Heritability and Repeatability Estimates for Milk Production Traits Using Phenotypic, Pedigree-Based and Genomic Data of Serbian Holstein Cows
2023
Štrbac Ljuba | Dedović Nebojša | Trivunović Snežana | Janković Dobrila | Šaran Momčilo | Stanojević Dragan | Đedović Radica | Pracner Doni
This research aims to estimate heritability and repeatability based on the data on milk production traits (MY – milk yield; FY – milk fat yield; FC – milk fat content; PY – milk protein yield and PC – milk protein content) as well as pedigree and genomic information. A total of 6,041 animals were included in the research, while 2,565 of them had data for milk production traits. In order to form a genomic relationship matrix, 58K SNP data were used for a total of 1,491 cows. Several software tools were used in the preparation and analysis of data, which were provided by the Central Breeding Organization, Department of Animal Science, Faculty of Agriculture, University of Novi Sad. PreGSF90, in combination with RENUMF90, was used for quality control of genomic information. Genetic analysis was performed in WOMBAT software by the REML using standard repeatability univariate analysis (BLUPpe) and repeatability models for genomic prediction (GBLUPpe and ssGBLUPpe). In all three analyses, the highest heritability (0.410, 0.378 and 0.389, respectively) and repeatability (0.449, 0.429 and 0.440, respectively) were calculated for FC. Heritability estimates for all other traits were lower. Heritability ranged from 0.158 to 0.185 for MY, from 0.166 to 0.178 for FY, from 0.141 to 0.154 for PY and from 0.135 to 0.221 for PC. Heritability estimates indicate that it is possible to achieve genetic improvement but it is necessary to introduce the best model for prediction of breeding values of cow.
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