Multi-Breed Evaluation For Growth Traits J. Keith Bertrand University of Georgia, Athens

1. Multi-Breed Evaluation For Growth TraitsJ. Keith BertrandUniversity of Georgia, Athens

2. Multi-Breed Evaluation: Background • Elzo and Famula (1985) and Arnold et al. (1992) presented models for multi-breed evaluation. • Rodriguez-Almeida et al. (1997) concluded that even with simplified models, separation of effects in a multi-breed model requires data from a variety of crosses. • Notter and Cundiff (1991) proposed an approach that used estimated sire breed differences from research obtained at MARC after correcting for sampling and genetic trend. These sire breed effects are then added to breed association EPDs. • Klei et al. (1996) proposed using an approach that uses a model that combines data, and prior literature information to provide multi-breed genetic values.

3. Multi-Breed Evaluation (MBE) Analyzing the data from animals of any breed composition and providing genetic values (EPDs) for virtually all animals in the data base, regardless of breed composition.

4. Why Consider Multi-Breed Genetic Evaluation? • Genetic values can be computed on animals of any breed composition contained in the data base or population. • There is a potential increase in the accuracy of the genetic values due to the inclusion of additional information.

5. Effects in Model for Genetic Evaluation of Purebred Data Model : WWT = Fixed Effects + Direct Genetic Effect + Maternal Genetic Effect + Maternal Permanent Environmental Effect + ε Genetic value (EPD) provided by for an animal = Estimated Genetic Effects

6. Multi-breed Model : WWT = Fixed Effects + Direct Heterosis+Maternal Heterosis+ Direct Breed Effect +Maternal Breed Effect + Direct Genetic Effect + Maternal Genetic Effect + Maternal Permanent Environmental Effect + ε Effects in MBE Model Genetic value provided by MBE for an animal = Est. Breed Effects + Est. Genetic Effects

7. Application of MBE Model to Field Data Structure of field data will probably not allow for estimation of breed and heterosis effects. Solution? • Combine field records with records from designed • crossbreeding project(s) and apply MBE model. • Estimate breed and heterosis effects from literature • and use these prior estimates in the application of • the MBE model to the field data.

8. Estimation of Heterosis and Breed Effects in MBE Model • Typical system of Equations: • Cb = y • Application of Bayesian Methodology: • (C + Vp-1)b = y + Vp-1p • If Vp is very large, data determines estimate • If Vp is very small, prior determines estimate • If no data is present, prior determines estimate

9. Heterosis • Heterosis affects the phenotypic performance of individuals and needs to be taken into inconsideration in the prediction of EPDs • The dominance model is assumed to explain the retention of heterosis.

10. Estimation of Heterosis No heterosis differences assumed between reciprocal crosses; therefore, heterosis in offspring produced from an Angus sire mated to a Limousin cow = heterosis in offspring from a Limousin sire mated to an Angus cow.

11. Estimation of Heterosis Breeds are grouped into biological types for heterosis computations: British [B], Continental [C], Zebu [Z], Other [O] 10 comb.: BxB, BxC, BxZ, BxO, CxC, CxZ, CxO, ZxZ, ZxO, OxO Why Group? – With 60 or more breeds represented, more than seventeen hundred or more possible F1 combinations are possible

12. British [B] Continental [C] Zebu [Z] Angus Charolais Africander Devon Gelbvieh Brahman Hereford Limousin Gyr Murray Grey Salers Nellore Shorthorn Simmental Sahiwal Grouping of Breeds Into Biological Types:Some Examples

13. Estimation of Heterosis Heterosis estimate for an animal = psi x pdj x hij i  j psi = proportion of breed i in the sire. pdj = proportion of breed j in the dam. hij = F1 heterosis estimate for the i & j breed combination. (F1 heterosis estimated from a combination of data and literature values)

14. Dam Sire ½ Gelbvieh [C] ¼ Hereford [B] ¼ Angus [B] ½ Gelbvieh [C] 1/8 hBC 1/8 hBC ¼ Brahman [Z] 1/8 hCZ 1/16 hBZ 1/16 hBZ ¼ Angus [B] 1/8 hBC 1/16 hBB Estimating Heterosis hij = F1 heterosis estimate for the i and j breed comb. Heterosis Est. = 1/16 hBB + 3/8 hBC + 1/8 hBZ + 1/8 hCZ

15. Accounting For Breed Composition • Animal pedigrees are traced back as far as possible. • The breed combinations of these “founder” animals are determined. These founder animals may not be representative of their breed(s). • All the genes in an animal originated from these founders.

16. Breed of Founder (BOF) Effects • BOF fit in model to account for the genes from various breeds that are contributed by the founder animals. • Yearly or generational BOF effects are fit in model to account for genetic trend in the animals that enter the population over time. • Animal: ½ Simmental, ¼ Angus, ¼ Brahman • BOF effect = ½ BOFSIML + ¼ BOFANG + ¼ BOFBRA • (BOF effects est. using a combination of data • and literature values.)

17. Breed of Founder (BOF) Effects • Some breeds are fit in model: Angus, Brahman, Charolais, Gelbvieh, Hereford, Limousin, Simmental, etc. • Some breeds are placed into groups due to small numbers of observations. • Simmental Evaluation: American, British, Continental, Dairy, and Mixed • Gelbvieh and Limousin Evaluation: British Beef, British Dairy, Continental Beef, Continental Dairy, and Zebu.

19. Prior Values For Breed of Founder Effects For Different MBE Evaluations From Two Different Breeds

20. 1 ρρ2 ρ3 · · ρn ρ 1 ρρ2 · · ρn-1 ρ2 ρ 1 ρ · · ρn-2 ρ3 ρ2ρ 1 · · ρn-3 · · · · · · · · · · · · · · ρnρn-1 ρn-2ρn-3 · · 1 U = V Fitting Breed of Founder Effects in MBE Model p(bBOF) ~ N(BOF, U) Placed into mixed model equations by adding U-1 to the left hand sides of equations and the vector U-1BOF to the right hand sides.

21. BOF Determined by Data BOF Determined by Priors Generation Angus Gelbvieh Angus Gelbvieh < 1980 0.0 90.6 0.0 58.4 1981-1985 18.9 79.4 0.0 58.4 1986-1990 32.0 99.4 0.0 58.4 1991-1995 27.6 91.3 0.0 58.4 >1996 37.8 96.4 0.0 58.4 Angus and Gelbvieh BOF WWT Estimates From Analysis of Gelbvieh Data Assuming Informative or Noninformative priors

22. Weaning Weight EPD Gametic Trends for Angus (An) and Gelbvieh (Gv) When Using Informative (IP) or Noninformative (NIP) Priors

23. Incorporation of Outside EPDs Into MBE Evaluation • Significant numbers of sires from another breed may be present in the data set. • Similar to the evaluation of heterosis and BOF effects, the data and the outside EPD can be combined. • The outside EPD information can be used to better evaluate and rank a set of bulls within a breed. • The base of external EPDs has no influence on the EPDs predicted in the MBE

24. Rank Correlation Between WWT External EPDs and Gelbvieh MBE EPDs of Angus Sires When External Information is Ignored or Included

25. Incorporation of Outside EPDs Into MBE:Magnitude of Outside vs MBE EPDs An Example: Two high accuracy Angus bulls with AAA weaning EPDs of 60 and 20 lbs may not have the same magnitude of EPD in the MBE for another breed. However, if the two bulls have very little data in the MBE, the difference in their EPDs out of the MBE will be close to 40 lbs.

26. Gametic Trends • Genetic trends usually estimated as average EPDs or EBVs for calves born by year. • For each breed group, a gametic trend can be estimated. Within each year, EPDs of animals born in that year can be regressed on their breed compositions. The regression coefficients estimate the genetic merit of each breed group contributing to the genetic makeup of the animals born in that year. • The gametic trend uses information from every animal born in a given year to measure genes contributed by different breed groups. Therefore, every animal with some fraction of Angus genes, for example, would contribute to the Angus gametic trend.

27. Weaning Weight EPD Genetic and Gametic Trends for Gelbvieh From MBE Analysis of American Gebvieh Association Data Set

28. Weaning Weight Gametic EPD Trends for Angus and Limousin Animals from Limousin (NALF) and Gelbvieh (AGA) Evaluations

29. Multi-Breed Evaluation (MBE) Does MBE provide EPDs? People expect sire EPDs to predict the difference in the expected average performance between the progeny of two sires provided they were mated to dams of the same genetics, including breed type. Sire A EPD = 30 lbs, Sire B EPD = -5 lbs Expected difference in the average performance of future progeny produced by two sires = 30 – (-5)) = 35 lbs

30. Does MBE provide EPDs? Sire A: 1/2 Limousin, 1/2 Brahman Sire B: 100% Limousin Bred to genetically similar Limousin dams EPDA - EPDB = provides a prediction of the difference in the additive transmitting abilities between sires A and B. Average perf. of progA - average perf. of progB = TAA - TAB + (1/2 F1 hetCZ)

31. Brief Summary • MBE combines prior literature estimates and performance and pedigree information using Bayesian methodology to provide genetic values for animals of various breed combinations. • Breed-of-founder by year or breed of founder by generation effects are fit to account for the genetic trend of animals entering the population at different points in time. • An autoregressive process was used to describe the (co)variance structure among breed-of-founder by year or generation effects to eliminate large fluctuations in breed-of-founder effects over time. • Heterosis is difficult to estimate in field data; therefore, a large amount of emphasis is placed on literature estimates for the estimation of heterosis.

32. Future • At the request of several breed associations, NBCEC will conduct a prototype MBE for growth traits on a pooled data set. • NBCEC is conducting research to improve MBE: incorporation of random regression models and use of difference variances across breeds.

33. References Arnold, J.W., J.K. Bertrand, and L.L. Benyshek. 1992. Animal model for genetic evaluation of multi-breed data. J. Anim. Sci. 70:3322-3332 Elzo, M. A., and T. R. Famula. 1985. Multi-breed sire evaluation procedures within a country. J. Anim. Sci. 60:942-952. Gregory K.E., L. V. Cundiff, and R. M. Koch. 1991. Breed effects and heterosis in advanced generations of composite populations for growth traits in both sexes of beef cattle. J. Anim. Sci. 69:3202-3212. Klei L., R. L. Quaas, E. J. Pollak, and B. E. Cunningham. 1996. Multiple breed evaluation. Pages 106-113 in Proc. Research Symposium and Annual Meeting, Beef Improvement Federation. Birmingham, AL. Notter, D. R., and L. V. Cundiff. 1991. Across-breed expected progeny differences: use of within-breed expected progeny differences to adjust breed evaluations for sire sampling and genetic trend. J. Anim Sci. 69:4763-4776.

34. References (Continued) Pollak, E. J., and R. L. Quaas. 1998. Multibreed genetic evaluations in beef cattle. Pages 81- 88 in Proceedings of 6th World Congress Applied To Livestock Production. Vol. 23. Armidale, Australia. Rodriguez-Almeida, F. A., L. D. Van Vleck, and K. E. Gregory. 1997. Estimation of direct and maternal breed effects for prediction of expected progeny differences for birth and weaning weights in three multi-breed populations. J. Anim. Sci. 75:1203-1212. Wade K.M., and R. L. Quaas. 1993. Solutions to a system of equations involving a first- order autoregressive process. J. Dairy Sci. 76:3026-3032. Westell, R.A., R. L. Quaas, and L. D. Van Vleck. 1988. Genetic groups in an animal model. J. Dairy Sci, 71:1310-1318.

35. More Information on Multi-Breed Evaluation American Simmental Association Website: www.simmental.org/ Click on: Performance Programs—six articles are available on MBE-ICE