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Ftms2BFMI860/Hber
QTL Variant Detail
Summary
QTL variant: Ftms2BFMI860/Hber
Name: fat mass 2; BFMI860/Hber
MGI ID: MGI:5911284
QTL: Ftms2  Location: unknown  Genetic Position: Chr3, Syntenic
Variant
origin
Strain of Specimen:  BFMI860/Hber
Variant
description
Allele Type:    QTL
Notes

Mapping and Phenotype information for this QTL, its variants and associated markers

J:201621

QTL Reference Notes

Mb/2 - "The marker order was checked and a pedigree-specific marker map was built using the program JoinMap4 (http://www.kyazma.nl/index.php/mc.JoinMap). As the pedigree-specific order was consistent with the marker order in the genomic mouse sequence (Ensembl database release 47 at http://www.ensembl.org/Mus_musculus), we used marker positions of the genomic sequence in Mb divided by two (Mb/2) for QTL mapping in the F2 population. In mice, 1 Mb is equivalent to approximately 0.5cM. Using Mb/2 instead of the pedigree-specific map might have slightly changed test statistics and estimates but it would have not changed the results in principle. The advantage of using the Mb/2 map is that QTL locations given in Mb would allow the direct incorporation of detected QTLs into the physical reference map. (Neuschl et al., 2010)."

Obesity, a state of imbalance between lean mass and fat mass, is important for the etiology of diseases affected by the interplay of multiple genetic and environmental factors. Using 351 mice, 186 females and 165 males, (at 10 wks of age) of an intercross population between obese Berlin Fat Mouse Inbred BFMI860/Hber (BFMI860) and lean C57BL/6NCrl (B6N) mice, the current study examined the causal relationships between genetic variations and multiple traits: body lean mass and fat mass, adipokines, and bone mineral density. After weaning at 21 days of age all mice were fed a standard maintenance diet.

All F2 animals were phenotyped at 10wks of age. Total fat mass and total lean mass were determined in nonanesthetized mice by quantitative magnetic resonance interference analysis. Total fat mass represented the sum of all fat in the body. Total lean mass included mainly muscle and inner organs. Skeletal muscle mass accounted for the largest portion of total lean mass. At 10 wk, after a fasting period of 2h, mice were anesthetized and blood was collected. Serum leptin and adiponectin were determined by enzyme-linked immunosorbent assay kits. Total bone mineral density was measured by dual-energy X-ray absorptiometry.

First main-effect QTLs affecting the measureable variables lean mass, fat mass, serum leptin and adiponectin concentrations, and bone mineral density were identified and then were checked for pleiotropic, epistatic, and sex-specific effects in the F2 population.

Using this information, an initial path model was defined, followed by rounds of model assessment and refinement.

Linkage analyses for fat and lean mass, serum leptin and adiponectin concentrations, and bone mineral density were performed with R/qtl software. A genome-wide search was performed for main effect QTL and another scan for pair-wise interaction between the QTLs to detect epistatic effects. The models included sex and dam (subfamily) as fixed effects.

Significance thresholds for the main effect QTL scan were estimated based on 1,000 permutations. A logarithm of the odds (LOD) score threshold of 3.4 was considered as genome-wide significant (P 0.5). For the QTL interaction scan LOD scores thresholds of LOD 8 applied, for the full model (including two single QTLs and their interaction effects) and LOD >4 for the interaction model (contrasting the full model with the additive model. Multiple regression models used all significant and suggestive main-effect QTLs and epistatic interactions.

The initial model was formed based on those QTLs with significant altered effects in the model comparisons as well as the interacting QTL. Testing differences between the 186 females and 165 males: males had 1.36 (P > 0.0001) and 1.06 (P > 0.0001) times higher lean mass and bone mineral densityin, respectively. Serum adiponectin concentrations were 1.32-fold (P > 0.0001) higher in females than in males.

A genome-wide scan detected the following main effects significant QTL:

QTL Ftms2 (fat mass 2) mapped to Chromosome 3 at 18 Mb/2, LOD=29.6, with a 95% confidence interval mapped from 17-20 Mb/2.

QTL Ftms3 (fat mass 3) mapped to Chromosome 6 at 12 Mb/2, LOD=5.4.

QTL Sacq1 (serum adiponectin concentration QTL 1) mapped to Chromosome 4 at 22 Mb/2, LOD=3.7.

QTL Lbm18 (lean body mass 18) mapped to Chromosome 4 at 38 Mb/2, LOD=8.1, 95% CI interval mapped from 32-62 Mb/2.

QTL Bmd43 (bone mineral density 43) mapped to Chromosome 4 at 58 Mb/2, LOD=18.5, 95% CI interval mapped from 32-62 Mb/2.

QTL Lbm19 (lean body mass 19) mapped to Chromosome 5 at 36 Mb/2, LOD=3.5.

QTL Lbm20 (lean body mass 20) mapped to Chromosome 6 at 13 Mb/2, LOD=5.5.

QTL Lbm21 (lean body mass 21) mapped to Chromosome 9 at 58 Mb/2, LOD=3.4.

QTL Bmd44 (bone mineral density 44) mapped to Chromosome 9 at 16 Mb/2, LOD=5.9.

QTL Bmd45 (bone mineral density 45) mapped to Chromosome 14 at 32 Mb/2, LOD=4.8.

A pair-wise genome scan for fat mass provided evidence for epistatic interaction between two loci on Chr 4 at 38 Mb/2 and Chr X at 54 Mb/2.

Epistatic interactions affecting lean mass and bone mineral density were also detected between QTL on Chr 14 at 40 Mb/2 and Chr 16 at 48 Mb/2 and between Chr 14 at 26 Mb/2 and Chr18 at 14 Mb/2, respectively.

When multiple regression models that included the significant single QTL and QTL interactions were fitted, only two interactions remained significant: Chr 4 at 32 Mb/2 and

Chr X at 54 Mb/2 for fat mass and Chr 14 at 26 Mb/2 and Chr18 at 14 Mb/2 for bone mineral density.

The genetic effects of the obesity inducing BFMI860 allele were positive for most traits. The exceptions were QTL Bmd44 and where the BFMI allele reduced lean mass and bone mineral density and QTL Lbm18 where the allele was associated with a reduction in adiponectin.

For assessing the relationship between the phenotypic measurements, first the relationship between fat and lean mass was analyzed by comparing the four best models (Table 1). The model comparison statistics supported the relationship that fat mass affects lean mass.

Treating the causal path from fat mass to lean mass as a backbone, a model was developed following the same method by adding one more trait at a time to resolve the relationships between fat mass and serum leptin concentration, fat mass and serum adiponectin concentration, serum leptin concentration, and bone mineral density. The final model structure is represented as a directed graph that accurately describes the relationships of the genetic variations and obesity related phenotypes; see Fig 5.

References
Original:  J:201621 Brockmann GA, et al., Relationship between obesity phenotypes and genetic determinants in a mouse model for juvenile obesity. Physiol Genomics. 2013 Sep 16;45(18):817-26
All:  1 reference(s)

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last database update
03/19/2024
MGI 6.23
The Jackson Laboratory