Skip to main content
×
Home
    • Aa
    • Aa

Bias in genomic predictions for populations under selection

  • Z. G. VITEZICA (a1), I. AGUILAR (a2), I. MISZTAL (a3) and A. LEGARRA (a4)
Summary
Summary

Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically.

Copyright
Corresponding author
*Corresponding author: UMR 1289 TANDEM, ENSAT, Avenue de l'Agrobiopole, Postal Box 32607, 31326 Auzeville Tolosane, France. E-mail: zulma.vitezica@ensat.fr
References
Hide All
Aguilar I., Misztal I., Johnson D. L., Legarra A., Tsuruta S. & Lawlor T. J. (2010). A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science 93, 743752.
Chen C. Y., Misztal I., Aguilar I., Legarra A. & Muir W. M. (2011). Effect of different genomic relationship matrices on accuracy and scale. Journal of Animal Science, in press.
Christensen O. F. & Lund M. S. (2010). Genomic prediction when some animals are not genotyped. Genetics Selection Evolution 42, 2.
Cockerham C. C. (1969). Variance of gene frequencies. Evolution 23, 7284.
Cockerham C. C. (1973). Analysis of gene frequencies. Genetics 74, 679700.
Daetwyler H. D., Pong-Wong R., Villanueva B. & Woolliams J. A. (2010). The impact of genetic architecture on genome-wide evaluation methods. Genetics 185, 10211031.
Fernando R. & Gianola D. (1986). Optimal properties of the conditional mean as a selection criterion. Theoretical and Applied Genetics 72, 822825.
Garrick D. J., Taylor J. F. & Fernando R. L. (2009). Deregressing estimated breeding values and weighting information for genomic regression analyses. Genetics Selection Evolution 41, 55.
Goddard M. E. & Hayes B. J. (2009). Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics 10, 381391.
Hayes B. J., Vissher P. M. & Goddard M. E. (2009). Increased accuracy of artificial selection by using the realized relationship matrix. Genetics Research 91, 4760.
Henderson C. R. (1973). Sire evaluation and genetic trends. In: Proceedings of the Animal Breeding and Genetics Symposium in Honor of Dr. J. L. Lush. pp. 1041. Champaign, IL: American Society of Animal Science and American Dairy Science Association.
Henderson C. R., Kempthorne O., Searle S. R. & von Krosigk C. M. (1959). The estimation of environmental and genetic trends from records subject to culling. Biometrics 15, 192218.
Henderson C. R. & Searle S. R. (1981). On deriving the inverse of a sum of matrices. SIAM Review 23, 5360.
Hill W. G. (2010). Understanding and using quantitative genetic variation. Philosophical Transactions of the Royal Society B 365, 7385.
Im S., Fernando R. L. & Gianola D. (1989). Likelihood inferences in animal breeding under selection: a missing-data theory viewpoint. Genetics Selection Evolution 21, 399414.
Kennedy B. W., Schaeffer L. R. & Sorensen D. A. (1988). Genetic properties of animal models. Journal of Dairy Science 71, 1726.
Legarra A., Aguilar I. & Misztal I. (2009). A relationship matrix including full pedigree and genomic information. Journal of Dairy Science 92, 46564663.
Luan T., Woolliams J. A., Lien S., Kent M., Svendsen M. & Meuwissen T. H. E. (2009). The accuracy of genomic selection in Norwegian red cattle assessed by cross-validation. Genetics 183, 11191126.
Mäntysaari E., Liu Z. & VanRaden P. (2010). Interbull validation test for genomic evaluations. Interbull Bulletin 41, 5 p.
Meuwissen T. H. E., Hayes B. J. & Goddard M. E. (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 18191829.
Oliehoek P. A., Winding J. J., van Arendonk J. A. M. & Bijma P. (2006). Estimating relatedness between individuals in general populations with a focus on their use in conservation programs. Genetics 173, 483496.
Patry C. & Ducrocq V. (2011). Evidence of biases in genetic evaluations due to genomic pre-selection in dairy cattle. Journal of Dairy Science 94, 10111020.
Powell J. E., Vissher P. M. & Goddard M. E. (2010). Reconciling the analysis of IBD and IBS in complex trait studies. Nature Reviews Genetics 11, 800805.
Quaas R. L. (1988). Additive genetic models with groups and relationships. Journal of Dairy Science 71, 13381345.
Roehe R. & Kennedy B. W. (1993). The influence of maternal effects on accuracy of evaluation of litter size in swine. Journal of Animal Science 71, 23532364.
Sargolzaei M. & Schenkel F. (2009). QMSim: a large-scale genome simulator for livestock. Bioinformatics 25, 680681.
Solberg T. R., Sonesson A. K., Woolliams J. A. & Meuwissen T. H. E. (2008). Genomic selection using different marker types and densities. Journal of Animal Science 86, 24472454.
Sorensen D. A. & Kennedy B. W. (1984). Estimation of response to selection using least squares and mixed model methodology. Journal of Animal Science 58, 10971103.
VanRaden P. M. (2008). Efficient methods to compute genomic predictions. Journal of Dairy Science 91, 44144423.
VanRaden P. M., Van Tassell C. P., Wiggans G. R., Sonstegard T. S., Schnabel R. D., Taylor J. F. & Schenkel F. S. (2009 a). Invited review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science 92, 1624.
VanRaden P. M., Tooker M. E. & Cole J. B. (2009 b). Can you believe those genomic evaluations for young bulls? Journal of Dairy Science 92(E-Suppl. 1), 314 (Abstr.).
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Genetics Research
  • ISSN: 0016-6723
  • EISSN: 1469-5073
  • URL: /core/journals/genetics-research
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Full text views

Total number of HTML views: 7
Total number of PDF views: 81 *
Loading metrics...

Abstract views

Total abstract views: 298 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 19th October 2017. This data will be updated every 24 hours.