intercross. Our inability to predict the results of CSS intercrosses suggests that additional complexity will be revealed by further crosses and that the CSS mapping strategy should be viewed as a complement to, rather than a replacement for, classical intercross mapping.

Finding the molecular basis of complex genetic variation in humans and mice

I survey the state of the art in complex trait analysis, including the use of new experimental and computational technologies and resources becoming available, and the challenges facing us. I also discuss how the prospects of rodent model systems compare with association mapping in humans.

Genome-wide isolation of growth and obesity QTL using mouse speed congenic strains

Background

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.

Results

The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.

Conclusion

The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.

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.

Impact of genomics on research in the rat

The need to translate genes to function has positioned the rat as an invaluable animal model for genomic research. The significant increase in genomic resources in recent years has had an immediate functional application in the rat. Many of the resources for translational research are already in place and are ready to be combined with the years of physiological knowledge accumulated in numerous rat models, which is the subject of this perspective. Based on the successes to date and the research projects under way to further enhance the infrastructure of the rat, we also project where research in the rat will be in the near future. The impact of the rat genome project has just started, but it is an exciting time with tremendous progress.

Selection in backcross programmes

Backcrossing is a well-known and long established breeding scheme where a characteristic is introgressed from a donor parent into the genomic background of a recurrent parent. The various uses of backcrossing in modern genetics, particularly with the help of molecular markers, are reviewed here. Selection in backcross programmes is used to either improve the genetic value of plant and animal populations or fine map quantitative trait loci. Both cases are helpful in our understanding of the genetic bases of quantitative traits variation.

Strategies for mapping and cloning quantitative trait genes in rodents

Over the past 15 years, more than 2,000 quantitative trait loci (QTLs) have been identified in crosses between inbred strains of mice and rats, but less than 1% have been characterized at a molecular level. However, new resources, such as chromosome substitution strains and the proposed Collaborative Cross, together with new analytical tools, including probabilistic ancestral haplotype reconstruction in outbred mice, Yin-Yang crosses and in silico analysis of sequence variants in many inbred strains, could make QTL cloning tractable. We review the potential of these strategies to identify genes that underlie QTLs in rodents.

Fine mapping of a QTL region with large effects on growth and fatness on mouse chromosome 2

We combined the use of a congenic line and recombinant progeny testing (RPT) to characterize and fine map a previously identified region of distal mouse chromosome 2 (MMU2) harboring quantitative trait loci (QTL) with large effects on growth and fatness. The congenic line [M16i.B6-(D2Mit306-D2Mit52); MB2] was created using an inbred line (M16i) derived from a line that had undergone long-term selection for rapid weight gain (M16) as the recipient for an approximately 38-cM region on MMU2 from the inbred line C57BL/6J. A large F2 cohort (1,200 mice) originating from a cross between MB2 and M16i was created, and 40 F2 males with defined recombinations within the QTL region were used to produce 665 segregating progeny. Linkage analysis of the F2 population detected QTL with very large effects on body weight, body fat, lean tissue mass, bone mineral density, and liver weight. Confidence intervals of the QTL were narrowed to regions of 1.5-4.5 cM. Analysis of progeny of the recombinant F2 males confirmed the existence of the QTL and further contributed to localization of their map positions. These efforts confirmed the presence of QTL with major effect on MMU2, narrowed the estimated region harboring the QTL from 38 to 12 cM, and further characterized phenotypic effects of the QTL, effectively culminating in a significantly decreased pool of positional candidate genes potentially representing these genes controlling predisposition to growth and fatness.

Microarray gene expression analysis of the Fob3b obesity QTL identifies positional candidate gene Sqle and perturbed cholesterol and glycolysis pathways

Obesity-related diseases are poised to become the primary cause of death in developed nations. While a number of monogenic causes of obesity have recently been identified, these are responsible for only a small proportion of human cases of obesity. Quantitative trait locus (QTL) studies using animal models have revealed hundreds of potential loci that affect obesity; however, few have been further analyzed beyond the original QTL scan. We previously mapped four QTL in an F(2) between divergently selected Fat (F) and Lean (L) lines. A QTL of large effect on chromosome 15 (Fob3) was subsequently mapped to a higher resolution into two smaller-effect QTL (Fob3a and Fob3b) using crosses between the F-line and a congenic line containing L-line alleles at the Fob3 QTL region. Here we report the gene expression characterization of Fob3b. Microarray expression analysis using the NIA-NIH 15K cDNA array set containing 14,938 mouse ESTs was employed to identify candidate genes and pathways that are differentially expressed between the F-line and a congenic line containing only the Fob3b QTL (Fob3b-line). Our study suggests squalene epoxidase (Sqle), a cholesterol biosynthesis enzyme, as a strong positional candidate gene for Fob3b. Several other cholesterol biosynthesis pathway genes unlinked to Fob3b were found to be differentially expressed, suggesting that a perturbation of this pathway could be in part responsible for the phenotypic difference between the F-line and Fob3b-line mice.