Across Breed EPD and multibreed genetic evaluation developments

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Across Breed EPD and multibreed genetic evaluation developments Larry Kuehn USDA, ARS, U.S. Meat Animal Research Center The USDA is an equal opportunity employer.

Across breed EPD program Program has been in place since 1993 Birth, weaning, yearling weight; milk Carcass traits added in 2008 Carcass weight added in 2015 Develop factors that allow producers to compare genetic merit of bulls across breeds Data from USMARC Germplasm Evaluation Program

2015 ABEPD factors

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 100 75 50 25 0-25 Genetic Trends for Yearling Weight, lb -50 Hereford Angus Red Angus Simmental Gelbvieh Limousin Charolais Beefmaster Brahman Braunvieh Chiangus Maine Anjou Santa Gertrudis Tarentaise Adapted from Spring 2015 Genetic Trends from Breed Associations and 2015 AB-EPD factors

Limitations of ABEPD program Factors do not account for difference in heterosis in commercial cross Angus vs. Simmental bull with Angus females Additive factors not adequate to accommodate many traits Calving ease, heifer pregnancy, etc. Yearly updates not sufficient for continuously updated national cattle evaluations

Possible solutions Web-based decision support Current focus of a collaboration/grant KSU, UNL, CSU, USMARC, Bruce Golden Could combine with bioeconomic simulation Heterosis, trait scaling, continuous updates all possible Multibreed evaluation Current implementation by American Simmental Association/International Genetic Solutions (ASA/IGS)

Obstacles to full Multibreed Merger of multiple breed databases Structures are often very different IDs duplicated in several breeds (but not known as duplicates) Difficult to resolve Standardized ID system would help Cooperation between database curators Breed associations Genetic prediction centers Individual producers/commercial entities

Multibreed obstacles Estimating population parameters Direct and maternal heterosis Direct and maternal additive breed effects Field data usually not suitable Contemporary groups structure Will discuss further Confounding between heterosis and breed Amount of crossbred data relative to purebred (depends on classification of purebred ) Research data useful here

Contemporary groups In order to estimate breed differences from field data, we need contemporary groups that include purebreds of both breeds Rarely occurs; often breeds are in different groups Even when crossbreds and purebreds are in the same group, direct comparisons are not possible without adjusting for heterosis (requires good estimates of heterosis)

Estimation of heterosis In order to estimate heterosis from field data, we need groups with crossbreds and purebreds of both parental breeds Rarely occurs; usually crossbreds are in a different groups Even when crossbreds and purebreds are in the same group, typically purebreds of only one of the breeds are present

Estimating breed differences Contemporary group Sire 1: Limousin WW Avg: 650 lb Sire 2: Angus WW Avg: 675 lb Sire 3: Lim-Flex WW Avg: 670 lb All mated to mature purebred Limousin cows What was the cause of the different averages? Heterosis Sire breeding YES value (and no) Breed differences

Estimating breed differences Problem can be improved with more sires in group still other considerations that are difficult to address Reciprocal matings Biased sampling of sires from other breeds Heterosis still difficult to separate from breed Were calves really treated the same?

Multibreed model Prior estimates of breed effects and heterosis essentially required Source of information most likely from research data GPE program is designed to estimate breed differences from current industry samples

Proposal Use breed differences from GPE to parameterize multibreed model currently in use by American Simmental Association Provide both breed effects and heterosis Can basically pre-adjust data for breed composition Need to consider where the programs are different and how to accommodate differences

GPE Target Population Structure AI Sires: AN, HH, SM, CH, AR, LM, GV, SH, BN, BM, MA, BR, CI, SG, SA, BV, SD, TA PB & F 1 Steers PB & F 1 Bulls PB & F 1 Heifers Natural Service PB, F 1, & F 1 2 Steers & Heifers

Across breed differences

Potential problems Currently, priors for ASA/IGS model are for breed by year effects GPE analysis based on sampling from industry sires and adjusting solutions to the EPDs of the sampled bulls In essence using breed genetic trends to adjust solutions from GPE data Only Hereford and Angus bulls sampled throughout GPE Interpolation likely necessary

Potential problems New trait development Currently summarize whole GPE database for weight traits and carcass traits as part of the ABEPD process Still missing CED, CEM, stayability and heifer pregnancy that are reported for several breeds Multinomial distributions of these traits will require some form of scaling from GPE to multibreed

Potential problems Heterosis While heterosis is reported as part of GPE, prior to current continuous sampling protocol, most estimates were based on Angus x Hereford crosses One goal of current program is to estimate breed-specific heterosis Important for multibreed Still far from complete

Possible solutions Breed x year solutions Need to examine what we can do to fill in the years Current ASA method places a high correlation among yearly estimates Possibly can reference old solutions and newer solutions and interpolate Adjust within years by within group EPD differences Would exclude genetic trend (circular logic)

Possible solutions New trait development Have already prototyped CED with UNL collaboration For ABEPD system, need to put all breeds on the same scale then transform to breed of interest Scaled EPD by additive SD of EPD Similar methodology could be applied to heifer pregnancy and stayability Records may be limited on some breeds in GPE, but will grow over time

Possible solutions Breed specific heterosis UNL collaboration also developed to begin exploring breed and breed-type specific heterosis (Schiermiester et al., 2015) Fitting main effect of heterosis (or breed-type) and random breed specific heterosis effects Resolution not great yet, but evidence of breedtype specific heterosis for weight traits Working on increasing crosses between 7 largest breeds and of those breeds with all others

Future plans Continue trait development and examination of breed effect model implications Important training in NCE for graduate student development

Conclusion We think the GPE program and the multibreed model are a natural fit Will improve the base adjustment among current members of IGS Can help to transition to mating and selection decision support programs

Acknowledgements Bruce Golden Wade Shafer Warren Snelling Mark Thallman Matt Spangler Lauren Hyde

Discussion and questions? Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply approval to the exclusion of other products that may be suitable.