Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of a Fine-mapping Method Exploiting Linkage Disequilibrium in Livestock Populations: Simulation Study

  • Kim, JongJoo (School of Biotechnology, Yeungnam University) ;
  • Farnir, Frederic (Department of Genetics, Faculty of Veterinary Medicine, University of Liege (B43))
  • Received : 2006.03.13
  • Accepted : 2006.08.30
  • Published : 2005.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

A simulation study was conducted to evaluate a fine-mapping method exploiting population-wide linkage disequilibrium. Data were simulated according to the pedigree structure based on a large paternal half-sib family population with a total of 1,034 or 2,068 progeny. Twenty autosomes of 100 cM were generated with 5 cM or 1 cM marker intervals for all founder individuals in the pedigree, and marker alleles and a number of quantitative trait loci (QTL) explaining a total of 70% phenotypic variance were generated and randomly assigned across the whole chromosomes, assuming linkage equilibrium between the markers. The founder chromosomes were then descended through the pedigree to the current offspring generation, including recombinants that were generated by recombination between adjacent markers. Power to detect QTL was high for the QTL with at least moderate size, which was more pronounced with larger sample size and denser marker map. However, sample size contributed much more significantly to power to detect QTL than map density to the precise estimate of QTL position. No QTL was detected on the test chromosomes in which QTL was not assigned, which did not allow detection of false positive QTL. For the multiple QTL that were closely located, the estimates of the QTL positions were biased, except when the QTL were located on the right marker positions. Our fine mapping simulation results indicate that construction of dense maps and large sample size is needed to increase power to detect QTL and mapping precision for QTL position.

Keywords

References

  1. Blott, S., J.-J. Kim, S. Moisio, A. Schmidt-Kuntzel, A. Cornet, P. Berzi, N. Cambisano, C. Ford, B. Grisart, D. Johnson, L. Karim, P. Simon, R. Snell, R. Spelman, J. Wong, J. Vilkki, M. Georges, F. Farnir and W. Coppieters. 2003. Molecular dissection of a QTL: a phenylalanine to tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition. Genet. 163:253-266
  2. Dekkers, J. C. M. 2004. Commercial application of marker- and gene-assisted selection in livestock: Strategies and lessons. J. Anim. Sci. 82: E313-328E
  3. Lee, S. H. and J. H. J. van der Werf. 2005. The role of pedigree information in combined linkage disequilibrium and linkage mapping of quantitative trait loci in a general complex pedigree. Genet. 169:455-466 https://doi.org/10.1534/genetics.104.033233
  4. Farnir, F., W. Coppieters, J. Arranz, P. Berzi, N. Cambisano, B. Grisart, L. Karim, F. Marcq, L. Moreau, M. Mni, C. Nezer, P. Simon, P. Vanmanshoven, D. Wagenaar and M. Georges. 2000. Extensive genome-wide linkage disequilibrium in cattle. Genome Res. 10:220-227 https://doi.org/10.1101/gr.10.2.220
  5. Farnir, F., B. Grisart, W. Coppieters, J. Riquet, P. Berzi, N. Cambisano, L. Karim, M. Mni, S. Moisio, P. Simon, D. Wagenaar, J. Vilkki and M. Georges. 2002. Simultaneous mining of linkage and linkage disequilibrium to fine-map QTL in outbred half-sib pedigrees: revisiting the location of a QTL with major effect on milk production on bovine chromosome 14. Genet. 161:275-287
  6. Gautier, M., R. R. Barcelona, S. Fritz, C. Grohs, T. Druet, D. Boichard, A. Eggen and T. H. E. Meuwissen. 2006. Fine mapping and physical characterization of two linked quantitative trait loci affecting milk fat yield in dairy cattle on BTA26. Genet. 172:425-436 https://doi.org/10.1534/genetics.105.046169
  7. Grisart, B., F. Farnir, L. Karim, N. Cambisano, J.-J. Kim, A. Kvasz, M. Mni, P. Simon, J.-M. Frere, W. Coppieters and M. Georges. 2004. Genetic and functional confirmation of the causality of the DGAT1 K232A quantitative trait nucleotide in affecting milk yield and composition. P.N.A.S. 101:2398-2403
  8. Harmegnies, N., F. Farnir, F. Davin, I. Geerts, N. Buys, M. Georges and W. Coppieters. 2006. Measuring the extent of linkage disequilibrium in commercial pig populations. Anim. Genet. 37:225-231 https://doi.org/10.1111/j.1365-2052.2006.01438.x
  9. Kim, J. J. and M. Georges. 2002. Evaluation of a new finemapping method exploiting linkage disequilibrium: a case study analysing a QTL with major effect on milk composition on bovine chromosome 14. Asian-Aust. J. Anim. Sci. 15:1250 -1256 https://doi.org/10.5713/ajas.2002.1250
  10. Kim, T.-H., B.-H. Choi, D.-H. Yoon, E.-W. Park, J.-T. Jeon, J.-Y. Han, S.-J. Oh and I.-C. Cheong. 2004. Identification of quantitative trait loci (QTL) affecting teat number in pigs. Asian-Aust. J. Anim. Sci. 17:1210-1213 https://doi.org/10.5713/ajas.2004.1210
  11. Kim, T.-H., B.-H. Choi, H.-K. Lee, H. S. Park, H. Y. Lee, D. H. Yoon, J. W. Lee, J.-T. Jeon, I.-C. Cheong, S.-J. Oh and J.-Y. Han. 2005. Identification of quantitative trait loci (QTL) affecting growth traits in pigs. Asian-Aust. J. Anim. Sci. 18:1524-1528 https://doi.org/10.5713/ajas.2005.1524
  12. McRae, A. F., J. C. McEwan, K. G. Dodds, T. Wilson, A. M. Crawford and J. Slate. 2002. Linkage diesequilibrium in domestic sheep. Genet. 160:1113-1122
  13. Meuwissen, T. H. E. and M. E. Goddard. 2000. Fine mapping of quantitative trait loci using linkage disequilibria with closely linked marker loci. Genet. 155:421-430
  14. Meuwissen, T. H. E., A. Karlsen, S. Lien, I. Olsaker and M. Goddard. 2002. Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping. Genet. 161:373-379
  15. Riquet, J., W. Coppieters, N. Cambisano, J. Arranz, P. Berzi, S. K. Davis, B. Grisart, F. Farnir, L. Karim, M. Mni, P. Simon, J. F. Taylor, P. Vanmanshoven, D. Wagenaar, J. E. Womack and M. Georges. 1999. Fine-mapping of quantitative trait loci by identity by descent in outbred populations: application to milk production in dairy cattle. Proc. Natl. Acad. Sci. USA 96:9252-9257
  16. Schnabel, R. D., J.-J. Kim, M. S. Ashwell, T. S. Sonstegard, C. P. van Tassell, E. E. Conner and J. F. Taylor. 2005. Finemapping milk production quantitative trait loci on BTA6: analysis of the bovine osteopontin gene. P.N.A.S. 102:6896- 6901

Cited by

  1. Investigation of porcine FABP3 and LEPR gene polymorphisms and mRNA expression for variation in intramuscular fat content vol.37, pp.8, 2010, https://doi.org/10.1007/s11033-010-0050-1
  2. Analyses of porcine public SNPs in coding-gene regions by re-sequencing and phenotypic association studies vol.38, pp.6, 2011, https://doi.org/10.1007/s11033-010-0496-1
  3. Porcine insulin-like growth factor 1 (IGF1) gene polymorphisms are associated with body size variation vol.35, pp.4, 2013, https://doi.org/10.1007/s13258-013-0098-0
  4. Detection of QTL on Bovine X Chromosome by Exploiting Linkage Disequilibrium vol.21, pp.5, 2006, https://doi.org/10.5713/ajas.2008.70474
  5. Multifactor Dimensionality Reduction (MDR) Analysis to Detect Single Nucleotide Polymorphisms Associated with a Carcass Trait in a Hanwoo Population vol.21, pp.6, 2006, https://doi.org/10.5713/ajas.2008.70645
  6. Maximizing the Selection Response by Optimal Quantitative Trait Loci Selection and Control of Inbreeding in a Population with Different Lifetimes between Sires and Dams vol.21, pp.11, 2006, https://doi.org/10.5713/ajas.2008.80020