Genetic Architecture of Body Fat Composition in Mice

Associate Prof. Muhammad Wali Salari; Patrick Ongom; Amanda Easterly; Qi Wang

doi:10.62810/jnsr.v1i1.11

Authors

Associate Prof. Muhammad Wali Salari Kabul University
Patrick Ongom Purdue University
Amanda Easterly Purdue University
Qi Wang Purdue University

DOI:

https://doi.org/10.62810/jnsr.v1i1.11

Keywords:

body weight, fat pads, gene action , mouse, obesity, QTL mapping

Abstract

Body fat composition is a quantitative measure of obesity, a major health concern in humans. Laboratory mice are considered an excellent model for dissecting the genetic basis of obesity due to the genetic variation present in inbred strains for body size and fat composition, as well as their historical use as a model organism for human disease studies. To identify the loci controlling fat pad weights and body weight in mice, we performed a quantitative trait loci (QTL) analysis of 513 (SM/J x NZB/BINJ) F₂ individuals fed a high-fat diet for 14 weeks. Our analysis separated fat composition genetic effects from those affecting overall body sizes in mouse. Composite interval mapping (CIM) results showed that body weight was conditioned by three major additive QTLs, explaining 3 to 30% of the phenotypic variation. One significant QTL on chromosome 19 conditioned all fat pads with the exception of the inguinal fat weight, which was controlled by a different QTL also on chromosome 19. Significant QTLs associated with fat compositions were detected on chromosomes 17 and 19 and differed from those of body weight. The fat pad QTLs also showed mainly additive gene effects and they explained 2 to 7% of variation in fat composition. Joint analysis of correlated traits detected five additional large effect QTLs on five different linkage groups. These findings have indicated that fat composition and body weight in mouse are conditioned by one to three major additive genes and can therefore be potentially manipulated in controlling obesity.

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References

Allayee, H., Ghazalpour, A., & Lusis, A. J. (2003). Using Mice to Dissect Genetic Factors in Atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 23(9), 1501–1509. https://doi.org/10.1161/01.ATV.0000090886.40027.DC DOI: https://doi.org/10.1161/01.ATV.0000090886.40027.DC

Basten, C. J., & Weir, B. S. (1994). Zmap-a QTL cartographer. In C. Smith, J. S. Gavora, B. B. J. Chesnais, W. Fairfull, J. P. Gibson, B. W. Kennedy, & E. B. Burnside (Eds.), Proceedings of the 5th World Congress on Genetics Applied to Livestock Production: Computing Strategies and Software (Vol. 22, pp. 65–66).

Broman, K. W., Wu, H., Sen, Ś., & Churchill, G. A. (2003). R/qtl: QTL mapping in experimental crosses. Bioinformatics, 19(7), 889–890. https://doi.org/10.1093/bioinformatics/btg112 DOI: https://doi.org/10.1093/bioinformatics/btg112

Churchill, G. A., & Doerge, R. W. (1994). Empirical threshold values for quantitative trait mapping. Genetics, 138(3), 963–971. https://doi.org/10.1093/genetics/138.3.963 DOI: https://doi.org/10.1093/genetics/138.3.963

Doerge, R. W. (1996). Constructing genetic maps by rapid chain delineation. Journal of Quantitative Trait Loci, 2, 121–132.

Ishimori, N., Li, R., Kelmenson, P. M., Korstanje, R., Walsh, K. A., Churchill, G. A., Forsman-Semb, K., & Paigen, B. (2004a). Quantitative trait loci that determine plasma lipids and obesity in C57BL/6J and 129S1/SvImJ inbred mice. J. Lipid Res., 45(9), 1624–1632. https://doi.org/10.1194/jlr.M400098-JLR200

Ishimori, N., Li, R., Kelmenson, P. M., Korstanje, R., Walsh, K. A., Churchill, G. A., Forsman-Semb, K., & Paigen, B. (2004b). Quantitative trait loci that determine plasma lipids and obesity in C57BL/6J and 129S1/SvImJ inbred mice. Journal of Lipid Research, 45(9), 1624–1632. https://doi.org/10.1194/jlr.M400098-JLR200 DOI: https://doi.org/10.1194/jlr.M400098-JLR200

Isomaa, B., Almgren, P., Tuomi, T., Forsén, B., Lahti, K., Nissén, M., Taskinen, M. R., & Groop, L. (2001). Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care, 24(4), 683–689. https://doi.org/10.2337/diacare.24.4.683 DOI: https://doi.org/10.2337/diacare.24.4.683

Jiang, C., & Zeng, Z. B. (1995). Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics, 140(3), 1111–1127. https://doi.org/10.1093/genetics/140.3.1111 DOI: https://doi.org/10.1093/genetics/140.3.1111

Lander, E. S., & Botstein, D. (1989). Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 121(1), 185–199. https://doi.org/10.1093/genetics/121.1.185 DOI: https://doi.org/10.1093/genetics/121.1.185

Lander, E. S., & Botstein, D. (1994). Mapping Mendelian factors underlying quantitative traits using RFLP linkage map. Genetics, 136(2), 705–705. https://doi.org/10.1093/genetics/136.2.705 DOI: https://doi.org/10.1093/genetics/136.2.705

Lynch, M., & Walsh, B. (1998). Genetics and analysis of quantitative traits. Oxford University Press.

Lyttle, T. W. (1991). SEGREGATION DISTORTERS. Annual Review of Genetics, 25(1), 511–581. https://doi.org/10.1146/annurev.ge.25.120191.002455 DOI: https://doi.org/10.1146/annurev.ge.25.120191.002455

Margarido, G. R. A., Souza, A. P., & Garcia, A. A. F. (2007). OneMap: software for genetic mapping in outcrossing species. Hereditas, 144(3), 78–79. https://doi.org/10.1111/j.2007.0018-0661.02000.x DOI: https://doi.org/10.1111/j.2007.0018-0661.02000.x

Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2012). Prevalence of obesity in the United States, 2009-2010. NCHS Data Brief, 82, 1–8. https://www.ncbi.nlm.nih.gov/pubmed/22617494

Schimenti, J. (2000). Segregation distortion of mouse t haplotypes the molecular basis emerges. Trends Genet., 16(6), 240–243. https://doi.org/10.1016/s0168-9525(00)02020-5 DOI: https://doi.org/10.1016/S0168-9525(00)02020-5

Snyder, E. E., Walts, B., Pérusse, L., Chagnon, Y. C., Weisnagel, S. J., Rankinen, T., & Bouchard, C. (2004). The human obesity gene map: the 2003 update. Obes. Res., 12(3), 369–439. https://doi.org/10.1038/oby.2004.47 DOI: https://doi.org/10.1038/oby.2004.47

Stylianou, I. M., Korstanje, R., Li, R., Sheehan, S., Paigen, B., & Churchill, G. A. (2006). Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci. Mamm. Genome, 17(1), 22–36. https://doi.org/10.1007/s00335-005-0091-2 DOI: https://doi.org/10.1007/s00335-005-0091-2