The genetic architecture of complete blood counts in lactating Holstein dairy cows.

Complete blood counts (CBCs) measure the abundance of individual immune cells, red blood cells, and related measures such as platelets in circulating blood. These measures can indicate the health status of an animal; thus, baseline circulating levels in a healthy animal may be related to the productive life, resilience, and production efficiency of cattle. The objective of this study is to determine the heritability of CBC traits and identify genomic regions that are associated with CBC measurements in lactating Holstein dairy cattle. The heritability of CBCs was estimated using a Bayes C0 model. The study population consisted of 388 cows with genotypes at roughly 75,000 markers and 16 different CBC phenotypes taken at one to three time points (n = 33, 131, and 224 for 1, 2, and 3 time points, respectively). Heritabilities ranged from 0.00 ± 0.00 (red cell distribution width) to 0.68 ± 0.06 (lymphocytes). A total of 96 different 1-Mb windows were identified that explained more than 1% of the genetic variance for at least one CBC trait, with 10 windows explaining more than 1% of the genetic variance for two or more traits. Multiple genes in the identified regions have functions related to immune response, cell differentiation, anemia, and disease. Positional candidate genes include RAD52 motif-containing protein 1 (RDM1), which is correlated with the degree of immune infiltration of immune cells, and C-X-C motif chemokine ligand 12 (CXCL12), which is critically involved in neutrophil bone marrow storage and release regulation and enhances neutrophil migration. Since animal health directly impacts feed intake, understanding the genetics of CBCs may be useful in identifying more disease-resilient and feed-efficient dairy cattle. Identification of genes responsible for variation in CBCs will also help identify the variability in how dairy cattle defend against illness and injury.

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle.

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.