The lack of myostatin promotes growth of skeletal muscle, and blockade of its activity has been proposed as a treatment for various muscle-wasting disorders. Here, we have examined two independent mouse lines that harbor mutations in the myostatin gene, constitutive null ( Mstn −/− ) and compact (Berlin High Line, BEH c/c ). We report that, despite a larger muscle mass relative to age-matched wild types, there was no increase in maximum tetanic force generation, but that when expressed as a function of muscle size (specific force), muscles of myostatin-deficient mice were weaker than wild-type muscles. In addition, Mstn −/− muscle contracted and relaxed faster during a single twitch and had a marked increase in the number of type IIb fibers relative to wild-type controls. This change was also accompanied by a significant increase in type IIB fibers containing tubular aggregates. Moreover, the ratio of mitochondrial DNA to nuclear DNA and mitochondria number were decreased in myostatin-deficient muscle, suggesting a mitochondrial depletion. Overall, our results suggest that lack of myostatin compromises force production in association with loss of oxidative characteristics of skeletal muscle.
The ability to accurately measure body or carcass composition is important for performance testing, grading and finally selection or payment of meat-producing animals. Advances especially in non-invasive techniques are mainly based on the development of electronic and computer-driven methods in order to provide objective phenotypic data. The preference for a specific technique depends on the target animal species or carcass, combined with technical and practical aspects such as accuracy, reliability, cost, portability, speed, ease of use, safety and for in vivo measurements the need for fixation or sedation. The techniques rely on specific device-driven signals, which interact with tissues in the body or carcass at the atomic or molecular level, resulting in secondary or attenuated signals detected by the instruments and analyzed quantitatively. The electromagnetic signal produced by the instrument may originate from mechanical energy such as sound waves (ultrasound – US), ‘photon’ radiation (X-ray-computed tomography – CT, dual-energy X-ray absorptiometry – DXA) or radio frequency waves (magnetic resonance imaging – MRI). The signals detected by the corresponding instruments are processed to measure, for example, tissue depths, areas, volumes or distributions of fat, muscle (water, protein) and partly bone or bone mineral. Among the above techniques, CT is the most accurate one followed by MRI and DXA, whereas US can be used for all sizes of farm animal species even under field conditions. CT, MRI and US can provide volume data, whereas only DXA delivers immediate whole-body composition results without (2D) image manipulation. A combination of simple US and more expensive CT, MRI or DXA might be applied for farm animal selection programs in a stepwise approach.
Understanding how polygenic traits evolve under selection is an unsolved problem, because challenges exist for identifying genes underlying a complex trait and understanding how multilocus selection operates in the genome. Here we study polygenic response to selection using artificial selection experiments. Inbred strains from seven independent long-term selection experiments for extreme mouse body weight ("high" lines weigh 42-77 g versus 16-40 g in "control" lines) were genotyped at 527,572 SNPs to identify loci controlling body weight. We identified 67 parallel selected regions (PSRs) where high lines share variants rarely found among the controls. By comparing allele frequencies in one selection experiment against its unselected control, we found classical selective sweeps centered on the PSRs. We present evidence supporting two G protein-coupled receptors GPR133 and Prlhr as positional candidates controlling body weight. Artificial selection may mimic natural selection in the wild: compared to control loci, we detected reduced heterozygosity in PSRs in unusually large wild mice on islands. Many PSRs overlap loci associated with human height variation, possibly through evolutionary conserved functional pathways. Our data suggest that parallel selection on complex traits may evoke parallel responses at many genes involved in diverse but relevant pathways.
Despite major advances in understanding monogenic causes of morbid obesity, the complex genetic and environmental etiology of idiopathic metabolic syndrome remains poorly understood. One hypothesis suggests that similarities between the metabolic disease of plasma glucocorticoid excess (Cushing's syndrome) and idiopathic metabolic syndrome results from increased glucocorticoid reamplification within adipose tissue by 11-hydroxysteroid dehydrogenase type 1 (11-HSD-1). Indeed, 11-HSD-1 is now a major therapeutic target. Because much supporting evidence for a role of adipose 11-HSD-1 comes from transgenic or obese rodents with single-gene mutations, we investigated whether the predicted traits of metabolic syndrome and glucocorticoid metabolism were coassociated in a unique polygenic model of obesity developed by long-term selection for divergent fat mass (Fat and Lean mice with 23 vs. 4% fat as body weight, respectively). Fat mice exhibited an insulin-resistant metabolic syndrome including fatty liver and hypertension. Unexpectedly, Fat mice had a marked intra-adipose (11-HSD-1) and plasma glucocorticoid deficiency but higher liver glucocorticoid action. Furthermore, metabolic disease was exacerbated only in Fat mice when challenged with exogenous glucocorticoids or a high-fat diet. Our data suggest that idiopathic metabolic syndrome might associate with such a novel pattern of glucocorticoid action and sensitivity in humans, with implications for tissue-specific therapeutic targeting of 11-HSD-1. Diabetes 54:3371-3378, 2005 I diopathic obesity is highly prevalent and strongly associated with other comorbid conditions such as insulin resistance, type 2 diabetes, dyslipidemia, and hypertension (the metabolic syndrome) (1). Despite major advances in understanding rare monogenic causes of obesity in humans and their striking recapitulation in transgenic or mutant rodent models (2), there is no consensus on a unified underlying biological mechanism accounting for the broader incidence of the metabolic syndrome because of its complex (3) polygenic origins.Close phenotypic parallels exist between idiopathic metabolic syndrome and plasma cortisol excess (e.g., Cushing's syndrome) (4), suggesting a common underlying role for glucocorticoid action in these disease processes. Indeed, rodent obesity and metabolic disease are ameliorated by adrenalectomy (5) and reinstated by exogenous glucocorticoids. Mechanistically, glucocorticoids mediate exaggerated adipocyte formation and hypertrophy (6,7), elevate liver glucose (8) and lipid production (9), exacerbate muscle insulin resistance (10), and inhibit central energy expenditure systems (11). However, in idiopathic human obesity, circulating glucocorticoid levels are usually unaltered, or even low (12). A potential explanation for this paradox is increased amplification of active glucocorticoid levels by the intracellular enzyme 11-hydroxysteroid dehydrogenase type 1 (11-HSD-1). 11-HSD-1 is elevated in the subcutaneous adipose tissue of obese humans (13-15) and in vis...
A genome-wide quantitative trait locus (QTL) analysis was performed in a polygenic obesity mouse model resulting from a long-term selection experiment. The parental lines were outbred lines divergently selected for 53 generations for high-fat (fat, F line) or low-fat (lean, L line) percentage (fat%) that differed fivefold in fat% at 14 weeks of age. An F2 population of 436 mice was used for the QTL analysis with 71 markers distributed across the genome. The analysis revealed significant QTLs Fob1 (for F-line obesity QTL 1), Fob2, Fob3, and Fob4, on Chromosomes (Chrs) 2, 12, 15, and X, respectively. None of these QTLs map to regions of known single gene obesity mutations (Lepob, Leprdb, Cpefat, Ay, tub), though they map to regions of previously described obesity QTLs and candidate genes. The effects of Fob1, Fob3, Fob4 were additive, and that of Fob2 was dominant. Fob2 also showed a significant female-specific effect. Fob1, Fob2, Fob3, and Fob4 explained 4.9%, 19.5%, 14.4%, and 7.3% of the F2 phenotypic variance for fat%, respectively. This study identified four loci that contributed to the response to divergent selection and control a significant proportion of the difference in obesity between the F and L lines.
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