|Thallman, Richard - Mark|
Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 6/18/2007
Publication Date: 10/23/2007
Citation: Thallman, R.M., Koohmaraie, M. 2007. Opportunities for collaborative phenotyping for disease resistance traits in a large beef cattle resource population [Abstract]. International Symposium on Animal Genomics for Animal Health, October 23-25, 2007, Paris, France. Page 52, Poster No. PA-057. Interpretive Summary:
Technical Abstract: The Germplasm Evaluation (GPE) Project at the U.S. Meat Animal Research Center (USMARC) produces about 3,000 calves per year in support of the following objectives: identification and validation of genetic polymorphisms related to economically relevant traits (ERT), estimation of breed and heterosis effects among 16 breeds for ERT, and estimation of genetic correlations among ERT and physiological indicator traits (PIT). The ERT include dystocia, survival, growth, carcass, meat quality, feed efficiency, reproductive, longevity, and maternal traits, as well as records of the diagnoses and treatments of naturally occurring diseases at USMARC. These include bovine respiratory disease, pinkeye, footrot, calf scours, failure of passive transfer, anaplasmosis, and bluetongue. Opportunities exist for collaboration in the development and collection of PIT phenotypes, including antibodies, cytokines, or other indicators of immune response to naturally occurring diseases or vaccination. Challenge experiments in which animals are infected with disease-causing agents will not be conducted at USMARC; however, a small number of animals can be transferred to other facilities. Other PIT could include gene expression, proteomics, metabolomics, and remote sensing of body temperature, respiration rate, or other parameters indicative of disease status. Other areas of potential collaboration include detailed diagnosis (identification of disease causing organisms, etc.) of treated animals, collaborative development of epidemiological statistical models that would extract more information from the records of diagnoses and treatments, or genetics of pharmacokinetics. Concentrating a variety of different phenotypes and research approaches on the same population makes each component much more valuable than it would be individually.