Marker weighting improves single-step genomic prediction reliabilities of udder health traits in Nordic Red and Jersey dairy cattle populations.

The standard single-step genomic prediction model assumes that all SNP markers explain an equal amount of genetic variance, which, however, may not be true. This is because SNPs are located in or near different genes with different functions. Therefore, it seems logical to consider SNP marker-specific weights when predicting genomic breeding values.

Genetic aspects of some reproductive, udder health and energy status traits in Holstein cows.

The objective of this study was to estimate heritability as well as genetic and environmental relationships between days to first heat (DFH), days to first service (DFS), interval from calving to conception (ICC), calving interval (CI) and number of inseminations per conception (NIS) with mastitis (Mast), number of mastitis occurrence (NumMast), different measures of somatic cell count (SCC) and fat to protein ratio (F:P) in the first lactation of Holstein cows in Iran using linear and threshold animal and sire models. The 33851 first lactation records of Holstein cows from five large dairy herds with calving dates from March 2002 to September 2014 were analyzed with univariate and bivariate linear and threshold animal and sire models using Gibbs sampling methodology. Data from parity one to nine comprising 62483 records were used to conduct repeatability model analysis for reproductive traits.

Appropriate selection indices for functional traits in dairy cattle breeding schemes.

The objective of this study was to establish different single or multiple trait selection indices to calculate genetic and economic gains by combining some production, reproduction and udder health traits in a population similar to the overall practical situation in Iran, with and without imposing restrictions on genetic change for some traits. The SelAction software was used to perform the analyses based on selection index theory through a deterministic model. Results indicated that among established indices, the index that showed the highest genetic gain for milk yield did not maximize the total genetic and economic gains.