2011 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, including publication of 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) to complement the web-based browser for viewing the data. Among other uses, this data is useful for determining the likelihood a given gene might be responsible for differences in animal characteristics. A complementary, collaborative effort examined microRNA abundance in a wide array of over 90 bovine 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.
Another major effort was devoted to exploring application of high density (735,000 markers) genotyping arrays (HD), 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. An approach was developed to make use of data from HD arrays on relatively few animals, and apply them to a broader population with lower density (48,000 markers) genotyping information, by imputing genotypes and developing an approach for rapid estimation of marker effects. This approach was applied to examine heifer fertility traits, and led to a discovery regarding the occurrence of Y chromosome segments in cows (described in accomplishments section). In addition, a “gene-set” analysis, incorporating the associations for multiple traits to identify genes known to participate in particular networks and pathways, was applied to gene sets affecting tenderness and heifer fertility, and with collaborators from New Mexico and Australia, to gene networks in the bovine hypothalamus affecting heifer growth and fertility.
Heifers from populations selected using combinations of markers are being grown at two rates to understand if specific genetic markers are associated with developmental programming effects on subsequent reproduction. Data are being collected as cows mature to address this question. Single Nucleotide Polymorphisms (SNP) in the TLR and GABA gene clusters were developed. These genetic markers were evaluated in a population derived from Hereford, Angus, Beefmaster, Brangus, Bonsmara, and Romosinuano (n= 580). Results indicate that SNP within the gene cluster of GABA were associated with bovine respiratory disease. Markers on the TLR cluster are unassociated with bovine respiratory disease. Bovine chromosome 6 harbors genes associated with incidence of respiratory disease.
Casas, E., Thallman, R.M., Cundiff, L.V. 2011. Birth and weaning traits in crossbred cattle from Hereford, Angus, Brahman, Boran, Tuli, and Belgian Blue sires. Journal of Animal Science. 89:979-987.
Neibergs, H., Zanella, R., Casas, E., Snowder, G.D., Wenz, J., Neibergs, J.S., Moore, D. 2011. Loci on Bos taurus chromosome 2 and Bos taurus chromosome 26 are linked with bovine respiratory disease and associated with persistent infection of bovine viral diarrhea virus. Journal of Animal Science. 89:907-915.
Lindholm-Perry, A.K., Rohrer, G.A., Kuehn, L.A., Keele, J.W., Holl, J.W., Shackelford, S.D., Wheeler, T.L., Nonneman, D.J. 2010. Genomic regions associated with kyphosis in swine. BMC Genetics. 11:112.
Cepica, S., Bartenschlager, H., Ovilo, C., Zrustova, J., Masopust, M., Fernandez, A., Lopez, A., Knoll, A., Rohrer, G.A., Snelling, W.M., Geldermann, H. 2010. Porcine NAMPT gene: search for polymorphism, mapping and association studies. Animal Genetics. 41:646-651.
Harhay, G.P., Smith, T.P.L., Alexander, L.J., Haudenschild, C.D., Keele, J.W., Matukumalli, L.K., Schroeder, S.G., Van Tassell, C.P., Gresham, C.R., Bridges, S.M., Burgess, S.C., Sonstegard, T.S. 2010. An atlas of bovine gene expression reveals novel distinctive tissue characteristics and evidence for improving genome annotation. Genome Biology [online serial]. 11:R102.
Snelling, W.M., Allan, M.F., Keele, J.W., Kuehn, L.A., Thallman, R.M., Bennett, G.L., Ferrell, C.L., Jenkins, T.G., Freetly, H.C., Nielsen, M.K., Rolfe, K.M. 2011. Partial-genome evaluation of postweaning feed intake and efficiency of crossbred beef cattle. Journal of Animal Science. 89:1731-1741.
Durso, L.M., Harhay, G.P., Smith, T.P., Bono, J.L., Desantis, T.Z., Clawson, M.L. 2011. Bacterial community analysis of beef cattle feedlots reveals that pen surface is distinct from feces. Foodborne Pathogens and Disease. 8(5):647-649. Available: DOI: 10.1089/fpd.2010.0774.
Durso, L.M., Harhay, G.P., Bono, J.L., Smith, T.P. 2011. Virulence-associated and antibiotic resistance genes of microbial populations in cattle feces analyzed using a metagenomic approach. Journal of Microbiological Methods. 84: 278-282.
Garcia, M.D., Matukumalli, L., Wheeler, T.L., Shackelford, S.D., Smith, T.P., Casas, E. 2010. Markers on bovine chromosome 20 associated with carcass quality and composition traits and incidence of contracting infectious bovine keratoconjunctivitis. Animal Biotechnology. 21(3):188-202.