Strategies and tools for genetic selection in dairy cattle and their application to improving animal welfare

Genetic improvement of farm animals, especially selection within breeds focussed on high production and efficiency, is often cited as a potential threat to animal welfare. However, many animal welfare issues can be addressed, at least partially, by animal breeding and genetics. In this chapter, we explore the relationship between genetic selection and animal welfare, the strategies and tools for genetic improvement and how they can contribute to improved animal welfare. A growing public awareness of animal welfare and environmental issues has led to breeding goals being broadened beyond farmer profitability. As animal welfare and behaviour are complex and multi-factorial, so the emergence of selection indices that include a large number of traits to optimise animal welfare in a way that is consistent with enterprise sustainability for the farmer is necessary. This trend is likely to continue and will be aided by the advent of new technologies for measuring animal welfare in conjunction with DNA-based predictions of genetic merit (genomic selection). The dairy cattle industry has been exemplary for the application of genomic selection, in addition to enabling selection decisions to be made earlier in life, it can be used to select for traits where it was not possible to select for previously. These include important welfare-related traits, such as improved disease resistance and heat tolerance. Dairy cattle breeding is a very international activity with just a few breeding companies dominating the market in semen for the most numerous breeds, especially the Holstein. Consequently, genetic diversity within breeds is diminishing and although genetic gain has been significant, the rate of inbreeding now presents itself as a threat to the future success of breeding programmes. A greater emphasis on diversity in breeding programmes and the traits under selection is needed as major themes in research and application. Innovation in methods to measure these new traits, (e.g. molecular phenotyping, sensor development, digitalisation data science, etc.) could dramatically transform selection for animal welfare, as these technologies can enable large-scale objective measurements of animal behaviours. In addition to animal-based outcome measures, factors like housing, feeding, specific management practices pose other risks to welfare. Risk factors and their interactions have an impact on the development of diseases or other challenges to welfare. Collaborative efforts between animal behaviour scientists, geneticists, engineers, data scientists, and others will potentially provide solutions to these challenges.