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Publication : Quantitative trait Loci for regional adiposity in mouse lines divergently selected for food intake.

First Author  Rance KA Year  2007
Journal  Obesity (Silver Spring) Volume  15
Issue  12 Pages  2994-3004
PubMed ID  18198308 Mgi Jnum  J:131441
Mgi Id  MGI:3773747 Doi  10.1038/oby.2007.357
Citation  Rance KA, et al. (2007) Quantitative trait Loci for regional adiposity in mouse lines divergently selected for food intake. Obesity (Silver Spring) 15(12):2994-3004
abstractText  OBJECTIVE: Obesity is thought to result from an interaction between genotype and environment. Excessive adiposity is associated with a number of important comorbidities; however, the risk of obesity-related disease varies with the distribution of fat throughout the body. The aim of this study was to map quantitative trait loci (QTLs) associated with regional fat depots in mouse lines divergently selected for food intake corrected for body mass. RESEARCH METHODS AND PROCEDURES: Using an F2 intercross design (n = 457), the dry mass of regional white (subcutaneous, gonadal, retroperitoneal, and mesenteric) adipose tissue (WAT) and brown adipose tissue (BAT) depots were analyzed to map QTLs. RESULTS: The total variance explained by the mapped QTL varied between 12% and 39% for BAT and gonadal fat depots, respectively. Using the genome-wide significance threshold, nine QTLs were associated with multiple fat depots. Chromosomes 4 and 19 were associated with WAT and BAT and chromosome 9 with WAT depots. Significant sex x QTL interactions were identified for gonadal fat on chromosomes 9, 16, and 19. The pattern of QTLs identified for the regional deposits showed the most similarity between retroperitoneal and gonadal fat, whereas BAT showed the least similarity to the WAT depots. Analysis of total fat mass explained in excess of 40% of total variance. DISCUSSION: There was limited concordance between the QTLs mapped in our study and those reported previously. This is likely to reflect the unique nature of the mouse lines used. Results provide an insight into the genetic basis of regional fat distribution.
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