Opportunities to Improve Resilience in Animal Breeding Programs

Abstract

Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to the state pertained before exposure to a disturbance. However, indicators for general resilience to environmental disturbances have not yet been defined, and perhaps therefore resilience is not yet included in breeding goals. The current developments on big data collection give opportunities to determine new resilience indicators based on longitudinal data, which can aid to incorporate resilience in animal breeding goals. The objectives of this paper were: (1) to define resilience indicator traits based on big data, (2) to define economic values for resilience, and (3) to show the potential to improve resilience of livestock through inclusion of resilience in breeding goals. Resilience might be measured based on deviations from expected production levels over a period of time. Suitable resilience indicators could be the variance of deviations, the autocorrelation of deviations, the skewness of deviations, and the slope of a reaction norm. These (new) resilience indicators provide opportunity to include resilience in breeding programs. Economic values of resilience indicators in the selection index can be calculated based on reduced costs due to labor and treatments. For example, when labor time is restricted, the economic value of resilience increases with an increasing number of animals per farm, and can become as large as the economic value of production. This shows the importance of including resilience in breeding goals. Two scenarios were described to show the additional benefit of including resilience in breeding programs. These examples showed that it is hard to improve resilience with only production traits in the selection index, but that it is possible to greatly improve resilience by including resilience indicators in the selection index. However, when health-related traits are already present in the selection index, the effect is smaller. Nevertheless, inclusion of resilience indicators in the selection index increases the response in the breeding goal and resilience, which results in less labor-demanding, and thus easier-to-manage livestock. Current developments on massive collection of data, and new phenotypes based on these data, offer exciting opportunities to breed for improved resilience of livestock.

Genotype-by-environment (temperature-humidity) interaction of milk production traits in Australian Holstein cattle

“…Similarly, Bryant et al (2006) suggested the development of customized EBV for specific environments, and (Nguyen et al, 2017) proposed a selection tool that could balance the profit index and heat tolerance. More recently, some authors have demonstrated opportunities for including resilience in breeding goals (Mulder, 2016;Friggens et al, 2017;Berghof et al, 2019). Berghof et al (2019) proposed using the slope of the reaction norms as an indicator trait for resilience to heat stress and calculating economic values for selection index based on the reduced labor costs associated with the management of heat-stressed animals.…”

“…Resilient animals are minimally affected by environmental disturbances (Colditz and Hine, 2016;Berghof et al, 2019), and their performances are expected to be comparatively consistent under different heat stress conditions. Our results suggest that the proportion of resilient sires has decreased in recent years (Figure 8), confirming the increasing relevance of G × E in the study population.…”

“…developed a reaction norm (RM) model, which assumes a range of heat load index delimited by a threshold value, beyond which production begins to decrease linearly with increasing THI. The RM approach is appealing because it allows environmental sensitivity (ES) of animals to be characterized based on the slope coefficient of the reaction norms (de Jong and Bijma, 2002), such that if the slope value of the RM is zero or close to zero, or if the trend of the RM is consistent across the environmental gradient, an animal is considered to be resilient; otherwise it is labeled "plastic" or sensitive to environmental changes (de Jong and Bijma, 2002;Berghof et al, 2019). These RM models have been widely used to evaluate genetic components of heat tolerance in dairy cattle in various countries, including the United States (Bohmanova et al, 2005;Aguilar et al, 2009), Spain (Carabaño et al, 2014), Italy (Bernabucci et al, 2014), and Germany (Hammami et al, 2015).…”

Beef cattle that respond differently to fescue toxicosis have distinct gastrointestinal tract microbiota

“…In order to identify which of the three periods better expressed the impact of FT on performance, two additional analyses were performed. First, the residual variance () of the data for each of the window periods were estimated with the model below, in order to identify the period in which greater variability of the data was observed, which is an indication of response to diseases [23]: where AWG ijk , μ , L i , p j , b 1 , iBW k , and e ijk are as previously defined in Eq. 1.…”

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

“…The h 2 v,litter can be interpreted as the reliability of EBVs based on a single litter. More recently, Berghof et al (2019) proposed the heritability of the residual variance for repeated records: ) and r records is the repeatability of the residual variance. Berghof et al (2019) show that reasonable heritabilities of 0.2 can be obtained at the animal level when having at least 50 observations, which is in agreement with recent empirical studies by Putz et al (2018) and Poppe et al (in press).…”