|
|
Click here to go back to the AGM Page... Feature Presentation: "The
Basics of Cattle Genetic Testing"
James M. Reecy
Education
Awards Dr. Reecy's current areas of research include beef cattle molecular genetics, gene function, and development livestock bioinformatics/database resources. Beef is a highly nutritious and valued food. It is a rich source of protein and micronutrients (vitamins A, B6, B12, D, and E, iron, zinc and more). However, one major factor affecting beef intake has been the nutritional recommendations of dieticians and health professionals. The consumer has been told that it is desirable to decrease the consumption of foods rich in SFA. Often, it is recommended that beef be excluded from the diet because it is rich in SFA and SFA intake has been positively correlated with atherosclerosis and other vascular diseases. However, lipids are not the only nutrients in beef that can impact human health. Iron is a mineral that is required to maintain adequate human health. Iron-containing compounds carry oxygen from the lungs to the rest of the body and regulate cell growth and differentiation. Insufficient iron is harmful resulting in anemia, which can cause weakness, lethargy, muscle fatigue, and shortness of breath. In addition to fatty acids and iron, there are other nutrients like CLA, omega-3 fatty acids, zinc, magnesium, creatinine, creatine, carnitine, vitamin E, vitamin B6 and B12, cholesterol, and sphingolipids that can impact human health. While beef is already a wonderful source of nutrients, there is a huge potential to further enhance beef so that it is an even better nutrient source. It is our contention that U.S. consumers will become increasingly supportive of food sources that they believe help them live a healthier life and that enhancing the nutritional value of beef will increase consumer demand for the product and ensure continued growth of the beef industry. We have determined that the heritability associated with individual fatty acids is very favorable (h2 = 0.25 - 0.45). Recently, we reported on the identification of mutations in Fatty Acid Synthase that were associated with decreased saturation of fat. Thus, producers can begin to select for cattle that produce a healthier product. Currently, we are conducting a large experiment designed to implement whole genome selection for healthfulness traits in cattle. Bovine Respiratory Disease (BRD) complex is the biggest health obstacle the cattle industry faces due to the economic ramifications. Recently, we reported that the potential decrease in performance and carcass merit resulted in an economic loss of $23.23, $30.15, and $54.01 in carcass value when comparing cattle never treated to cattle treated once, twice, or three or more times, respectively. In addition, we have preliminary data with industry fed cattle indicating that the heritability of resistance to BRD is low (h2 = 0.1). In addition, we are interested in the response to vaccination. If we could identify those animals that will respond to vaccination, we should be able to improve the overall health of feedlot cattle. When Myostatin was knocked out in mice, it resulted in a 200% increase in muscle mass. This finding resulted the realization that the double-muscling phenotype in cattle was the result of mutations in Myostatin. While progress has been made into the elucidation of intracellular signaling mechanisms controlled by Myostatin, there is much that we still do not understand. Previously, we evaluated global gene expression levels in wild-type and myostatin-null mice during primary and secondary myotube formation, as well as five weeks postnatal. Interestingly, gene expression changes could be binned into any phenotype one was interested with respect to muscle growth. We went on to report that Wnt4 and sFRPs lie downstream of Myostatin and are most likely involved in regulation of satellite cell proliferation. Recently, we initiated an experiment with myostatin-null mice and M16i obese mice to identify epistatic alleles that control skeletal, skeletal muscle, and adipose growth. As a result of this experiment, we hope to identify alleles that have differential effects in the presence and absence of functional Myostatin. These findings should lead to the development of novel strategies to enhance postnatal skeletal muscle growth. Livestock geneticists have done a wonderful job of identifying regions of the genome that are associated with traits of economic importance. However, they have identified so many QTL that it is no longer feasible for researchers to stay abreast of all publications. To alleviate this problem, we have developed a livestock QTL database where we have curated cattle, chicken and pig QTL. We are working to expand this resource to allow researchers to seamlessly move from QTL information to genomic information to assist them in the identification of causative alleles underlying QTL. As a result of this work, we realized there is a large need to develop a standardized nomenclature for phenotypes. Toward this end, we have developed resources to allow for the collaborative development of an Animal Trait Ontology (ATO). We are currently working with the Rat Genome Database, Mouse Genome Informatics, EADGENE and SABRE to expand this resource. We will use this resource in conjunction with a comparative QTL viewer that we are developing to allow for the exchange of genomic and phenotypic information across multiple species.
Professional Affiliations Koltes, J.E., Z.-L. Hu, E.Fritz, J.M. Reecy. 2009. BEAP: The BLAST Extension and Alignment Program- a tool for contig construction and analysis of preliminary genome sequence. BMC Research Notes (accepted). Schneider, M.J., R.G. Tait, Jr., W.D. Busby, and J.M. Reecy. 2009. An evaluation of bovine respiratory disease complex incidence in feedlot cattle: Fixed sources of variation and genetic parameter estimates. Journal of Animal Science (accepted). Hu, Z.-L., J. Bao, J.M. Reecy. 2008. "CateGOrizer: A Web-Based Program to Batch Analyze Gene Ontology Classification Categories". Online Journal of Bioinformatics 9(2):108-112. Taylor, C.F., D. Field, S.-A. Sansone, J. Aerts, R. Apweiler, M. Ashburner, C. A. Ball, P.-A. Binz, M. Bogue, T. Booth, A. Brazma, R. R. Brinkman, A. M. Clark, E. W. Deutsch, O. Fiehn, J. Fostel, P. Ghazal, F. Gibson, T. Gray, G. Grimes, N. W. Hardy, H. Hermjakob, R. K. Julian, Jr., M. Kane, C. Kettner, C. Kinsinger, E. Kolker, M. Kuiper, N. Le Novère, J. Leebens-Mack, S. E. Lewis, P. Lord, A.-M. Mallon, N. Marthandan, H. Masuya, R. McNally, A. Mehrle, N. Morrison, S. Orchard, J. Quackenbush, J.M. Reecy, D. G. Robertson, P. Rocca-Serra, H. Rodriguez, H. Rosenfelder, J. Santoyo-Lopez, R. H. Scheuermann, D. Schober, B. Smith, J. Snape, K. Tipton, P. Sterk, A. Untergasser, J. Vandesompele, S. Wiemann. 2008. Promoting Coherent Minimum Reporting Requirements for Biological and Biomedical Investigations: The MIBBI Project. Nature Biotechnology 26(8):889-96. Li, P., Z. L. Hu, S. J. Moon, K. T. Do, Y. K. Ha, H. Kim, M. J. Byun, B. H. Choi, M. F. Rothschild, J.M. Reecy, K. S. Kim. 2008. Development of an in silico Coding Gene SNP map in pigs. Animal Genetics 39(4):446-50. Hughes, L.M., J. Bao, Z-L. Hu, V. Honavar, J.M. Reecy. 2008. Animal Trait Ontology (ATO): The importance and usefulness of a unified trait vocabulary for animal species. Journal of Animal Science. 86(6):1485-91. Zhang, S., T.J. Knight, J.M. Reecy, D.C. Beitz. 2008. DNA polymorphisms in bovine fatty acid synthase affect beef fatty acid composition. Animal Genetics 39(1):62-70. Nettleton, D., J. Recknor, J.M. Reecy. 2008. Identification of Differentially Expressed Gene Categories in Microarray Studies Using Nonparametric Multivariate Analysis. Bioinformatics 24(2):192-201. Epub 2007 Nov 27 Karlskov-Mortensen P., Z.-L. Hu, J.M. Reecy, M. Fredholm. 2008. A data resource of 838 porcine microsatellite sequences with repeat motifs of three to six bases. Animal Genetics 39(1):85-6. Epub 2007 Nov 1.
Other
Links
|