Sensitivity to dietary obesity linked to a locus on chromosome 15 in a CAST/Ei x C57BL/6J F2 intercross

Genetics of metabolic syndrome: potential clues from wild-derived inbred mouse strains

The metabolic syndrome (MetS) is a complex constellation of metabolic abnormalities including obesity, abnormal glucose metabolism, dyslipidemia, and elevated blood pressure that together substantially increase risk for cardiovascular disease and Type 2 diabetes. Both genetic and environmental factors contribute to the development of MetS, but this process is still far from understood. Human studies have revealed only part of the underlying basis. Studies in mice offer many strengths that can complement human studies to help elucidate the etiology and pathophysiology of MetS. Here we review the ways mice can contribute to MetS research. In particular, we focus on the information that can be obtained from studies of the inbred strains, with specific focus on the phenotypes of the wild-derived inbred strains. These are newly derived inbred strains that were created from wild-caught mice. They contain substantial genetic variation that is not present in the classical inbred strains, have phenotypes of relevance for MetS, and various mouse strain resources have been created to facilitate the mining of this new genetic variation. Thus studies using wild-derived inbred strains hold great promise for increasing our understanding of MetS.

Adiposity QTL Adip20 decomposes into at least four loci when dissected using congenic strains

An average mouse in midlife weighs between 25 and 30 g, with about a gram of tissue in the largest adipose depot (gonadal), and the weight of this depot differs between inbred strains. Specifically, C57BL/6ByJ mice have heavier gonadal depots on average than do 129P3/J mice. To understand the genetic contributions to this trait, we mapped several quantitative trait loci (QTLs) for gonadal depot weight in an F2 intercross population. Our goal here was to fine-map one of these QTLs, Adip20 (formerly Adip5), on mouse chromosome 9. To that end, we analyzed the weight of the gonadal adipose depot from newly created congenic strains. Results from the sequential comparison method indicated at least four rather than one QTL; two of the QTLs were less than 0.5 Mb apart, with opposing directions of allelic effect. Different types of evidence (missense and regulatory genetic variation, human adiposity/body mass index orthologues, and differential gene expression) implicated numerous candidate genes from the four QTL regions. These results highlight the value of mouse congenic strains and the value of this sequential method to dissect challenging genetic architecture.

High-resolution mapping of a genetic locus regulating preferential carbohydrate intake, total kilocalories, and food volume on mouse chromosome 17

The specific genes regulating the quantitative variation in macronutrient preference and food intake are virtually unknown. We fine mapped a previously identified mouse chromosome 17 region harboring quantitative trait loci (QTL) with large effects on preferential macronutrient intake-carbohydrate (Mnic1), total kilcalories (Kcal2), and total food volume (Tfv1) using interval-specific strains. These loci were isolated in the [C57BL/6J.CAST/EiJ-17.1-(D17Mit19-D17Mit50); B6.CAST-17.1] strain, possessing a ∼ 40.1 Mb region of CAST DNA on the B6 genome. In a macronutrient selection paradigm, the B6.CAST-17.1 subcongenic mice eat 30% more calories from the carbohydrate-rich diet, ∼ 10% more total calories, and ∼ 9% more total food volume per body weight. In the current study, a cross between carbohydrate-preferring B6.CAST-17.1 and fat-preferring, inbred B6 mice was used to generate a subcongenic-derived F2 mapping population; genotypes were determined using a high-density, custom SNP panel. Genetic linkage analysis substantially reduced the 95% confidence interval for Mnic1 (encompassing Kcal2 and Tfv1) from 40.1 to 29.5 Mb and more precisely established its boundaries. Notably, no genetic linkage for self-selected fat intake was detected, underscoring the carbohydrate-specific effect of this locus. A second key finding was the separation of two energy balance QTLs: Mnic1/Kcal2/Tfv1 for food intake and a newly discovered locus regulating short term body weight gain. The Mnic1/Kcal2/Tfv1 QTL was further de-limited to 19.0 Mb, based on the absence of nutrient intake phenotypes in subcongenic HQ17IIa mice. Analyses of available sequence data and gene ontologies, along with comprehensive expression profiling in the hypothalamus of non-recombinant, cast/cast and b6/b6 F2 controls, focused our attention on candidates within the QTL interval. Zfp811, Zfp870, and Btnl6 showed differential expression and also contain stop codons, but have no known biology related to food intake regulation. The genes Decr2, Ppard and Agapt1 are more appealing candidates because of their involvement in lipid metabolism and down-regulation in carbohydrate-preferring animals.

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.

The importance of context to the genetic architecture of diabetes-related traits is revealed in a genome-wide scan of a LG/J × SM/J murine model

Variations in diabetic phenotypes are caused by complex interactions of genetic effects, environmental factors, and the interplay between the two. We tease apart these complex interactions by examining genome-wide genetic and epigenetic effects on diabetes-related traits among different sex, diet, and sex-by-diet cohorts in a Mus musculus model. We conducted a genome-wide scan for quantitative trait loci that affect serum glucose and insulin levels and response to glucose stress in an F(16) Advanced Intercross Line of the LG/J and SM/J intercross (Wustl:LG,SM-G16). Half of each sibship was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (parent-of-origin imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. We found that different cohorts often have unique genetic effects at the same loci, and that genetic signals can be masked or erroneously assigned to specific cohorts if they are not considered individually. Our data demonstrate that the effects of genes on complex trait variation are highly context-dependent and that the same genomic sequence can affect traits differently depending on an individual's sex and/or dietary environment. Our results have important implications for studies of complex traits in humans.

Biology of obesity: lessons from animal models of obesity

Obesity is an epidemic problem in the world and is associated with several health problems, including diabetes, cardiovascular disease, respiratory failure, muscle weakness, and cancer. The precise molecular mechanisms by which obesity induces these health problems are not yet clear. To better understand the pathomechanisms of human disease, good animal models are essential. In this paper, we will analyze animal models of obesity and their use in the research of obesity-associated human health conditions and diseases such as diabetes, cancer, and obstructive sleep apnea syndrome.

Further understanding of fat biology: lessons from a fat fly

Obesity is a leading risk factor for insulin resistance, hypertension, hyperlipidemia, and cardiovascular complications, collectively referred to as metabolic diseases. Given the prevalence of obesity and its associated medical problems, new strategies are required to prevent or treat obesity and obesity-related metabolic effects. Here we summarize contributors of obesity, and molecular mechanisms controlling adipogenesis from studies in mammalian systems. We also discuss the possibilities of using Drosophila as a genetic model system to advance our understanding of players in fat biology.

Metabolic syndrome components in murine models

Animal models have enriched understanding of the physiological basis of metabolic disorders and advanced identification of genetic risk factors underlying the metabolic syndrome (MetS). Murine models are especially appropriate for this type of research, and are an excellent resource not only for identifying candidate genomic regions, but also for illuminating the possible molecular mechanisms or pathways affected in individual components of MetS. In this review, we briefly discuss findings from mouse models of metabolic disorders, particularly in light of issues raised by the recent flood of human genome-wide association studies (GWAS) results. We describe how mouse models are revealing that genotype interacts with environment in important ways, indicating that the underlying genetics of MetS is highly context dependant. Further we show that epistasis, imprinting and maternal effects each contribute to the genetic architecture underlying variation in metabolic traits, and mouse models provide an opportunity to dissect these aspects of the genetic architecture that are difficult if not impossible to ascertain in humans. Finally we discuss how knowledge gained from mouse models can be used in conjunction with comparative genomic methods and bioinformatic resources to inform human MetS research.

The contribution of animal models to the study of obesity

Obesity results from prolonged imbalance of energy intake and energy expenditure. Animal models have provided a fundamental contribution to the historical development of understanding the basic parameters that regulate the components of our energy balance. Five different types of animal model have been employed in the study of the physiological and genetic basis of obesity. The first models reflect single gene mutations that have arisen spontaneously in rodent colonies and have subsequently been characterized. The second approach is to speed up the random mutation rate artificially by treating rodents with mutagens or exposing them to radiation. The third type of models are mice and rats where a specific gene has been disrupted or over-expressed as a deliberate act. Such genetically-engineered disruptions may be generated through the entire body for the entire life (global transgenic manipulations) or restricted in both time and to certain tissue or cell types. In all these genetically-engineered scenarios, there are two types of situation that lead to insights: where a specific gene hypothesized to play a role in the regulation of energy balance is targeted, and where a gene is disrupted for a different purpose, but the consequence is an unexpected obese or lean phenotype. A fourth group of animal models concern experiments where selective breeding has been utilized to derive strains of rodents that differ in their degree of fatness. Finally, studies have been made of other species including non-human primates and dogs. In addition to studies of the physiological and genetic basis of obesity, studies of animal models have also informed us about the environmental aspects of the condition. Studies in this context include exploring the responses of animals to high fat or high fat/high sugar (Cafeteria) diets, investigations of the effects of dietary restriction on body mass and fat loss, and studies of the impact of candidate pharmaceuticals on components of energy balance. Despite all this work, there are many gaps in our understanding of how body composition and energy storage are regulated, and a continuing need for the development of pharmaceuticals to treat obesity. Accordingly, reductions in the use of animal models, while ethically desirable, will not be feasible in the short to medium term, and indeed an expansion in activity using animal models is anticipated as the epidemic continues and spreads geographically.

The role of the Agouti-Related Protein in energy balance regulation

The Agouti-Related Protein (AgRP) is a powerful orexigenic peptide that increases food intake when ubiquitously overexpressed or when administered centrally. AgRP-deficiency, on the other hand, leads to increased metabolic rate and a longer lifespan when mice consume a high fat diet. In humans, AgRP polymorphisms have been consistently associated with resistance to fatness in Blacks and Whites and resistance to the development of type-2 diabetes in African Blacks. Systemically administered AgRP accumulates in the liver, the adrenal gland and fat tissue while recent findings suggest that AgRP may also have inverse agonist effects, both centrally and peripherally. AgRP could thus modulate energy balance via different actions. Its absence or reduced functionality may offer a benefit both in terms of bringing about negative energy balance in obesigenic environments, as well as leading to an increased lifespan.

Positional cloning of "Lisch-Like", a candidate modifier of susceptibility to type 2 diabetes in mice

In 404 Lep^ob/ob F2 progeny of a C57BL/6J (B6) x DBA/2J (DBA) intercross, we mapped a DBA-related quantitative trait locus (QTL) to distal Chr1 at 169.6 Mb, centered about D1Mit110, for diabetes-related phenotypes that included blood glucose, HbA1c, and pancreatic islet histology. The interval was refined to 1.8 Mb in a series of B6.DBA congenic/subcongenic lines also segregating for Lep^ob. The phenotypes of B6.DBA congenic mice include reduced β-cell replication rates accompanied by reduced β-cell mass, reduced insulin/glucose ratio in blood, reduced glucose tolerance, and persistent mild hypoinsulinemic hyperglycemia. Nucleotide sequence and expression analysis of 14 genes in this interval identified a predicted gene that we have designated “Lisch-like” (Ll) as the most likely candidate. The gene spans 62.7 kb on Chr1qH2.3, encoding a 10-exon, 646–amino acid polypeptide, homologous to Lsr on Chr7qB1 and to Ildr1 on Chr16qB3. The largest isoform of Ll is predicted to be a transmembrane molecule with an immunoglobulin-like extracellular domain and a serine/threonine-rich intracellular domain that contains a 14-3-3 binding domain. Morpholino knockdown of the zebrafish paralog of Ll resulted in a generalized delay in endodermal development in the gut region and dispersion of insulin-positive cells. Mice segregating for an ENU-induced null allele of Ll have phenotypes comparable to the B.D congenic lines. The human ortholog, C1orf32, is in the middle of a 30-Mb region of Chr1q23-25 that has been repeatedly associated with type 2 diabetes.

Type 2 diabetes (T2D) accounts for over 90% of instances of diabetes and is a leading cause of medical morbidity and mortality. Twin studies indicate a strong polygenic contribution to susceptibility within the context of obesity. Although approximately ten genes making important contributions to individual risk have been identified, it is clear that others remain to be identified. In this study, we intercrossed obese, diabetes-resistant and diabetes-prone mouse strains to implicate a genetic interval on mouse Chr1 associated with reduced β-cell numbers and elevated blood glucose. We narrowed the region using molecular genetics and computational approaches to identify a novel gene we designated “Lisch-like” (Ll). The orthologous human genetic interval has been repeatedly implicated in T2D. Mice with an induced mutation that reduces Ll expression are impaired in both β-cell development and glucose metabolism, and reduced expression of the homologous gene in zebrafish disrupts islet development. Ll is expressed in organs implicated in the pathophysiology of T2D (hypothalamus, islets, liver, and skeletal muscle) and is predicted to encode a transmembrane protein that could mediate cholesterol transport and/or convey signals related to cell division. Either mechanism could mediate effects on β-cell mass that would predispose to T2D.

A genome-wide set of congenic mouse strains derived from CAST/Ei on a C57BL/6 background

We previously reported the construction of two sets of heterozygous congenic strains spanning the mouse genome. For both sets, C57BL/6J was employed as the background strain while DNA from either DBA/2 or CAST/Ei was introgressed to form the congenic region. We have subsequently bred most of these strains to produce homozygous breeding stocks. Here, we report the characterization of the strain set based on CAST/Ei. CAST/Ei is the most genetically distant strain within the Mus mus species and many trait variations relevant to common diseases have been identified in CAST/Ei mice. Despite breeding difficulties for some congenic regions, presumably due to incompatible allelic variations between CAST/Ei and C57BL/6, the resulting congenic strains cover about 80% of the autosomal chromosomes and will be useful as a resource for the further analysis of quantitative trait loci between the strains.

Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.

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.

Identification of quantitative trait loci that regulate obesity and serum lipid levels in MRL/MpJ x SJL/J inbred mice

The total body fat mass and serum concentration of total cholesterol, HDL cholesterol, and triglyceride (TG) differ between standard diet-fed female inbred mouse strains MRL/MpJ (MRL) and SJL/J (SJL) by 38-120% (P < 0.01). To investigate genetic regulation of obesity and serum lipid levels, we performed a genome-wide linkage analysis in 621 MRLx SJL F2 female mice. Fat mass was affected by two significant loci, D11Mit36 [43.7 cM, logarithm of the odds ratio (LOD) 11.2] and D16Mit51 (50.3 cM, LOD 3.9), and one suggestive locus at D7Mit44 (50 cM, LOD 2.4). TG levels were affected by two novel loci at D1Mit43 (76 cM, LOD 3.8) and D12Mit201 (26 cM, LOD 4.1), and two suggestive loci on chromosomes 5 and 17. HDL and cholesterol concentrations were influenced by significant loci on chromosomes 1, 3, 5, 7, and 17 that were in the regions identified earlier for other strains of mice, except for a suggestive locus on chromosome 14 that was specific to the MRL x SJL cross. In summary, linkage analysis in MRL x SJL F2 mice disclosed novel loci affecting TG, HDL, and fat mass, a measure of obesity. Knowledge of the genes in these quantitative trait loci will enhance our understanding of obesity and lipid metabolism.

Genetic analysis of diet-induced hypercholesterolemia in exogenously hypercholesterolemic rats

The exogenously hypercholesterolemic (ExHC) rat is an established strain that exhibits a polygenic syndrome of hypercholesterolemia after feeding on a cholesterol-containing diet, and the extent of this differs between male and female rats in the strain. The present study was performed to determine the genetic background of diet-induced hypercholesterolemia in ExHC rats. We used quantitative trait locus (QTL) analyses of the F2 progeny derived from ExHC and Brown-Norway rats. Rats were fed a diet containing 1% cholesterol, and a genome-wide scan was then performed. Significant QTLs for serum total cholesterol levels were revealed on chromosomes 5 and 14 in the vicinity of markers D5Rat95 and D14Rat43, having maximum logarithm of the odds scores of 6.0 and 5.8, respectively. A suggestive QTL for the trait was also detected on chromosome 3 at D3Rat140. In particular, the QTL on chromosome 5 was specific for female rats. These loci were novel QTLs for post-dietary serum total cholesterol levels. In addition, cross-mating analysis in F1 generations suggested that the responsiveness to dietary cholesterol in ExHC rats is partly attributable to X-linked inheritance. Identifying such genetic factors may be useful in predicting the risks associated with diet-induced hypercholesterolemia in humans.

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

Obesity is proving to be a serious health concern in the developed world as well as an unwanted component of growth in livestock production. While recent advances in genetics have identified a number of monogenic causes of obesity, these are responsible for only a small proportion of human cases of obesity. By divergent selection for high and low fat content over 60 generations, we have created Fat (F) and Lean (L) lines of mice that represent a model of polygenic obesity similar to the situation in human populations. From previous crosses of these lines, four body fat quantitative trait loci (QTL) were identified. We have created congenic lines (F(chr15L)), by recurrent marker-assisted backcrossing, to introgress the QTL region with the highest LOD score, Fob3 on Chr 15, from the L-Iine into the F-line background. We have further mapped this QTL by progeny testing of recombinants, produced from crosses between the F-line and congenic F(chrl5L) mice, showing that the Fob3 QTL region is a composite of at least two smaller effect QTL-the proximal QTL Fob3a is a late-onset obesity QTL, whereas the distal Fob3b is an early-onset obesity QTL.

Characterization of QTL with major effects on fatness and growth on mouse chromosome 2

OBJECTIVE

To isolate and characterize a region on mouse chromosome 2 harboring quantitative trait loci with large influences on growth and fatness.

RESEARCH METHODS AND PROCEDURES

A congenic line [M16i.B6-(D2Mit306-D2Mit52); MB2] was created using the polygenic obese M16i selection line as the recipient for an approximately 38-centimorgan region from C57BL/6J. Males and females from M16i and MB2 were compared for body weight, body composition, feed consumption, and additional traits at 6, 15, and 24 weeks. Interactions of genotype and environment (low and high dietary fat) were investigated. Males (8 weeks) were evaluated for fatty acid profiles in liver and for transcriptional profiles in liver and adipose.

RESULTS

Consequences of replacing M16i alleles with C57BL/6J alleles in MB2 were maximized at 15 weeks. MB2 mice were up to 15% lighter than M16i at this age, with no differences in feed consumption. As a percentage of body weight, MB2 had dramatically less epididymal (males) or perimetrial (females) fat (1.17% vs. 2.79% pooled across sex) and lower total lipids (16.1% vs. 23.3%) than M16i. Decreased adiposity in MB2 was not dependent on gender or diet. MB2 mice also had significant decreases in levels of leptin, insulin, and glucose, decreased de novo synthesis of hepatic fatty acid, and transcriptional changes for many genes both within, and external to, the congenic region.

DISCUSSION

Results confirm the presence and large effects of mouse chromosome 2 quantitative trait loci and further define their phenotypic consequences related to energy balance. The MB2 congenic line is a powerful resource for eventual identification of pathways and mutations within genes regulating predisposition to growth and obesity.

A large-sample QTL study in mice: I. Growth

By use of long-term selection lines for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted in mice to further understand the genetic architecture of complex polygenic traits. In combination with previous work, we conclude that QTL analysis has reinforced classic polygenic paradigms put in place prior to molecular analysis. Composite interval mapping revealed large numbers of QTL for growth traits with an exponential distribution of magnitudes of effects and validated theoretical expectations regarding gene action. Of particular significance, large effects were detected on Chromosome (Chr) 2. Regions on Chrs 1, 3, 6, 10, 11, and 17 also harbor loci with significant contributions to phenotypic variation for growth. Despite the large sample size, average confidence intervals of approximately 20 cM exhibit the poor resolution for initial estimates of QTL location. Analysis with genome-wide and chromosomal polygenic models revealed that, under certain assumptions, large fractions of the genome may contribute little to phenotypic variation for growth. Only a few epistatic interactions among detected QTL, little statistical support for gender-specific QTL, and significant age effects on genetic architecture were other primary observations from this study.

A large-sample QTL study in mice: II. Body composition

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from male F2 mice (n = 552) detected 50 QTL on 15 chromosomes impacting weights of various organ and adipose subcomponents of growth, including heart, liver, kidney, spleen, testis, and subcutaneous and epididymal fat depots. Nearly all aggregate growth QTL could be interpreted in terms of the organ and fat subcomponents measured. More than 25% of QTL detected map to MMU2, accentuating the relevance of this chromosome to growth and fatness in the context of this cross. Regions of MMU7, 15, and 17 also emerged as important obesity "hot-spots." Average degrees of directional dominance are close to additivity, matching expectations for body composition traits. A strong QTL congruency is evident among heart, liver, kidney, and spleen weights. Liver and testis are organs whose genetic architectures are, respectively, most and least aligned with that for aggregate body weight. In this study, growth and body weight are interpreted in terms of organ subcomponents underlying the macro aggregate traits, and anchored on the corresponding genomic locations.

Loci on chromosomes 2, 4, 9, and 16 for body weight, body length, and adiposity identified in a genome scan of an F2 intercross between the 129P3/J and C57BL/6ByJ mouse strains

Mice have proved to be a powerful model organism for understanding obesity in humans. Single gene mutants and genetically modified mice have been used to identify obesity genes, and the discovery of loci for polygenic forms of obesity in the mouse is an important next step. To pursue this goal, the inbred mouse strains 129P3/J (129) and C57BL/6ByJ (B6), which differ in body weight, body length, and adiposity, were used in an F2 cross to identify loci affecting these phenotypes. Linkages were determined in a two-phase process. In the first phase, 169 randomly selected F2 mice were genotyped for 134 markers that covered all autosomes and the X Chromosome (Chr). Significant linkages were found for body weight and body length on Chr 2. In addition, we detected several suggestive linkages on Chr 2 (adiposity), 9 (body weight, body length, and adiposity), and 16 (adiposity), as well as two suggestive sex-dependent linkages for body length on Chrs 4 and 9. In the second phase, 288 additional F2 mice were genotyped for markers near these regions of linkage. In the combined set of 457 F2 mice, six significant linkages were found: Chr 2 (Bwq5, body weight and Bdln3, body length), Chr 4 (Bdln6, body length, males only), Chr 9 (Bwq6, body weight and Adip5, adiposity), and Chr 16 (Adip9, adiposity), as well as several suggestive linkages (Adip2, adiposity on Chr 2, Bdln4 and Bdln5, body length on Chr 9). In addition, there was a suggestive linkage to body length in males on Chr 9 (Bdln4). For adiposity, there was evidence for epistatic interactions between loci on Chr 9 (Adip5) and 16 (Adip9). These results reinforce the concept that obesity is a complex trait. Genetic loci and their interactions, in conjunction with sex, age, and diet, determine body size and adiposity in mice.

The human obesity gene map: the 2002 update

This is the ninth update of the human obesity gene map, incorporating published results through October 2002 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 various animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. For the first time, transgenic and knockout murine models exhibiting obesity as a phenotype are incorporated (N = 38). As of October 2002, 33 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and the causal genes or strong candidates have been identified for 23 of these syndromes. QTLs reported from animal models currently number 168; there are 68 human QTLs for obesity phenotypes from genome-wide scans. Additionally, significant linkage peaks with candidate genes have been identified in targeted studies. Seven 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 222 studies reporting positive associations with 71 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. More than 300 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.

QTL analysis of self-selected macronutrient diet intake: fat, carbohydrate, and total kilocalories

The present study investigated the inheritance of dietary fat, carbohydrate, and kilocalorie intake traits in an F(2) population derived from an intercross between C57BL/6J (fat-preferring) and CAST/EiJ (carbohydrate-preferring) mice. Mice were phenotyped for self-selected food intake in a paradigm which provided for 10 days a choice between two macronutrient diets containing 78/22% of energy as a composite of either fat/protein or carbohydrate/protein. Quantitative trait locus (QTL) analysis identified six significant loci for macronutrient intake: three for fat intake on chromosomes (Chrs) 8 (Mnif1), 18 (Mnif2), and X (Mnif3), and three for carbohydrate intake on Chrs 17 (Mnic1), 6 (Mnic2), and X (Mnic3). An absence of interactions among these QTL suggests the existence of separate mechanisms controlling the intake of fat and carbohydrate. Two significant QTL for cumulative kilocalorie intake, adjusted for baseline body weight, were found on Chrs 17 (Kcal1) and 18 (Kcal2). Without body weight adjustment, another significant kcal locus appeared on distal Chr 2 (Kcal3). These macronutrient and kilocalorie QTL, with the exception of loci on Chrs 8 and X, encompassed chromosomal regions influencing body weight gain and adiposity in this F2 population. These results provide new insight into the genetic basis of naturally occurring variation in nutrient intake phenotypes.

Using mouse models to dissect the genetics of obesity

Mice have proved to be powerful models for understanding obesity in humans and farm animals. Single-gene mutants and genetically modified mice have been used successfully to discover genes and pathways that can regulate body weight. For polygenic obesity, the most common pattern of inheritance, many quantitative trait loci (QTLs) have been mapped in crosses between selected and inbred mouse lines. Most QTL effects are additive, and diet, age and gender modify the genetic effects. Congenic, recombinant inbred, advanced intercross, and chromosome substitution strains are needed to map QTLs finely, to identify the genes underlying the traits, and to examine interactions between them.

Diet-induced obesity and hepatic gene expression alterations in C57BL/6J and ICAM-1-deficient mice

The effects of high-fat feeding on the development of obesity were evaluated in intercellular adhesion molecule-1 (ICAM-1) knockout and C57BL/6J (B6) male mice fed a high-fat diet for < or =50 days. Serum and tissues were collected at baseline and after 1, 11, and 50 days on the diet. After 11 days on the diet, ICAM-1-deficient, but not B6, mice developed fatty livers and showed a significant increase in inguinal fat pad weight. At day 50, ICAM-1-deficient mice weighed less, and their adiposity index and circulating leptin levels were significantly lower than those of B6 controls. To better understand the early differential response to the diet, liver gene expression was analyzed at three time points by use of Affymetrix GeneChips. In both strains, a similar pattern of gene expression was detected in response to the high-fat diet. However, sterol regulatory element-binding protein-1, apolipoprotein A4, and adipsin mRNAs were significantly induced in ICAM-1-deficient livers, suggesting that these genes and their associated pathways may be involved in the acute diet response observed in the knockout mice.

Genome-tagged mice (GTM): two sets of genome-wide congenic strains

An important approach for understanding complex disease risk using the mouse is to map and ultimately identify the genes conferring risk. Genes contributing to complex traits can be mapped to chromosomal regions using genome scans of large mouse crosses. Congenic strains can then be developed to fine-map a trait and to ascertain the magnitude of the genotype effect in a chromosomal region. Congenic strains are constructed by repeated backcrossing to the background strain with selection at each generation for the presence of a donor chromosomal region, a time-consuming process. One approach to accelerate this process is to construct a library of congenic strains encompassing the entire genome of one strain on the background of the other. We have employed marker-assisted breeding to construct two sets of overlapping congenic strains, called genome-tagged mice (GTMs), that span the entire mouse genome. Both congenic GTM sets contain more than 60 mouse strains, each with on average a 23-cM introgressed segment (range 8 to 58 cM). C57BL/6J was utilized as a background strain for both GTM sets with either DBA/2J or CAST/Ei as the donor strain. The background and donor strains are genetically and phenotypically divergent. The genetic basis for the phenotypic strain differences can be rapidly mapped by simply screening the GTM strains. Furthermore, the phenotype differences can be fine-mapped by crossing appropriate congenic mice to the background strain, and complex gene interactions can be investigated using combinations of these congenics.

Nutrient preference and diet-induced adiposity in C57BL/6ByJ and 129P3/J mice

Purified carbohydrates and fats are usually palatable to humans and other animals, and their consumption often induces weight gain and accumulation of fat. In this study, we examined consumption of complex carbohydrates (cornstarch and Polycose) and fats (soybean oil and margarine) in mice from two inbred strains, C57BL/6ByJ and 129P3/J. At lower concentrations of liquid nutrients tested using two-bottle tests, when the amounts consumed had negligible energy content, the C57BL/6ByJ mice had higher acceptance of Polycose and soybean oil. This was probably due to strain differences in chemosensory perception of Polycose and oil. At higher concentrations, the mice consumed a substantial part of their daily energy from the macronutrient sources, however, there were no or only small strain differences in nutrient consumption. These small differences were probably due to strain variation in body size. The two strains also did not differ in chow intake. Despite similar energy intakes, access to the nutrients resulted in greater body weight (BW) gain in the C57BL/6ByJ mice than in the 129P3/J mice. The diet-induced weight gain was examined in detail in groups of 2-month-old C57BL/6ByJ and 129P3/J mice given ether chow, or chow and margarine to eat. Access to margarine did not increase total energy consumption of either strain. It increased BW and adiposity of the C57BL/6ByJ mice, but only after they reached the age of approximately 3 months. There were no differences in BW and adiposity between control and margarine-exposed 129P3/J mice. The results suggest that diet-induced adiposity in the B6 mice depends on age and does not depend on hyperphagia.

The future of obesity research

As endocrinologists, we view better treatment as the goal of obesity research. The ideal obesity treatment would reduce body fat substantially, with preferential loss from the visceral compartment, and preserve lean tissue with a minimum of side effects. Obesity has been recognized as a chronic disease since 1985. Chronic diseases recognized before obesity may predict the future of obesity research. Initial treatments of chronic diseases commonly arise from empirical observations. These observations often stimulate basic research into the physiologic mechanisms responsible. Such cross-fertilization between the clinic and basic science is desirable and expected. As more is learned about the physiology of obesity, treatments can be expected to use more downstream mechanisms with less unwanted side effects, the reliance on surgical treatments can be expected to decline, and molecular approaches are likely to play an increasingly important role. With a better physiologic understanding of obesity, advanced clinical endpoints will become more important and molecular approaches are likely to play a more important role in discovery and treatment. Due to the availability of molecular approaches, obesity treatment is expected to advance faster than chronic disease research of the past.

Gene expression in hypothalamus and brown adipose tissue of mice divergently selected for heat loss

Gene expression was evaluated in mice divergently selected for 16 generations for heat loss, measured by direct calorimetry. The high (MH) heat loss line has approximately 50% greater heat loss, approximately 35% less body fat, approximately 20% greater feed intake, and twofold greater activity levels than the low (ML) heat loss line. At 11 wk, inbred males (developed from MH and ML) were euthanized 3 h after dark for dissection of tissues and extraction of RNA. Differential display PCR (DD-PCR) was used to evaluate transcriptional differences between lines in hypothalamus and brown adipose tissue (BAT). Evaluation was replicated within and across lines, using family pools of mRNA. Two genes were confirmed by competitive RT-PCR and/or Northern analysis to have greater levels of mRNA present in ML relative to MH mice. In both hypothalamus and BAT, the ribosomal protein L3 (RPL3) gene was expressed at higher levels in ML, whereas an unknown expressed sequence tag (EST) was also found at higher levels in the hypothalamus of ML mice. These results implicate RPL3 in regulation of energy balance and extend the genetic dissection of response to selection to the transcriptional level.

Microsatellite marker panels for use in high-throughput genotyping of mouse crosses

Several microsatellite genotyping panel sets have been developed that are polymorphic between C57BL/6J and CAST/Ei mice, or C57BL/6J and DBA/2J. One set of markers for each strain pair has an intermarker distance of approximately 20 cM, and a second set has an intermarker distance of 5 cM. The 20-cM set contains 105 markers for C57BL/6J x DBA/2J and 108 for C57BL/6J x CAST/Ei, divided into 13 panels. Each 5-cM set includes 350 markers arranged into 45 panels. A panel contains a number of primer pairs whose fluorescently labeled PCR products can be pooled together and separated on one lane of a polyacrylamide gel. The sets are arranged by the size of the PCR product and by the type of fluorescent dye; 5-cM sets are also arranged by chromosomal region. The 20-cM sets are most useful for full-genome scans, the 5-cM sets are useful for full-genome and/or for region-specific chromosome screens. Both sets were proven as useful tools for speed congenic development, quantitative trait loci (QTL) analysis and physical mapping. These panel sets provide a throughput of 1,536-2,304 mouse genotypes daily per one gel-based system. Whole genome scans of one animal require 13 or 48 gel lanes, with 20 cM or 5 cM density, respectively.

Mouse genetics/genomics: an effective approach for drug target discovery and validation

The mouse has become the premier mammalian system for the identification of the genetic basis of both mono- and oligogenic disorders, as well as the understanding of complex diseases with gene-gene and gene-environment interactions. The similarity between human and mouse genetic disease is sometimes striking, while in other cases the phenotypes are less similar. The ability to genetically map and then clone single gene disorders rapidly, and the emerging technologies that will allow the economical identification of the polygenes controlling quantitative traits further demonstrate the utility of the mouse as a model for gene discovery. Additionally, the ability to genetically manipulate the mouse through transgenesis and gene targeting allows for the testing of hypotheses regarding specific gene function and their role in disease. The utility of the mouse extends beyond being just a gene discovery tool to provide prevalidated targets. It can also be used for the development of animal models, and the testing of compounds in specifically constructed transgenic and knockout strains to further define the target and pathway of a therapeutic compound.

Genetics of body-weight regulation

The role of genetics in obesity is twofold. Studying rare mutations in humans and model organisms provides fundamental insight into a complex physiological process, and complements population-based studies that seek to reveal primary causes. Remarkable progress has been made on both fronts, and the pace of advance is likely to accelerate as functional genomics and the human genome project expand and mature. Approaches based on mendelian and quantitative genetics may well converge, and lead ultimately to more rational and selective therapies.

Macronutrient diet selection in thirteen mouse strains

The strain distribution for macronutrient diet selection was described in 13 mouse strains (AKR/J, NZB/B1NJ, C57BL/6J, C57BL/6ByJ, DBA/2J, SPRET/Ei, CD-1, SJL/J, SWR/J, 129/J, BALB/cByJ, CAST/Ei, and A/J) with the use of a self-selection protocol in which separate carbohydrate, fat, and protein diets were simultaneously available for 26-30 days. Relative to carbohydrate, nine strains consumed significantly more calories from the fat diet; two strains consumed more calories from carbohydrate than from fat (BALB/cByJ, CAST/Ei). Diet selection by SWR/J mice was variable over time, resulting in a lack of preference. One strain (A/J) failed to adapt to the diet paradigm due to inadequate protein intake. Comparisons of proportional fat intake across strains revealed that fat selection/consumption ranged from 26 to 83% of total energy. AKR/J, NZB/B1NJ, and C67BL/6J mice self-selected the highest proportion of dietary fat, whereas the CAST/Ei and BALB/cByJ strains chose the lowest. Finally, epididymal fat depot weight was correlated with fat consumption. There were significant positive correlations in AKR/J and C57BL/6J mice, which are highly sensitive to dietary obesity. However, absolute fat intake was inversely correlated with epididymal fat in two of the lean strains: SWR/J and CAST/Ei. We hypothesize that the SWR/J and CAST/Ei strains are highly sensitive to a negative feedback signal generated by increasing body fat, but the AKR/J and C67BL/6J mice are not. The variation in dietary fat selection across inbred strains provides a tool for dissecting the complex genetics of this trait.

The human obesity gene map: the 1999 update

This report constitutes the sixth update of the human obesity gene map incorporating published results up to the end of October 1999. Evidence from the rodent and human obesity cases caused by single gene mutations, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTL) uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, pig and chicken models, association and linkage studies with candidate genes and other markers is reviewed. Twenty-five human cases of obesity can now be explained by variation in five genes. Twenty Mendelian disorders exhibiting obesity as one of their clinical manifestations have now been mapped. The number of different QTLs reported from animal models reaches now 98. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 89 reports of positive associations pertaining to 40 candidate genes. Finally, 44 loci have linked to obesity indicators in genomic scans and other linkage study designs. The obesity gene map depicted in Figure 1 reveals that putative loci affecting obesity-related phenotypes can be found on all autosomes, with chromosomes 14 and 21 showing each one locus only. The number of genes, markers, and chromosomal regions that have been associated or linked with human obesity phenotypes continues to increase and is now well above 200.

Mapping genes that control hormone-induced ovulation rate in mice

The present study mapped quantitative trait loci (QTL) that control 6-fold genetic differences in hormone-induced ovulation rate (HIOR) between C57BL/6J (B6) (HIOR = 54) and A/J strain mice (HIOR = 9). (The gene name is Ovulation Rate Induced [ORI] QTL and the gene symbol is Oriq.) QTL linkage analysis was conducted on 167 (B6xA)xA backcross mice at 165 loci. Suggestive B6 ORI QTL that control the number of eggs in cumulus mapped, as follows, near: Cyp19 and D9Mit4 on chromosome (Chr) 9 (Oriq1); D2Mit433 on Chr2 (Oriq2); D6Mit316 on Chr6 (Oriq3); DXMit22 on ChrX (Oriq4) and were associated with a 2.7, 2.7, 2.6, and 4.2 egg increases in HIOR, respectively. Oriq3 was significant (LOD = 3.45) based on composite interval mapping. QTL linkage analysis of the number of eggs matured by endogenous gonadotropins and ovulated by eCG mapped a significant Oriq5 to Chr 10 and suggestive Oriq to Chr 6, 7, and X. These data provide the first molecular genetic markers for reproductive QTL that control major differences in ovarian responsiveness to gonadotropins. These and closely linked syntenic molecular markers will enable a more accurate prediction of ovarian responsiveness to gonadotropins and provide selection criteria for improving reproductive performance in diverse mammalian species.

The human obesity gene map: the 1998 update

An update of the human obesity gene map incorporating published results up to the end of October 1998 is presented. Evidence from the human obesity cases caused by single gene mutations; other Mendelian disorders exhibiting obesity as a clinical feature; quantitative trait loci uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, and pig models; association and case-control studies with candidate genes; and linkage studies with genes and other markers is reviewed. The most noticeable changes from the 1997 update is the number of obesity cases due to single gene mutations that increased from three cases due to mutations in two genes to 25 cases due to 12 mutations in seven genes. A look at the obesity gene map depicted in Figure 1 reveals that putative loci affecting obesity-related phenotypes are found on all but chromosome Y of the human chromosomes. Some chromosomes show at least three putative loci related to obesity on both arms (1, 2, 3, 6, 7, 8, 9, 11, 17, 19, 20, and X) and several on one chromosome arm only (4q, 5q, 10q, 12q, 13q, 15q, 16p, and 22q). The number of genes and other markers that have been associated or linked with human obesity phenotypes is increasing very rapidly and now approaches 200.

Genome scan for human obesity and linkage to markers in 20q13

Obesity is a highly prevalent, multigenic trait that predicts increased morbidity and mortality. Here we report results from a genome scan based on 354 markers in 513 members of 92 nuclear families ascertained through extreme obesity and normal body weight. The average marker interval was approximately 10 cM. We examined four correlated obesity phenotypes, including the body-mass index (BMI) (both as a quantitative trait and as a discrete trait with a threshold of BMI > or /=30 kg/m2) and percentage of fat (both as a quantitative trait and as a discrete trait with a threshold of 40%) as assessed by bioelectrical impedance. In the initial stage of the genome scan, four markers in 20q gave positive evidence for linkage, which was consistent across most obesity phenotypes and analytic methods. After saturating 20q with additional markers (25 markers total) in an augmented sample of 713 members from 124 families, we found linkage to several markers in a region, 20q13, previously implicated in both human and animal studies. Three markers (D20S107, D20S211, and D20S149) in 20q13 had empirical P values (based on Monte Carlo simulations, which controlled for multiple testing) < or /=. 01 for single-point analysis. In addition, the parametric, affecteds-only analysis for D20S476 yielded a LOD score of 3.06 (P=. 00009), and the affected-sib-pair test yielded a LOD score of 3.17 (P=.000067). Multipoint analyses further strengthened and localized these findings. This region includes several plausible candidate genes for obesity. Our results suggest that one or more genes affecting obesity are located in 20q13.

Test of candidate gene--quantitative trait locus association applied to fatness in mice

We test for the contribution of five strong candidate genes for obesity to quantitative variation for fatness in mice. The candidate loci are known through their major mutant phenotypes. We propose a randomization test for overall contribution of candidate genes, based on the empirical distribution of LOD scores from a quantitative trait locus (QTL) genome scan. The test is applied to data on body fat content and male gonadal fatpad weight from a QTL genome scan with an F2 population of C57BL/6J and DBA/2J inbred mice. The test is nonsignificant in this experiment for overall body fat content. QTLs detected at an experiment-wide significance level on chromosome 4, 6, 13 and 15 have effects on mean fatness of up to 19% between the homozygotes, but map to locations where there is no strong candidate gene. The test is significant for gonadal fat pad weight in males, and gives weak support for an association with the diabetes gene.

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.

The human obesity gene map: the 1997 update

An update of the human obesity gene map incorporating published results up to October 1997 is presented. Evidence from Mendelian disorders exhibiting obesity as a clinical feature; single-gene mutation rodent models; quantitative trait loci uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, and pig models; association and case-control studies with candidate genes; and linkage studies with genes and other markers is reviewed. All chromosomal locations of the animal loci are converted into human genome locations based on syntenic relationships between the genomes. A complete listing of all of these loci reveals that all but chromosome Y of the 24 human chromosomes are represented. Some chromosomes show at least three putative loci related to obesity on both arms (1, 2, 6, 8, 11, and 20) and several on one chromosome arm only (3p, 4q, 5q, 7q, 12q, 13q, 15q, 15p, 22q, and Xq). Studies reporting negative association and linkage results are also listed, with the exception of the unlinked markers from genome-wide scans.

Theoretical and empirical issues for marker-assisted breeding of congenic mouse strains

Congenic breeding strategies are becoming increasingly important as a greater number of complex trait linkages are identified. Traditionally, the development of a congenic strain has been a time-consuming endeavour, requiring ten generations of backcrosses. The recent advent of a dense molecular genetic map of the mouse permits methods that can reduce the time needed for congenic-strain production by 18-24 months. We present a theoretical evaluation of marker-assisted congenic production and provide the empirical data that support it. We present this 'speed congenic' method in a user-friendly manner to encourage other investigators to pursue this or similar methods of congenic production.

Mapping of mouse obesity genes: A generic approach to a complex trait

Identification of genes underlying any complex trait such as obesity is an important and difficult problem in genetics. Traditional candidate gene approaches cannot be relied on to identify all of the genes influencing a complex trait, and positional cloning is very laborious. With the advent of new tools and methods, however, comprehensive approaches to the identification of any genes underlying complex traits are now available. Quantitative trait locus (QTL) mapping is a general technique to map Mendelian factors influencing complex traits. The QTL approach involves the crossing of two strains that differ in the trait of interest to produce F2 or back-cross progeny, individually phenotyping and genotyping each progeny, and statistically associating the typed markers and the phenotype. QTL mapping has been used in the last 4 years to map genes for a wide variety of traits, including body weight and growth, obesity, atherosclerosis and susceptibility to cancer in the mouse, and hypertension, hyperactivity and arthritis in the rat. QTL mapping has also been used to map genes in pigs, poultry, cows, fish and plants. Once a trait has been located in a chromosomal subregion, identifying the underlying gene remains a significant problem. A monogenic model must be developed, isolating one gene influencing a trait from other genes affecting the same phenotype. Then the positional candidate strategy, which relies on a combination of mapping to a chromosomal subregion followed by a survey of the interval to see if attractive candidates reside there, becomes practical.

The human obesity gene map: the 1996 update

An update of the human obesity gene map up to October 1996 is presented. Evidence from Mendelian disorders exhibiting obesity as a clinical feature, single-gene mutation rodent models, quantitative trait loci uncovered in crossbreeding experiments with mouse, rat, and pig models, association and case-control studies with candidate genes, and linkage studies with genes and other markers is reviewed. All chromosomal locations of the animal loci are converted into human genome locations based on syntenic relationships between the genomes. A complete listing of all these loci reveals that only 4 of the 24 human chromosomes are not yet represented, i.e., 9, 18, 21, and Y. Several chromosome arms are characterized by the presence of several putative loci. The following arms include at least three such loci: 1p, 1q, 3p, 4q, 6p, 7q, 8p, 8q, 11p, 11q, 15q, 20q, and Xq. Studies with negative association and linkage results are also reviewed.