Multi-trait, multi-breed conception rate evaluations P. M. VanRaden 1, J. R. Wright 1 *, C. Sun 2, J. L. Hutchison 1 and M. E. Tooker 1 1 Animal Genomics.

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Multi-trait, multi-breed conception rate evaluations P. M. VanRaden 1, J. R. Wright 1 *, C. Sun 2, J. L. Hutchison 1 and M. E. Tooker 1 1 Animal Genomics & Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD National Association of Animal Breeders, Columbia, MO INTRODUCTION  Cow conception rate (CCR) and heifer conception rate (HCR) evaluations have been calculated since 2010  Definitions:  The percent of inseminated heifers (HCR) or cows (CCR) that become pregnant at each service  Daughter pregnancy rate (DPR): The percent of non-pregnant cows that become pregnant in each 21-day time interval Previous model:  Single breed BLUPF90 model software (Misztal). No crossbred cows included, only crossbred breeding  Modeled with multiple binary success per lactation (e.g. no, no, yes)  Model included adjustments for permanent environment, management group (herd-year- season-parity-registry status), year-state-month of breeding, service number, mating type, short cycle, age group at breeding and lactation number  Breeding records only available since 2003 New model :  All breeds combined; crossbreds included  Pre-adjusted for region-month of breeding, service number, mating type, short cycle effects and combined into a single lactation record  Permanent environment and management group kept in the model  Effects for inbreeding and heterosis added to the model  DPR included as a correlated trait (data available since 1960) CONCLUSIONS  Multi-trait processing with DPR makes CCR and HCR more accurate  Multi-breed processing allows CCR and HCR evaluations to be available for crossbred animals  The new software allows for different models for different traits and enables easier testing of potential changes to model  Implementation of new software for a MT model for fertility traits was initiated in December 2013  Implementation is scheduled to begin later this year of a multi-trait yield model, and single trait models for somatic cell score and productive life  A remaining challenge is to affordably include genotype information in the software OBJECTIVES  Compare the accuracy of conception rate evaluations from the previous (BLUPF90) and the new software  Examine applications of new software to other traits DATA & METHODS  US national dairy database as of August 2013  Individual breeding records combined to create 13 million CCR lactation records, 3.8 million HCR records  66 million DPR records (correlated trait)  Pedigree records (64.9 million) included old, young and disconnected animals not included previously  Birth year groups before 2000 were combined  Model included: 27 million permanent environment effects 6.8 million herd management groups 274,795 heifer management groups 495 age-parity groups 5 parity groups 6 heifer age groups 300 unknown parent groups 2 regressions for inbreeding and heterosis FUTURE / ADDITIONAL WORK Multi-trait genetic correlations (above diagonal), heritabilities (on diagonal), and phenotypic correlations (below diagonal) Phenotypic and breeding value means for conception rate of heifers and cows born in 2005 expressed as a difference from Holsteins RESULTS (cont.) Poster T044 Abstract #946 ADSA-ASAS-CSAS Joint Meeting July 22, 2014, Kansas City, MO HCRCCRDPR HCR CCR DPR Genetic trends by breed for CCR on all-breed scale Genetic trends by breed for HCR on all-breed scale Correlations of previous evaluation and single trait (ST) and multi-trait (MT) model evaluation for HCR and CCR for bulls born 1996 or later with >50% reliability Breed Females with records (no.) Phenotypic mean (%) Breeding value mean (%) HCRCCRHCRCCRHCRCCR Holstein302,007543, Jersey11,53332,  Brown Swiss1,6204,  7.1  4.5 Guernsey6121,  6.7  7.1 Ayrshire5741,  Milking Shorthorn RESULTS  Additional models combining 6 other traits (milk, fat, and protein yield, somatic cell score, productive life and DPR) were run with the new software on 76.8 million lactations and compared with previous results  All-breed models and genetic parameters were similar to those used in current software Correlations of previous evaluation and single and multi-trait model evaluation from new software for 9,476 Holstein* bulls born with >50 daughters  All breeds passed Interbull method 1 trend test for CCR and all passed method 3 for CCR and HCR, except for Ayrshire CCR  Estimated genetic correlations with other Interbull countries were similar for Holstein; slightly different for other breeds * Other breeds slightly lower  Correlations were higher between previous and ST because previous evaluations were ST Trait / Breed Correlation with previous evaluation Correlation of ST and MT EBV from new software Number of bulls All- breed ST All- breed MT HCR: Holstein ,107 Jersey Brown Swiss CCR: Holstein ,556 Jersey ,390 Brown Swiss Trait Correlation with previous evaluation Correlation of ST and MT EBV from new software STMT Milk Fat Protein Somatic cell score Dau preg. rate Productive life (ST) Productive life (MT)