Genomics
Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Genetic trends of American dairy cattle breeds were examined by Guinan et al (2023) (Journal of Dairy Sciencehttps://doi.org/10.3168/jds.2022-22205) to determine the genetic gain since the implementation of genomic evaluations in 2009. Inbreeding levels and generation intervals were also investigated. Breeds included Ayrshire, Brown Swiss, Guernsey, Holstein and Jersey. Mean genomic predicted breeding values were analysed per year to calculate genetic trends for bulls and cows. The data set contained 154 008 bulls and 33 022 242 cows born since 1975. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat and protein yields, somatic cell score, productive life, daughter pregnancy rate, and livability predicted breeding values were documented. In 2017, 100% of bulls in this data set were genotyped.
Overall, production traits have increased steadily over time. The Holstein and Jersey breeds have benefited most from genomics, with up to 192% increase in genetic gain since 2009. Owing to the low number of observations, trends for Ayrshire, Brown Swiss, and Guernsey are difficult to infer. Trends in fertility are most substantial; particularly, most breeds are trending downwards and the daughter pregnancy rate for Jersey breed has been decreasing steadily since 1975 for bulls and cows.
Levels of genomic inbreeding are increasing in Holstein bulls and cows. In 2017, genomic inbreeding levels were 12.7% for bulls and 7.9% for cows. A suggestion to control this is to include the genomic inbreeding coefficient with a negative weight to the selection index of bulls with high future genomic inbreeding levels. For sires of bulls, the current generation intervals are 2.2 years in Holstein, 3.2 years in Jersey, 4.4 years in Brown Swiss, 5.1 years in Ayrshire, and 4.3 years in Guernsey. The authors concluded that increased education could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and genetic diversity in the genomic selection era.
Claw diseases and mastitis are the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed.
Schneider et al (2023) (Journal of Dairy Sciencehttps://doi.org/10.3168/jds.2022-22312) attempted a detailed analysis of milk production and disease traits as well as their interrelationship using 50K genotypes, raw phenotypes, and the pedigree data of 34 497 primiparous Holstein cows with lactation records for milk and disease traits collected between 2015 and 2020. They performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, they generated genome-wide association study summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations.
The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher between 0.27 for milk energy yield and 0.48 for fat:protein ratio. Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (−0.07).
The genomic analysis revealed significant single nucleotide polymorphisms for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, they found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas they did not find significantly trait-associated single nucleotide polymorphisms for the other disease traits. These results confirm the known genetic background of disease and milk production traits and reveal additional knowledge about the localisation of regions with shared genetic effects on these trait complexes.
Welfare and herd size
The structural change toward larger dairy farms is often criticised because it supposedly has a negative effect on animal welfare. Lindena and Hess (2022) (Journal of Dairy Sciencehttps://doi.org/10.3168/jds.2022-21906) investigated this criticism using cross-sectional survey data from 3085 German farms. Their sample closely resembled the diverse structures of dairy farming in Germany and covered a wide range of dairy farm sizes (7–2900 cows per farm, mean 122). They developed an animal welfare index in close consultation with experts along the dairy value chain (e.g. farm animal welfare scientists, farmers, dairy representatives).
Results showed that larger farms tended to achieve a better animal welfare index than smaller farms. However, the effect size was small. Nevertheless, in contrast to the widespread assumption in public discussion, larger dairy herds were not necessarily associated with poorer animal welfare. In all herd size classes, they found a large variation of animal welfare index between herds.
As many of us would have expected, they also found that the knowledge and skills of the farm manager and the amount of time devoted to animals had a positive effect on the animal welfare index.