Fine-Mapping Gene-by-Diet Interactions on Chromosome 13 in a LG/J × SM/J Murine Model of Obesity

Abstract

Obesity is one of the most serious threats to human health today. Although there is general agreement that environmental factors such as diet have largely caused the current obesity pandemic, the environmental changes have not affected all individuals equally. To model gene-by-environment interactions in a mouse model system, our group has generated an F 16 advanced intercross line (AIL) from the SM/J and LG/J inbred strains. Half of our sample was fed a low-fat (15% energy from fat) diet while the other half was fed a high-fat (43% energy from fat) diet. The sample was assayed for a variety of obesity-and diabetes-related phenotypes such as growth rate, response to glucose challenge, organ and fat pad weights, and serum lipids and insulin. An examination in the F 16 sample of eight adiposity quantitative trait loci previously identified in an F 2 intercross of SM/J and LG/J mouse strains reveals locus-by-diet interactions for all previously mapped loci. Adip7, located on proximal chromosome 13, demonstrated the most interactions and therefore was selected for fine mapping with microsatellite markers. Three phenotypic traits, liver weight in male animals, serum insulin in male animals, and reproductive fat pad weight, show locus-by-diet interactions in the 127-kb region between markers D13Mit1 and D13Mit302. The phosphofructokinase (PFK) C (Pfkp) and the pitrilysin metalloprotease 1 (Pitrm1) genes are compelling positional candidate genes in this region that show coding sequence differences between the parental strains in functional domains. Diabetes 54:1863-1872, 2005 E stimates of the heritability of obesity in humans range as high as 70% based on twin studies (1). However, obesity in the developed world is increasing too rapidly to be caused by changes in genetic background (2). Moreover, some human genotypes are apparently resistant to an obesogenic environment and do not become obese (3). Genotype-byenvironment interactions such as these have long been of concern to evolutionary biologists and have been commonly noted as important for evolutionary processes (4 -6). Likewise, gene-by-diet interactions are known to influence obesity-and diabetes-related traits in humans (7-9).The elucidation of the biochemistry of appetite control in mouse models generally depends on transgenic or knockout mice (7-8). Because of the complexity of the obese phenotype, it is unlikely that all gene-by-environment interactions will be discovered using these methods (9). Human studies examining gene-by-diet interactions rely on epidemiological data collected from large samples (10 -12). While these and other studies make valuable contributions to our understanding of gene-by-diet interactions, large-scale human studies can be difficult due to unknown genetic lineages (13) as well as data collection biases (11).With carefully controlled lineages and environments, samples derived from inbred mouse strains are amenable to powerful statistical dissection of complex genetic and environmental interactions (15). Crosses derived from the ...

Quantitative Trait Loci for Obesity- and Diabetes-Related Traits and Their Dietary Responses to High-Fat Feeding in LGXSM Recombinant Inbred Mouse Strains

“…This population can be used to follow up the results reported here. Ehrich et al (25) have fine mapped the proximal portion of chromosome 13 for dietary response QTLs and located a region with differential effects on liver weight, reproductive fat depot weight, and insulin levels, depending on diet. At this locus, SM/J homozygotes respond more strongly to the high-fat diet than LG/J homozygotes.…”

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

“…The breeding mice were selected randomly from intercross II individuals to form an advanced intercross line (AIL) (Ehrich et al 2005) and a panel of recombinant inbred lines (RILs) (Kramer et al 1998;Cheverud et al 1999;Hrbek et al 2006). Standard mouse chow, an irradiated diet of 20% protein and 4.5% fat ½Purina (St. Louis) PicoLab Rodent Chow 20 (5353), was fed to the animals ad libitum postweaning.…”

Using an advanced intercross line to identify quantitative trait loci controlling immune response during collagen-induced arthritis

“…Indeed, this approach was successfully applied to refine QTLs in several studies. Since the propositon of AIL in 1995, eight AIL have been generated, including five mouse lines, [2][3][4][5][6] one rat line, 7,8 one chicken line 9 and one mosquito line. 10 All were used to refine QTLs that were originally identified in the F2 progeny with big CIs.…”