2006 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Predicting Genetic.

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Presentation transcript:

2006 Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Predicting Genetic Interactions Within and Across Breeds

8 th World Congress Genetics Applied to Livestock Production, 2006 (2) P.M. VanRaden 2006 Modeling Genetic Interactions  Crossbreeding and heterosis in an all-breed animal model Estimate breed differences routinely Recommend mating strategies  Inbreeding depression adjustments in genetic evaluations  Within-breed interactions predicted using dominance relationships

8 th World Congress Genetics Applied to Livestock Production, 2006 (3) P.M. VanRaden 2006 All-Breed Analyses  Crossbred animals Will have EBVs, most did not before Reliable EBVs from both parents  Purebred animals Information from crossbred relatives More contemporaries  Routinely used in other populations New Zealand (1994), Netherlands (1997) USA goats (1989)

8 th World Congress Genetics Applied to Livestock Production, 2006 (4) P.M. VanRaden 2006 Purebred and Crossbred Data USA milk yield records BreedCows born 2002% of total Holstein632, Jersey43, Brown Swiss5,884.8 Guernsey2,851.4 Ayrshire2,101.3 F1 Crossbred7,8631.1

8 th World Congress Genetics Applied to Livestock Production, 2006 (5) P.M. VanRaden 2006 Across-Breed Methods  All-breed animal model Purebreds and crossbreds together Age adjust to 36 months, not mature Variance adjustments by breed Unknown parents grouped by breed Westell groups instead of regressing on breed fractions  General heterosis subtracted

8 th World Congress Genetics Applied to Livestock Production, 2006 (6) P.M. VanRaden 2006 Unknown Parent Groups  Groups formed based on Birth year Breed Path (dams of cows, sires of cows, parents of bulls) Origin (domestic vs other countries)  Paths have >1000 in last 15 years  Groups each have >500 animals

8 th World Congress Genetics Applied to Livestock Production, 2006 (7) P.M. VanRaden 2006 All- vs Within-Breed Evaluations Correlations of PTA Milk Breed 99% REL bulls Recent bulls Recent cows Holstein > Jersey Brown Swiss Guernsey Ayrshire Milking Shorthorn

8 th World Congress Genetics Applied to Livestock Production, 2006 (8) P.M. VanRaden 2006 Display of PTAs  Genetic base Compute on all-breed base Convert back to within-breed-of-sire bases for ease of comparing to previous PTA  Heterosis and inbreeding Both effects removed in the animal model Heterosis added to crossbred animal PTA Expected Future Inbreeding (EFI) and genetic merit differ with mate breed

8 th World Congress Genetics Applied to Livestock Production, 2006 (9) P.M. VanRaden 2006 Within-Breed Methods  Adjust for inbreeding depression Remove past F, include future F Expected future F (EFI) =.5 mean A ij EBV 0 vs EBV EFI vs unadjusted EBV  Optimal selection theory Maximize w’ EBV 0 + b y.F w’ A w Use of EBV 0 avoids double-counting

8 th World Congress Genetics Applied to Livestock Production, 2006 (10) P.M. VanRaden 2006 Effect of Inbreeding Adjustments Used in USA since 2005  Protein genetic trend estimates 3% more for EBV 0 than EBV 6% less for EBV EFI than EBV  Correlations of EBVs within breed.993 corr(EBV EFI, EBV) for cows.998 corr(EBV EFI, EBV) for bulls  Select on EBV 0 for crossbreeding?

8 th World Congress Genetics Applied to Livestock Production, 2006 (11) P.M. VanRaden 2006 Within-Breed Interactions  Dominance relationship matrix 5.5 million Holstein cows with data 1.6 million interactions among 4263 sires and maternal grandsires 30 minutes for D -1, 16 hours to solve  Dominance variance Assumed 5% of phenotypic variance Estimate from Van Tassell et al, 2000

8 th World Congress Genetics Applied to Livestock Production, 2006 (12) P.M. VanRaden 2006 Predicted Sire-MGS Interactions 305-d milk kg (heterosis = 318 kg) BullsDuster Man- fredDurham BW Mar- shallGarter Duster Manfred Durham BW Mar- shall Garter Numbers of observations below diagonal

8 th World Congress Genetics Applied to Livestock Production, 2006 (13) P.M. VanRaden 2006 Conclusions  Can predict genetic interactions Inbreeding adjustments since 2005 All-breed animal model expected 2007 Sire-MGS dominance effects within breed mostly smaller than heterosis  Future research on interactions Specific heterosis and epistasis Delivery of information to breeders