Identification of quantitative trait loci influencing traits related to energy balance in selection and inbred lines of mice.

Energy balance is a complex trait with relevance to the study of human obesity and maintenance energy requirements of livestock. The objective of this study was to identify, using unique mouse models, quantitative trait loci (QTL) influencing traits that contribute to variation in energy balance. Two F2 resource populations were created from lines of mice differing in heat loss measured by direct calorimetry as an indicator of energy expenditure. The HB F2 resource population originated from a cross between a noninbred line selected for high heat loss and an inbred line with low heat loss. Evidence for significant QTL influencing heat loss was found on chromosomes 1, 2, 3, and 7. Significant QTL influencing body weight and percentage gonadal fat, brown fat, liver, and heart were also identified. The LH F2 resource population originated from noninbred lines of mice that had undergone divergent selection for heat loss. Chromosomes 1 and 3 were evaluated. The QTL for heat loss identified on chromosome 1 in the HB population was confirmed in the LH population, although the effect was smaller. The presence of a QTL influencing 6-wk weight was also confirmed. Suggestive evidence for additional QTL influencing heat loss, percentage subcutaneous fat, and percentage heart was found for chromosome 1.

[1]  T. Shows,et al.  Mapping thyrotropin β subunit gene in man and mouse , 1986 .

[2]  Steven A. Thomas,et al.  Thermoregulatory and metabolic phenotypes of mice lacking noradrenaline and adrenaline , 1997, nature.

[3]  M. K. Nielsen,et al.  Genetic variation in liver mass, body mass, and liver:body mass in mice. , 1992, Journal of animal science.

[4]  Hitoshi Yamashita,et al.  Mice lacking mitochondrial uncoupling protein are cold-sensitive but not obese , 1997, nature.

[5]  Christophe Fleury,et al.  Uncoupling protein-2: a novel gene linked to obesity and hyperinsulinemia , 1997, Nature Genetics.

[6]  J. Himms-Hagen,et al.  Role of thermogenesis in the regulation of energy balance in relation to obesity. , 1989, Canadian journal of physiology and pharmacology.

[7]  Z B Zeng,et al.  Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Y. Chagnon,et al.  Linkage between markers in the vicinity of the uncoupling protein 2 gene and resting metabolic rate in humans. , 1997, Human molecular genetics.

[9]  W. Coward,et al.  Energy expenditure and intake in infants born to lean and overweight mothers. , 1988, The New England journal of medicine.

[10]  C. Haley,et al.  Mapping quantitative trait loci in crosses between outbred lines using least squares. , 1994, Genetics.

[11]  E. Lander,et al.  Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results , 1995, Nature Genetics.

[12]  B. Taylor,et al.  Detection of obesity QTLs on mouse chromosomes 1 and 7 by selective DNA pooling. , 1996, Genomics.

[13]  C. Bouchard,et al.  Genetic pleiotropy for resting metabolic rate with fat-free mass and fat mass: the Québec Family Study. , 1996, Obesity research.

[14]  M. Ehm,et al.  Autosomal genomic scan for loci linked to obesity and energy metabolism in Pima Indians. , 1998, American journal of human genetics.

[15]  M. Nakamura,et al.  Cloning and functional expression of a cDNA encoding a mouse type 2 neuropeptide Y receptor. , 1996, Biochimica et biophysica acta.

[16]  E. Saltzman,et al.  The role of energy expenditure in energy regulation: findings from a decade of research. , 2009, Nutrition reviews.

[17]  A. Stunkard,et al.  Metabolic rate and physical development in children at risk of obesity , 1990, The Lancet.

[18]  R. Doerge,et al.  Empirical threshold values for quantitative trait mapping. , 1994, Genetics.

[19]  A. Cassard-Doulcier,et al.  In vitro interactions between nuclear proteins and uncoupling protein gene promoter reveal several putative transactivating factors including Ets1, retinoid X receptor, thyroid hormone receptor, and a CACCC box-binding protein. , 1994, The Journal of biological chemistry.

[20]  D. Pomp.  Genetic Dissection of Obesity in Polygenic Animal Models , 1997, Behavior genetics.

[21]  D. E. Moody,et al.  Variability in metabolic rate, feed intake and fatness among selection and inbred lines of mice. , 1997, Genetical research.

[22]  M. K. Nielsen,et al.  Divergent selection for heat loss in mice: II. Correlated responses in feed intake, body mass, body composition, and number born through fifteen generations. , 1997, Journal of animal science.

[23]  B. Lowell,et al.  UCP3: an uncoupling protein homologue expressed preferentially and abundantly in skeletal muscle and brown adipose tissue. , 1997, Biochemical and biophysical research communications.

[24]  D. Falconer,et al.  Introduction to Quantitative Genetics. , 1962 .

[25]  B. Dujon,et al.  The nucleotide sequence of Saccharomyces cerevisiae chromosome VII. , 1997, Nature.

[26]  C. Haley,et al.  A simple regression method for mapping quantitative trait loci in line crosses using flanking markers , 1992, Heredity.

[27]  O. Boss,et al.  Uncoupling protein‐3: a new member of the mitochondrial carrier family with tissue‐specific expression , 1997, FEBS letters.

[28]  B V Howard,et al.  Reduced rate of energy expenditure as a risk factor for body-weight gain. , 1988, The New England journal of medicine.

[29]  D. Pomp,et al.  Quantitative genetics of energy balance--lessons from animal models. , 1999, Obesity research.

[30]  L. Andersson,et al.  Genetic mapping of quantitative trait loci for growth and fatness in pigs. , 1994, Science.

[31]  E. Lander,et al.  Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. , 1989, Genetics.

[32]  S. Woods,et al.  Signals that regulate food intake and energy homeostasis. , 1998, Science.

[33]  J. Deshazer,et al.  Divergent selection for heat loss in mice: I. Selection applied and direct response through fifteen generations. , 1997, Journal of animal science.