Location: Genetics, Breeding, & Animal Health
2010 Annual Report
Objective 2. Develop approaches, methods, and software to support efficient conversion of QTL data into DNA markers with predictive merit. It has been established that DNA sequence variation among cattle contributes to differences in economically important traits between individual animals. Our overall hypothesis is that we can successfully identify specific DNA markers that track functional variation, and develop new methods to make the process of marker identification and testing more efficient.
Objective 3. Develop DNA marker systems with predictive merit for phenotypes important to cattle production in the United States, and characterize their effects on a wide range of economically important traits. The hypothesis is that single nucleotide polymorphisms (SNP) can be identified that are in linkage disequilibrium (LD) with functional DNA sequence variation causing effects on production traits. The corollary hypothesis is that an SNP or set of SNP can have sufficient predictive merit in a wide range of production settings and breed backgrounds, permitting Marker Assisted Selection (MAS) to improve herd genetics and Marker Assisted Management (MAM) to classify animals by genetic potential. The starting point for marker development is initial discovery of QTL positions in the genome. For the current CRIS cycle, three sources of QTL will be utilized. First, published bovine QTL developed at USMARC or at other institutions provide QTL targets. More than 15 QTL for just the two traits of meat tenderness and marbling have been reported. Second, development of comparative QTL database in Objective 2a is expected to identify additional target regions. Finally, we propose to use WGA approach to identify QTL using the SNP developed in Objective 2b. Whichever method is used to provide initial focus on genomic segments, we will develop an additional set of targeted SNP markers for testing to identify marker systems with the most consistent and widely applicable predictive merit. Below we describe the approaches that will be used, the details of proposed WGA studies, and marker system testing. As in the expiring CRIS projects, our focus will be on phenotypes of meat quality (tenderness and marbling), yield, and feed efficiency, however in this CRIS cycle we propose to incorporate the phenotypes available on cows to examine reproductive longevity and success.
Objective 4. Evaluate DNA marker systems in use by industry for their effectiveness in a variety of genetic backgrounds and potential impact on a range of production traits. The hypothesis is that utility of marker systems may depend on genetic background, or have unintentional effects on other traits than that for which the marker was developed. In many cases, data supporting the assertion of association.
Major efforts include continued annotation of the genome sequence expanding knowledge of gene content and boundaries and identify genomic regions encoding for RNA with important direct regulatory functions. A manuscript detailing the Bovine Gene Atlas (a description of the array of genes expressed in over 90 normal, apparently healthy cattle tissues from fetal, juvenile, and adult animals) was prepared to complement the web-based browser for viewing the data, and describes several unique discoveries regarding gene expression in cattle. Among other uses, this data is useful for determining the likelihood a given gene might be responsible for differences in animal characteristics. A parallel effort involved the application of the latest sequencing technology to examine the complete repertoire of the protein-coding class of RNA in muscle and fat tissues, the most comprehensive look at the “transcriptome” yet available. This data provided a large amount of new information on the boundaries of genes expressed in these tissues, and the different subtypes of RNA molecules that are produced from a single gene. A complementary effort examined microRNA abundance in four different bovine skeletal muscles and three adipose (fat) tissues. MicroRNA are a class of small non-protein coding RNAs that regulate gene translation and subsequent developmental decisions, and the data help to evaluate the role microRNA may play in development and growth of skeletal muscle and adipose tissue in cattle. A collaborative effort extended this study by generating microRNA profiles of over 80 normal cattle tissues to create a “microRNA Atlas” of cattle.
Another major effort was devoted to exploring application of high density genotyping arrays, which were developed in part through efforts of the first two years of the project, to identify genomic regions harboring DNA sequence variation affecting production traits. Numerous such regions were identified for a wide range of traits using an array with 50,000 markers. For example, candidate genes were identified in a genomic region of chromosome 6 that shows consistent association with incidence of pinkeye and respiratory disease, allowing these genes to be targeted for further marker development to provide assays with predictive merit to the industry. In addition, genomic regions associated with feed intake, gain on feed, and feed efficiency measures were identified. Finally, the effects of selection using markers in two genes associated with muscling and meat tenderness were evaluated. Results support that selection permits gains in muscle area, retail product yield, and fatness, with no detectable detrimental effects on other off-target traits.
Snelling, W.M., Allan, M.F., Keele, J.W., Kuehn, L.A., Mcdaneld, T.G., Smith, T.P., Sonstegard, T.S., Thallman, R.M., Bennett, G.L. 2010. Genome-Wide Association Study of Growth in Crossbred Beef Cattle. Journal of Animal Science. 88(3):837-848.
Frylinck, L., Van Wyk, G.L., Smith, T.P., Strydom, P.E., van Marle-Koster, E., Webb, E.C., Koohmaraie, M., Smith, M.F. 2009. Evaluation of Biochemical Parameters and Genetic Markers for Association with Meat Tenderness in South African Feedlot Cattle. Meat Science. 83:657-665.
Liu, G., Hou, Y., Zhu, B., Cardone, M.F., Jiang, L., Cellamare, A., Mitra, A., Alexander, L.J., Coutinho, L.L., Gasbarre, L.C., Heaton, M.P., Li, R.W., Matukumalli, L.K., Nonneman, D.J., De A Regitano, L.C., Smith, T.P., Song, J., Sonstegard, T.S., Van Tassell, C.P., Eichler, E.E., Mcdaneld, T.G., Keele, J.W. 2010. Analysis of copy number variations among cattle breeds. Genome Research. 20:693-703.
Sanchez Castano, C., Smith, T.P., Wiedmann, R.T., Vallejo, R.L., Salem, M., Yao, J., Rexroad Iii, C.E. 2009. Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library. Biomed Central (BMC) Genomics. 10:559.
Meyers, S.N., McDaneld, T.G., Swist, S.L., Marron, B.M., Steffen, D.J., O'Toole, D., O'Connell, J.R., Beever, J.E., Sonstegard, T.S., Smith, T.P. 2010. A Deletion Mutation in Bovine SLC4A2 is Associated with Osteopetrosis in Red Angus Cattle. Biomed Central (BMC) Genomics. 11:337.
Durso, L.M., Harhay, G.P., Smith, T.P.L., Bono, J.L., Desantis, T.Z., Harhay, D.M., Andersen, G.L., Keen, J.E., Laegreid, W.W., Clawson, M.L. 2010. Animal-to-Animal Variation in Fecal Microbial Diversity among Beef Cattle. Applied and Environmental Microbiology. 76(14):4858-4862.
Ramos, A.M., Crooijmans, R.P.M.A., Affara, N.A., Amaral, A.J., Archibald, A.L., Beever, J.E., Bendixen, C., Churcher, C., Clark, R., Dehais, P., Hansen, M.S., Hedegaard, J., Hu, Z.L., Kerstens, H.H., Law, A.S., Megens, H.J., Milan, D., Nonneman, D.J., Rohrer, G.A., Rothschild, M.F., Smith, T.P.L., Schnabel, R.D., Van Tassell, C.P., Taylor, J.F., Wiedmann, R.T., Schook, L.B., Groenen, M.A.M. 2009. Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology. PLoS One 4(8):E6524. p. 1-13.