Mammalian Genome

, Volume 21, Issue 3, pp 115–129

Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

  • Lindsay C. Burrage
  • Annie E. Baskin-Hill
  • David S. Sinasac
  • Jonathan B. Singer
  • Colleen M. Croniger
  • Andrew Kirby
  • E. J. Kulbokas
  • Mark J. Daly
  • Eric S. Lander
  • Karl W. Broman
  • Joseph H. Nadeau
Article

DOI: 10.1007/s00335-010-9247-9

Cite this article as:
Burrage, L.C., Baskin-Hill, A.E., Sinasac, D.S. et al. Mamm Genome (2010) 21: 115. doi:10.1007/s00335-010-9247-9

Abstract

Discovery of genes that confer resistance to diseases such as diet-induced obesity could have tremendous therapeutic impact. We previously demonstrated that the C57BL/6J-ChrA/J/NaJ panel of chromosome substitution strains (CSSs) is a unique model for studying resistance to diet-induced obesity. In the present study, three replicate CSS surveys showed remarkable consistency, with 13 A/J-derived chromosomes reproducibly conferring resistance to high-fat-diet-induced obesity. Twenty CSS intercrosses, one derived from each of the 19 autosomes and chromosome X, were used to determine the number and location of quantitative trait loci (QTLs) on individual chromosomes and localized six QTLs. However, analyses of mean body weight in intercross progeny versus C57BL/6J provided strong evidence that many QTLs discovered in the CSS surveys eluded detection in these CSS intercrosses. Studies of the temporal effects of these QTLs suggest that obesity resistance was dynamic, with QTLs acting at different ages or after different durations of diet exposure. Thus, these studies provide insight into the genetic architecture of complex traits such as resistance to diet-induced obesity in the C57BL/6J-ChrA/J/NaJ CSSs. Because some of the QTLs detected in the CSS intercrosses were not detected using a traditional C57BL/6J × A/J intercross, our results demonstrate that surveys of CSSs and congenic strains derived from them are useful complementary tools for analyzing complex traits.

Supplementary material

335_2010_9247_MOESM1_ESM.doc (456 kb)
Supplementary material 1 (DOC 456 kb)

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Lindsay C. Burrage
    • 1
    • 7
  • Annie E. Baskin-Hill
    • 1
  • David S. Sinasac
    • 1
    • 8
  • Jonathan B. Singer
    • 2
    • 9
  • Colleen M. Croniger
    • 3
  • Andrew Kirby
    • 4
  • E. J. Kulbokas
    • 4
  • Mark J. Daly
    • 4
  • Eric S. Lander
    • 5
  • Karl W. Broman
    • 6
  • Joseph H. Nadeau
    • 1
  1. 1.Department of GeneticsCase Western Reserve University School of MedicineClevelandUSA
  2. 2.Broad Institute of MIT and Harvard UniversityCambridgeUSA
  3. 3.Department of NutritionCase Western Reserve University School of MedicineClevelandUSA
  4. 4.Center for Human Genetics Research, MGH Simches Research CenterBostonUSA
  5. 5.Department of Systems BiologyHarvard Medical SchoolBostonUSA
  6. 6.Department of Biostatistics and Medical InformaticsUniversity of WisconsinMadisonUSA
  7. 7.Department of PediatricsUniversity Hospitals Case Medical CenterClevelandUSA
  8. 8.Biochemical Genetics LaboratoryAlberta Children’s HospitalCalgaryCanada
  9. 9.Clinical PharmacogeneticsNovartis Institutes for Biomedical ResearchCambridgeUSA