Simulation of Base (Historical) Population and Determining Accuracy of Linkage Disequilibrium in Genomic Simulated Studies

Document Type : research

Authors

1 Ph. D student of Genetic and Animal Breeding, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj

2 Genetic and Animal Breeding, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj

3 Professor Genetic and Animal Breeding, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj

4 . Assistante Professor Genetic and Animal Breeding, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj

Abstract

To investigate accuracy of linkage disequilibrium (LD) in genomic simulation studies a base population was simulated in two statuses LD with values of zero and one in first generation. Effective population size, LD and variance of markers frequency were used for determination of simulation accuracy. The results showed a high correlation between actual and expected effective population sizes. Also observed and expected LD’s were nearly similar and the given trend was improved with increasing effective population size. In addition, the variances of the observed and expected free recombination markers frequency were adapted with each other. According to the evaluated criteria the base population was accurately simulated which it could be used to generate the reference population.  Based on the results, we suggest that proposed criteria should be used to verify the simulation after creating of historical population in genomic simulated studies.
 

Keywords

References

Amini, S. 2009. Genetic Evaluation by Genomic Selection in granddaughter design. MSc. Dissertation. University of Tehran. (In Farsi).
Calus, M. P. L., Meuwissen, T. H. E., de Ross, A. P. W. and Veerkamp, R. F. 2008. Accuracy of genomic selection using different methods to define haplotypes. Genetics, 178: 553-561.
Clark, S. A., Hickey, J. M. and Van der Werf, J. H. 2011. Different models of genetic variation and their effect on genomic evaluation. Genetics Selection Evolution, 43:18-27.
Daetwyler, H. D., Pong-Wong, R., Villanueva, B. and Woolliams, J. A. 2010. The impact of genetic architecture on genome-wide evaluation methods. Genetics, 185: 1021-1031.
de Roos, A. P. W., Hayes, B. J., Spelman, R. J. and Goddard, M. E. 2008. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle. Genetics, 179: 1503-1512.
Falconer, D. S. and Mackay, T. F. C. 1996. Introduction to quantitative genetics. Third edition. Longman Group, Essex, UK.
Goddard, M. E. and Hayes, B. J. 2007. Genomic selection. Journal of Animal Breeding and Genetics, 124: 323-330.
Haldane, J. B. S. 1919. The combination of linkage values, and the calculation of distances between the loci of linked factors. Genetics, 8: 299-309.
Hayes, B. J. 2007. QTL mapping, MAS and Genomic Selection.Department of Primary Industries Victoria, Australia.A Short-Course Organized by Animal Breeding and Genetics, Department of Animal Science, Iowa State University.
Hill, W. G. 1981. Estimation of effective population size from data on linkage disequilibrium. Genetical Research, 38: 209- 216.
Hill, W. G. and Robertson, A. 1968. Linkage disequilibrium in finite populations. Theoretical Application Genetics, 38: 226-231.
Khansefid, M. 2010. Genetic Evaluation of Animals using Sire Genotypes for Dense Marker by Simulation. MSc. Dissertation. University of Tehran. (In Farsi).
Meuwissen, T. H. E., Hayes, B. J.  and Goddard, M. E. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157: 1819-1829.
Saatchi, M., Miraei-Ashtiani, S. R. , Nejati Javaremi, A., Moradi-Shahrebabak, M.  and Mehrabani-Yeghaneh, H. 2010. The impact of information quantity and strength of relationship between training set and validation set on accuracy of genomic estimated breeding values. African Journal of Biotechnology, 9: 438-442.
Solberg, T. R., Sonesson, A. K., Woolliams, J. A. and Meuwissen, T. H. E. 2008. Genomic selection using different marker types and densities. Journal of Animal Science, 86: 2447-2454.
Sved, J. A. 1971. Linkage disequilibrium and homozygosity of chromosome segments in finite populations. Theoretical Population Biology, 2: 125-141.
Toro, M. A. and Varona, L. 2010. A note on mate allocation for dominance handling in genomic selection. Genetics Selection Evolution, 42(1): 33-42.
Villumsen, T. M., Janss, L. and Lund, M. S. 2009. The importance of haplotype length and heritability using genomic selection in dairy cattle. Journal of Animal Breeding and Genetics, 126: 3-13.
Weigel, K. A. 2011. Haplotypes Affecting Fertility and their Impact on Dairy Cattle Breeding Programs. http://www.holsteinworld.com/story.php?id=4493.
Wellmann, R. and Bennewitz, J. 2012. Bayesian models with dominance effects for genomic evaluation of quantitative traits. Genetics Research, 94: 21-37.
Zhang, Z., Liu, J., Ding, X., Bijma, P., de Koning, D. J. and Zhang, Q. 2010. Best linear unbiased prediction of genomic breeding values using a trait-specific marker-derived relationship matrix. PLoS ONE, 5(9): e12648. Doi: 10 . 1371 / journal. Pone .0012648.
 
 
 
 
 
 
 
 
 
 
 

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