Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins.

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, termed ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss (ML) estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively.

Longitudinal genome-wide association analysis using a single-step random regression model for height in Japanese Holstein cattle.

Growth traits, such as body weight and height, are essential in the design of genetic improvement programs of dairy cattle due to their relationship with feeding efficiency, longevity, and health. We investigated genomic regions influencing height across growth stages in Japanese Holstein cattle using a single-step random regression model. We used 72,921 records from birth to 60 mo of age with 4,111 animals born between 2000 and 2016.

Longitudinal genetic analysis of semen production traits in Holstein bulls according to a random regression animal models on age.

Here we used random regression animal models (RRAMs) to investigate genetic change over age in the semen volume (VOL) and sperm concentration (CON) of Holstein bulls. We used 35,294 collection records from 1284 Holstein bulls and their 4166 pedigree records. The models included year and month of collection, collection place, collection method, and number of collections attempted for each day and month of age (second-order regressions) as fixed effects; technician as a random effect; and additive genetic and permanent environment as random regressions (first-order regressions).