Unraveling the phenotypic and genomic background of behavioral plasticity and temperament in North American Angus cattle

Invited review: Phenotyping strategies and genetic background of dairy cattle behavior in intensive production systems-From trait definition to genomic selection

Understanding and assessing dairy cattle behavior is critical for developing sustainable breeding programs and management practices. The behavior of individual animals can provide valuable information on their health and welfare status, improve reproductive management, and predict efficiency traits such as feed efficiency and milking efficiency. Routine genetic evaluations of animal behavior traits can contribute to optimizing breeding and management strategies for dairy cattle but require the identification of traits that capture the most important biological processes involved in behavioral responses. These traits should be heritable, repeatable, and measured in noninvasive and cost-effective ways in many individuals from the breeding populations or related reference populations. Although behavior traits are heritable in dairy cattle populations, they are highly polygenic, with no known major genes influencing their phenotypic expression. Genetically selecting dairy cattle based on their behavior can be advantageous because of their relationship with other key traits such as animal health, welfare, and productive efficiency, as well as animal and handler safety. Trait definition and longitudinal data collection are still key challenges for breeding for behavioral responses in dairy cattle. However, the more recent developments and adoption of precision technologies in dairy farms provide avenues for more objective phenotyping and genetic selection of behavior traits. Furthermore, there is still a need to standardize phenotyping protocols for existing traits and develop guidelines for recording novel behavioral traits and integrating multiple data sources. This review gives an overview of the most common indicators of dairy cattle behavior, summarizes the main methods used for analyzing animal behavior in commercial settings, describes the genetic and genomic background of previously defined behavioral traits, and discusses strategies for breeding and improving behavior traits coupled with future opportunities for genetic selection for improved behavioral responses.

Advancing Dairy and Beef Genetics Through Genomic Technologies

The US beef and dairy industries have made remarkable advances in sustainability and productivity through technological advancements, including selective breeding. Yet, challenges persist due to the complex nature of quantitative traits. While the beef industry has progressed in adopting genomic technologies, the availability of phenotypic data remains an obstacle. To meet the need for sustainable production systems, novel traits are being targeted for selection. Additionally, emerging approaches such as genome editing and high-throughput phenotyping hold promise for further genetic progress. Future research should address the challenges of translating functional genomic findings into practical applications, while simultaneously harnessing analytical methods.

Trait development and genetic parameters of resilience indicators based on variability in milk consumption recorded by automated milk feeders in North American Holstein calves

The implementation of automated milk feeders (AMF) on precision dairy farms has enabled efficient management of large numbers of group-housed replacement calves with reduced labor requirements and improved calf welfare. In this study, we investigated the feasibility of deriving calf resilience indicators based on variability in milk consumption using data from 10,076 North American Holstein calves collected between 2015 and 2021. We modeled and evaluated deviations in observed and predicted daily milk consumption trajectories as indicators of resilience to environmental perturbations. We also analyzed average milk intake and the number of treatments for bovine respiratory disease (BRD) and their genetic correlations with the derived resilience parameters. Milk consumption was recorded using the Förster-Technik AMF. Deviations in cumulative milk intake were modeled using various methods, including quantile regression and the Gompertz function. Ten resilience indicators were derived to quantify the degree and duration of perturbations, including amplitude, perturbation time, recovery time, and deviation velocities. After data editing, genomic data from 9,273 calves and pedigree information from 10,076 calves with 321,388 phenotypic records were used to estimate genetic parameters for 12 traits, including 10 calf resilience indicators as well as average milk intake and treatments for bovine respiratory disease. Substantial phenotypic variability was observed for all calf resilience indicators derived and genetic parameters related to these novel resilience indicators were estimated. The heritability estimates for the resilience traits are as follows: amplitude of the deviation (in L) 0.047 (0.032, 0.064) (HPD interval), perturbation time of deviation (in d) 0.011 (0.0056, 0.016), recovery time of the deviation (in d) 0.025 (0.016, 0.035), maximum velocity of perturbation (L/d) 0.039 (0.024, 0.053), average velocity of perturbation (L/d) 0.038 (0.022, 0.050), area between the curves (L x d) 0.039 (0.027, 0.054), recovery ratio 0.053 (0.036, 0.072), deviation variance 0.049 (0.32, 0.068), log-deviation variance 0.027 (0.016, 0.044), deviation auto-correlation 0.010 (0.0042, 0.017) and number of deviation occurrences 0.023 (0.0094, 0.036). Some of the highlighted genetic correlations observed with average milk consumption include amplitude: 0.569 (0.474, 0.666), perturbation time: -0.534 (-0.73, -0.342), and average velocity: 0.554 (0.432, 0.672). Similarly, the genetic correlations between the number of times treated for BRD with perturbation time was 0.494 (0.251, 0.723), -0.294 (-0.52, -0.095) with number of deviations, and 0.348 (0.131, 0.578) with deviation autocorrelation. This study highlights the genetic influence on various resilience traits in calves, including amplitude, perturbation time, recovery time, and velocity measures of the perturbation. Our findings suggest the need for prioritizing genetic selection based on traits like recovery time, which exhibits higher heritability and a moderate genetic correlation with the number of times a calf is treated for BRD. The combination of AMF data, mathematical modeling, and genomic evaluation provides a comprehensive framework for assessing and breeding more resilient dairy calves in the face of environmental and health challenges.

Is the genetic architecture of behavior exceptionally complex?

Are traits with high levels of plasticity more complex in their genetic architecture, as they can be modulated by numerous different environmental inputs? Many authors have assumed that behavioral traits, in part because they are highly plastic, have an exceptionally complex genetic basis. We quantitatively summarized data from 31 genome-wide association studies (GWAS) and 87 traits in Drosophila melanogaster and found no evidence that behavioral traits have fundamental differences in the number of single-nucleotide polymorphisms or the significance or effect size of those associations, compared with nonbehavioral (morphological or physiological) traits. We suggest the assertion that behavioral traits are inherently more complex on a genetic basis compared with other types of traits should not be assumed true, and merits further investigation.

Genetic evaluation of crossbred Bos indicus cow temperament at parturition

Cow temperament at parturition may be mostly a measure of aggressiveness. The heritability of cow temperament at parturition in Bos taurus cows has been reported to be low. The objectives of this study were to estimate the heritability of cow temperament at parturition, conduct a genome-wide association analysis of cow temperament at the time of parturition, and estimate the correspondence of cow temperament at the time of parturition with cow productive performance and early-life temperament traits in Bos indicus crossbreds. Cow temperament was assessed from 1 to 5 indicating increasing levels of aggressiveness of cows (937 cows and 4,337 parturitions) from 2005 to 2022. Estimates of heritability and repeatability were 0.12 ± 0.024 and 0.24 ± 0.018. The estimates of proportion of phenotypic variance were 0.13 ± 0.019 and 0.02 ± 0.011 for permanent and maternal permanent environmental components, respectively. Estimates of heritability for maximum lifetime temperament score and proportions of temperament scores >1 were 0.18 ± 0.07 and 0.13 ± 0.072. Within cycles (generations), 2-yr-old cows had lower temperament score means than cows in most other age categories. There were low to moderate positive estimates of unadjusted correlation coefficients (r = 0.22 to 0.29; P < 0.05) of unadjusted temperament score with temperament measured on the same females when they were 8 mo old. There were low to moderate positive estimates of correlation coefficients (r = 0.09 to 0.37; P < 0.05) of unadjusted temperament score with calving rate, weaning rate, weaning weight per cow exposed, and weaning weight per 454 kg cow weight at weaning. Cows with the lowest temperament score had lower (P < 0.05) calving and weaning rate than cows in other temperament categories. Within 3 of 5 cycles, cows with the lowest temperament score (totally docile) had lower (P < 0.05) weaning weight per cow exposed than cows in other temperament categories. There were 2 SNP on BTA 4 associated with maximum lifetime temperament score (FDR < 0.05). The non-genetic influence of a cow's mother was documented in her own temperament measured at the time of calving; this may be a consequence of learned behavior. Less aggressiveness displayed by cows at the time of calving may be accompanied by lower reproductive and maternal performance.