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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #416037

Research Project: Increasing Accuracy of Genomic Prediction, Developing Algorithms, Selecting Markers, and Evaluating New Traits to Improve Dairy Cattle

Location: Animal Genomics and Improvement Laboratory

Title: Validating genomic predictions for economic traits in purebred U.S. dairy heifers

Author
item Toghiani, Sajjad
item Vanraden, Paul
item Null, Daniel
item Miles, Asha
item Van Tassell, Curtis - Curt

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/14/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: While previous studies primarily focused on validating genomic predictions in bulls, this study shifted its focus to heifers to validate genomic predictions based on their own recorded data. Dairy herds may encounter obstacles and barriers when implementing genomic selection strategies in farms. These challenges stem from several critical factors. Limited access to education or guidance contributes to the difficulties, but more pressing issues include the labor-intensive process of genotyping, the hassle of correcting pedigree errors, and the significant time lag in obtaining results for the first month of a calf's life. These practical obstacles often outweigh concerns about the high upfront costs of genotyping. Furthermore, there is a prevailing skepticism regarding the effectiveness of genomic predictions and whether the potential return on investment justifies the associated expenses. To address this gap, researchers conducted a comprehensive genomic validation study involving only U.S. dairy heifers across different breeds. The official within-breed genomic predicted transmitting ability (PTA) outperformed parent averages in predicting performance deviations, also known as yield deviations, for economic traits of purebred U.S. dairy cows. The improvements in prediction ability were substantial for most traits in the large purebred populations of Holsteins and Jerseys. However, smaller purebred populations with limited historical data and fewer genotyped heifers experienced relatively smaller gains in predictive ability. These findings emphasize the potential advantages of incorporating genomic predictions in dairy farming, suggesting greater benefits for herd owners.

Technical Abstract: Most genotypes in the National Cooperator Database now originate from cows, but most previous studies validating genomic predictions have primarily focused on bulls. This study paired official within-breed genomic predicted transmitting ability (GPTA) and parent average (PA) for genotyped heifer calves born between 2019 and 2021 using the August 2021 database with their corresponding yield deviations (YD) for 17 different traits. The YD data became available when the heifers completed their first lactation and were extracted from the August 2023 database in which at least one YD value for those 17 traits existed for each genotyped heifer record. The separate breed analyses included records for 219 Ayrshires (AY), 2,715 Brown Swiss (BS), 1,055 Guernseys (GU), 949,904 Holsteins (HO), and 125,275 Jerseys (JE). However, due to timing or recording patterns, each trait had missing or incomplete YD data, leading to unbalanced distributions of records across traits. The squared accuracy of genomic prediction, or genomic reliability (r2), was divided by the corresponding heritability for each trait, as only the heritable portion of cow records could be predicted, and this reliability varied across different traits and breeds. For HO and JE, the predictive ability of GPTA outperformed PA in predicting cow YD for yield, productive life, somatic cell score, fertility, and health traits. The improvement ranged from 33% to 142% compared to the predictive ability of the PA. However, the results for AY, BS, and GU breeds were less consistent due to the smaller number of genotyped heifers. The r2 gains in those breeds were smaller and aligned with the published reliabilities of GPTA. Weighted and unweighted regressions of YD on GPTA and PA traits mostly exceeded the expected value of 2.00 when predicting the future trait YD using GPTA or PA. The larger number of observations and lower standard error of the weighted regression coefficient prediction in HO and JE breeds contributed to more stable and consistent regression coefficients for all traits except milk fever and heifer livability. Our study suggests that herd owners may experience greater benefits from genomics than originally forecast.