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Genetic influences on growth and body composition in mice: multilocus interactions

International Journal of Obesity volume 33, pages 89–95 (2009)Cite this article

Abstract

Background:

The genetic architecture of body weight and body composition is complex because these traits are normally influenced by multiple genes and their interactions, even after controlling for the environment. Bayesian methodology provides an efficient way of estimating these interactions.

Subjects and measurements:

We used Bayesian model selection techniques to simultaneously estimate the main effects, epistasis and gene–sex interactions on age-related body weight (at 3, 6 and 10 weeks, denoted as WT3wk, WT6wk and WT10wk) and body composition (organ weights and fat-related traits) in an F2 sample obtained from a cross between high-growth (M16i) mice and low-growth (L6) mice.

Results:

We observed epistatic and main-effect quantitative trait loci (QTL) that controlled both body weight and body composition. Epistatic effects were generally more significant for WT6wk than WT10wk. Chromosomes 5 and 13 interacted strongly to control body weight at 3 weeks. A pleiotropic QTL on chromosome 2 was associated with body weight and some body composition phenotypes. Testis weight was regulated by a QTL on chromosome 13 with a significantly large main effect (2logeBF ∼15).

Conclusion:

By analyzing epistatic interactions, we detected QTL not found in a previous analysis of this mouse population. Hence, the detection of gene–gene interactions may provide new information about the genetic architecture of complex obesity-related traits and may lead to the detection of additional obesity genes.

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References

  1. Comuzzie AG, Allison DB . The search for human obesity genes. Science 1998; 280: 1374–1377.

    Article  CAS  PubMed  Google Scholar 

  2. Tiwari HK, Allison DB . Do allelic variants of SLC6A14 predispose to obesity? J Clin Invest 2003; 112: 1633–1636.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Yi N, Diament A, Chiu S, Kim K, Allison DB, Fisler JS et al. Characterization of epistasis influencing complex spontaneous obesity in the BSB model. Genetics 2004; 167: 399–409.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Cheverud JM, Routman EJ, Duarte FAM, van Swinderen B, Cothran K, Perel C . Quantitative trait loci for murine growth. Genetics 1996; 142: 1305–1319.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Vaughn TT, Pletscher LS, Peripato A, King-Ellison K, Adams E, Erikson C et al. Mapping quantitative trait loci for murine growth: a closer look at genetic architecture. Genet Res 1999; 74: 313–322.

    Article  CAS  PubMed  Google Scholar 

  6. Carlborg O, Kerje S, Schutz K, Jacobsson L, Jensen P, Andersson L . A global search reveals epistatic interaction between QTL for early growth in the chicken. Genome Res 2003; 13: 413–421.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Carlborg O, Brockmann GA, Haley CS . Simultaneous mapping of epistatic QTL in DU6i x DBA/2 mice. Mamm Genome 2005; 16: 481–494.

    Article  CAS  PubMed  Google Scholar 

  8. Segal NL, Allison DB . Twins and virtual twins: bases of relative body weight revisited. Int J Obes 2002; 26: 437–441.

    Article  CAS  Google Scholar 

  9. Rocha JL, Eisen EJ, Van Vleck LD, Pomp D . A large-sample QTL study in mice: I. Growth. Mamm Genome 2004; 15: 83–99.

    Article  CAS  PubMed  Google Scholar 

  10. Yi N, Zinniel DK, Kim K, Eisen EJ, Bartolucci A, Allison DB et al. Bayesian analysis of multiple epistatic QTL models for body weight and body composition in mice. Genet Res 2006; 87: 45–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ishikawa A, Hatada S, Nagamine Y, Namikawa T . Further mapping of quantitative trait loci for postnatal growth in an intersubspecific backcross of wild Mus musculus castaneus and C57BL/6J mice. Genet Res 2005; 85: 127–137.

    Article  CAS  PubMed  Google Scholar 

  12. Fijneman RJ, De Vries SS, Jansen RC, Dermant P . Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse. Nat Genet 1996; 14: 465–467.

    Article  CAS  PubMed  Google Scholar 

  13. Boer MP, ter Braak CJF, Jansen RC . A penalized likelihood method for mapping epistatic quantitative trait loci with one-dimensional genome searches. Genetics 2002; 162: 951–960.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Kao C-H, Zeng Z-B . Modeling epistasis of quantitative trait loci using Cockerham's model. Genetics 2002; 160: 1243–1261.

    PubMed  PubMed Central  Google Scholar 

  15. Yi N, Yandell BS, Churchill GA, Allison DB, Eisen EJ, Pomp D . Bayesian model selection for genome-wide epistatic quantitative trait loci analysis. Genetics 2005; 170: 1333–1344.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rocha JL, Eisen EJ, Van Vleck LD, Pomp D . A large-sample QTL study in mice: II. Body composition. Mamm Genome 2004; 14: 100–113.

    Article  Google Scholar 

  17. Ott L . An Introduction to Statistical Methods and Data Analysis, 2nd edn. Duxbury Press: Boston, Mass, 1984.

    Google Scholar 

  18. Paterson A, Lander E, Lincoln S, Hewitt J, Peterson S, Tanksley S . Resolution of quantitative traits into mendelian factors using a complete RFLP linkage map. Nature 1988; 335: 721–726.

    Article  CAS  PubMed  Google Scholar 

  19. Yi N, Shriner D, Banerjee S, Mehta T, Pomp D, Yandell BS . An efficient Bayesian model selection approach for interacting QTL models with many effects. Genetics 2007; 176: 1865–1877.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Yandell BS, Mehta T, Banerjee S, Shriner D, Venkataraman R, Moon JY et al. R/qtlbim: QTL with Bayesian interval mapping in experimental crosses. Bioinformatics 2007; 23: 641–643.

    Article  CAS  PubMed  Google Scholar 

  21. Kass RE, Raftery AE . Bayes factors. J Am Stat Assoc 1995; 90: 773–795.

    Article  Google Scholar 

  22. Lembertas AV, Perusse L, Chagnon YC, Fisler JS, Warden CH, Purcell-Huynh DA et al. Identification of an obesity quantitative trait locus on mouse chromosome 2 and evidence of linkage to body fat and insulin on the human homologous region20q. J Clin Invest 1997; 100: 1240–1247.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Jerez-Timaure NC, Kearney F, Simpson EB, Eisen EJ, Pomp D . Characterization of QTL with major effects on fatness and growth on mouse chromosome 2. Obes Res 2004; 9: 1408–1420.

    Article  Google Scholar 

  24. Vitarius JA, Sehayek E, Breslow JL . Identification of quantitative trait loci affecting body composition in a mouse intercross. Proc Natl Acad Sci USA 2006; 103: 19860–19865.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Routman EJ, Cheverud JM . Gene effects on a quantitative trait: two-locus epistatic effects measured at microsatellites markers and at estimated QTL. Evolution 1997; 51: 1654–1662.

    Article  PubMed  Google Scholar 

  26. Brockmann GA, Kratzsch J, Haley CS, Renne U, Schwerin M, Karle S . Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F2 variance of growth and obesity in DU6i x DBA/2 mice. Genome Res 2000; 10: 1941–1957.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Abdellatif MA . Genetic study of Dandawary chickens: I. Heritabilities and genetic correlations of body weight and weight gain. Genet Sel Evol 1989; 21: 81–92.

    Article  PubMed Central  Google Scholar 

  28. Le Roy I, Tordjman S, Migliore-Samour D, Degrelle H, Roubertoux PL . Genetic architecture of testis and seminal vesicle weights in mice. Genetics 2001; 158: 333–340.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Morris KH, Ishakawa A, Keightley PD . Quantitative trait loci for growth traits in C57BL/6J x DBA/2J mice. Mamm Genome 1999; 10: 225–228.

    Article  CAS  PubMed  Google Scholar 

  30. Leamy LJ, Pomp D, Eisen EJ, Cheverud JM . Pleiotropy of quantitative trait loci for organ weights and limb bone lengths mice. Physiol Genomics 2002; 10: 21–29.

    Article  CAS  PubMed  Google Scholar 

  31. Zidek V, Musilova A, Pintir J, Simakova M, Pravenec M . Genetic dissection of testicular weight in the mouse with the BXD recombinant inbred strains. Mamm Genome 1998; 9: 503–505.

    Article  CAS  PubMed  Google Scholar 

  32. Warden CH, Fisler JS, Shoemaker SM, Wen PZ, Svenson KL, Pace MJ et al. Identification of four chromosomal loci determining obesity in a multifactorial mouse model. J Clin Invest 1995; 95: 1545–1552.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. West DB, Goudey-Lefevre J, York B, Truett GE . Dietary obesity linked to genetic loci on chromosomes 9 and 15 in a polygenic mouse model. J Clin Invest 1994; 94: 1410–1416.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Drewnowski A . The real contribution of added sugars and fats to obesity. Epidemiol Rev 2007; 29: 160–171.

    Article  PubMed  Google Scholar 

  35. Keith S, Redden D, Kazmarzyk P, Boggiano M, Hanlon E, Benca R et al. Putative contributors to the secular increase in obesity: exploring the roads less traveled. Int J Obes 2006; 30: 1585–1594.

    Article  CAS  Google Scholar 

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Acknowledgements

This research was partly supported by the National Institutes of Health Grants GM069430, DK056336, DK076050 and HL072757.

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Authors and Affiliations

  1. Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA

    G A Ankra-Badu, D Shriner, D B Allison & N Yi

  2. Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA

    D Pomp

  3. Department of Cell and Molecular Physiology, University of North Carolina, Chapel Hill, NC, USA

    D Pomp

  4. Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, AL, USA

    D B Allison & N Yi

Authors
  1. G A Ankra-Badu
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  2. D Pomp
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  3. D Shriner
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  5. N Yi
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Correspondence to N Yi.

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Ankra-Badu, G., Pomp, D., Shriner, D. et al. Genetic influences on growth and body composition in mice: multilocus interactions. Int J Obes 33, 89–95 (2009). https://doi.org/10.1038/ijo.2008.215

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