The Tas1r3 gene encodes the T1R3 receptor protein, which is involved in sweet taste transduction. To characterize ligand specificity of the T1R3 receptor and the genetic architecture of sweet taste responsiveness, we analyzed taste responses of 129.B6-Tas1r3 congenic mice to a variety of chemically diverse sweeteners and glucose polymers with three different measures: consumption in 48-h two-bottle preference tests, initial licking responses, and responses of the chorda tympani nerve. The results were generally consistent across the three measures. Allelic variation of the Tas1r3 gene influenced taste responsiveness to nonnutritive sweeteners (saccharin, acesulfame-K, sucralose, SC-45647), sugars (sucrose, maltose, glucose, fructose), sugar alcohols (erythritol, sorbitol), and some amino acids (D-tryptophan, D-phenylalanine, L-proline). Tas1r3 genotype did not affect taste responses to several sweet-tasting amino acids (L-glutamine, L-threonine, L-alanine, glycine), glucose polymers (Polycose, maltooligosaccharide), and nonsweet NaCl, HCl, quinine, monosodium glutamate, and inosine 5'-monophosphate. Thus Tas1r3 polymorphisms affect taste responses to many nutritive and nonnutritive sweeteners (all of which must interact with a taste receptor involving T1R3), but not to all carbohydrates and amino acids. In addition, we found that the genetic architecture of sweet taste responsiveness changes depending on the measure of taste response and the intensity of the sweet taste stimulus. Variation in the T1R3 receptor influenced peripheral taste responsiveness over a wide range of sweetener concentrations, but behavioral responses to higher concentrations of some sweeteners increasingly depended on mechanisms that could override input from the peripheral taste system.

Obesity is a heritable trait caused by complex interactions between genes and environment, including diet. Gene-by-diet interactions are difficult to study in humans because the human diet is hard to control. Here, we used mice to study dietary obesity genes, by four methods. First, we bred 213 F2 mice from strains that are susceptible [C57BL/6ByJ (B6)] or resistant [129P3/J (129)] to dietary obesity. Percent body fat was assessed after mice ate low-energy diet and again after the same mice ate high-energy diet for 8 weeks. Linkage analyses identified QTLs associated with dietary obesity. Three methods were used to filter candidate genes within the QTL regions: (a) association mapping was conducted using >40 strains; (b) differential gene expression and (c) comparison of genomic DNA sequence, using two strains closely related to the progenitor strains from Experiment 1. The QTL effects depended on whether the mice were male or female or which diet they were recently fed. After feeding a low-energy diet, percent body fat was linked to chr 7 (LOD = 3.42). After feeding a high-energy diet, percent body fat was linked to chr 9 (Obq5; LOD = 3.88), chr 12 (Obq34; LOD = 3.88), and chr 17 (LOD = 4.56). The Chr 7 and 12 QTLs were sex dependent and all QTL were diet-dependent. The combination of filtering methods highlighted seven candidate genes within the QTL locus boundaries: Crx, Dmpk, Ahr, Mrpl28, Glo1, Tubb5, and Mut. However, these filtering methods have limitations so gene identification will require alternative strategies, such as the construction of congenics with very small donor regions.

Effects of gustatory nerve transection on salt taste have been studied extensively in rats and hamsters but have not been well explored in the mouse. We examined the effects of chorda tympani (CT) nerve transection on NaCl taste preferences and thresholds in outbred CD-1 mice using a high-throughput phenotyping method developed in our laboratory. To measure taste thresholds, mice were conditioned by oral self-administration of LiCl or NaCl and then presented with NaCl concentration series in 2-bottle preference tests. LiCl-conditioned and control NaCl-exposed mice were given bilateral transections of the CT nerve (LiCl-CTX, NaCl-CTX) or were left intact as controls (LiCl-CNT, NaCl-CNT). After recovery from surgery, mice received a concentration series of NaCl (0–300 mM) in 48-h 2-bottle tests. CT transection increased NaCl taste thresholds in LiCl-conditioned mice and eliminated avoidance of concentrated NaCl in control NaCl-exposed mice. This demonstrates that in mice, the CT nerve is important for detection and recognition of NaCl taste and is necessary for the normal avoidance of high concentrations of NaCl. The results of this experiment also show that the method of high-throughput phenotyping of salt taste thresholds is suitable for detecting changes in the taste periphery in mouse genetic studies.

Genetic variation contributes to individual differences in obesity, but defining the exact relationships between naturally occurring genotypes and their effects on fatness remains elusive. As a step toward positional cloning of previously identified body composition quantitative trait loci (QTLs) from F2 crosses of mice from the C57BL/6ByJ and 129P3/J inbred strains, we sought to recapture them on a homogenous genetic background of consomic (chromosome substitution) strains. Male and female mice from reciprocal consomic strains originating from the C57BL/6ByJ and 129P3/J strains were bred and measured for body weight, length, and adiposity. Chromosomes 2, 7, and 9 were selected for substitution because previous F2 intercross studies revealed body composition QTLs on these chromosomes. We considered a QTL confirmed if one or both sexes of one or both reciprocal consomic strains differed significantly from the host strain in the expected direction after correction for multiple testing. Using these criteria, we confirmed two of two QTLs for body weight (Bwq5-6), three of three QTLs for body length (Bdln3-5), and three of three QTLs for adiposity (Adip20, Adip26 and Adip27). Overall, this study shows that despite the biological complexity of body size and composition, most QTLs for these traits are preserved when transferred to consomic strains; in addition, studying reciprocal consomic strains of both sexes is useful in assessing the robustness of a particular QTL.

Male and female Microtus ochrogaster were presented with anesthetized and awake conspecifics while ultrasonic vocalizations (USVs) were monitored. Males produced significantly more USVs than females during 5-min testing sessions. Males tended to produce more USVs to unfamiliar females than to familiar female siblings. Sexual experience led to increased USV scores by males. These results suggest that USVs by male prairie voles communicate to females the male's gender and his availability for reproductive behavior.

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.

To fine map a mouse QTL for lean body mass (Burly1), we used information from intercross, backcross, consomic, and congenic mice derived from the C57BL/6ByJ (host) and 129P3/J (donor) strains. The results from these mapping populations were concordant and showed that Burly1 is located between 151.9 and 152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. The congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. Of the protein-coding genes, 7 have missense variants, including genes that may contribute to lean body weight, such as Angpt41, Slc52c3, and Rem1. Lean body mass was increased by the B6-derived variant relative to the 129-derived allele. Burly1 influenced lean body weight at all ages but not food intake or locomotor activity. However, congenic mice with the B6 allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs and to identify a short list of candidate genes.

Our goal was to fine map a mouse QTL for lean body mass (Burly1) using information from several populations including newly created congenic mice derived from the B6 (host) and 129 (donor) strains. The results from each mapping population were concordant and showed that Burly1 is likely a single QTL in a 0.8-Mb region at 151.9-152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. Results from mice of all the mapping populations we studied including intercrossed, backcrossed, consomic, and congenic strains indicate that lean body mass was increased by the B6-derived allele relative to the 129-derived allele. We determined that the congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. The effect of the Burly1 locus on lean body weight was apparent at all ages measured and did not affect food intake or locomotor activity. However, congenic mice with the B6-allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs. peer-reviewed)