2012 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.
The main 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 developed last year 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 was used for rapid estimation of marker effects. It was determined that predicted breeding values using the more expensive, HD arrays were not significantly more informative than the less expensive, lower density arrays, an important result for the industry. The imputation approach identified markers associated with fertility in cows, a major issue for cattle producers in the U.S., providing an opportunity to use marker assisted management and marker assisted selection to improve overall herd fertility and avoid economic losses due to supporting cows that fail to conceive each year. In addition, a promising approach to identifying causative variation (which provides the most robust and predictive markers) by incorporation of low coverage whole genome sequencing of key animals in the population was developed and is being tested. Regardless of whether a marker is predictive for causative variation or is itself the cause, it may have simple or complicated association to the traits that are the target of selection that might influence how the marker(s) are best used. To demonstrate this concept and develop appropriate strategies, two markers shown to influence carcass fatness were examined in depth through a multi-year selection process and were shown to have complex relation to fat and meat tenderness traits. These complex associations may be important for marker-predicted performance schemes.
Another effort was continued annotation of the bovine genome sequence, including a collaborative effort to examine 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. This data is complete and analyzed, and a manuscript is being drafted. An international collaborative effort to improve the draft genome was launched, and the current Project led the effort to incorporate optical mapping into the new assembly. This ongoing effort is expected to culminate in FY2013 with a new, higher quality assembly and annotation of the cattle genome. Part of the improvement will come from comparative genomics with Bos indicus cattle, Water Buffalo, and Goat genomes, for which we provided substantial support and effort during FY2012.
Casas, E., Garcia, M.D., Wells, J., Smith, T.P.L. 2011. Association of single nucleotide polymorphisms in the ANKRA2 and CD180 genes with bovine respiratory disease and presence of Mycobacterium avium subsp. paratuberculosis. Animal Genetics. 42:571-577.
Rolfe, K.M., Snelling, W.M., Nielsen, M.K., Freetly, H.C., Ferrell, C.L., Jenkins, T.G. 2011. Genetic and phenotypic parameter estimates for feed intake and other traits in growing beef cattle, and opportunities for selection. Journal of Animal Science. 89:3452-3459.
Zanella, R., Casas, E., Snowder, G., Neibergs, H. L. 2011. Fine mapping of loci on BTA2 and BTA26 associated with bovine viral diarrhea persistent infection and linked with bovine respiratory disease in cattle. Frontiers in Genetics. 2:82. Available: http://www.frontiersin.org/livestock_genomics/10.3389/fgene.2011.00082/abstract.
Snelling, W.M., Cushman, R.A., Fortes, M., Reverter, A., Bennett, G.L., Keele, J.W., Kuehn, L.A., McDaneld, T.G., Thallman, R.M., Thomas, M.G. 2012. How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females. Journal of Animal Science. 90:1152-1165.
Miles, J.R., McDaneld, T.G., Wiedmann, R.T., Cushman, R.A., Echternkamp, S.E., Vallet, J.L., Smith, T.P.L. 2012. MicroRNA expression profile in bovine cumulus–oocyte complexes: Possible role of let-7 and miR-106a in the development of bovine oocytes. Animal Reproduction Sciences. 130(1-2):16-26.
Bono, J.L., Smith, T.P., Keen, J.E., Harhay, G.P., McDaneld, T.G., Mandrell, R.E., Jung, W., Besser, T.E., Gerner-Smidt, P., Bielaszewska, M., Karch, H., Clawson, M.L. 2012. Phylogeny of Shiga toxin-producing Escherichia coli O157 isolated from cattle and clinically ill humans. Molecular Biology and Evolution. 29(8):2047-2062. doi: 10.1093/molbev/mss072.
McDaneld, T.G., Kuehn, L.A., Thomas, M.G., Snelling, W.M., Sonstegard, T.S., Matukumalli, L.K., Smith, T.P., Pollak, E.J., Keele, J.W. 2012. Y are you not pregnant: identification of Y chromosome segments in female cattle with decreased reproductive efficiency. Journal of Animal Science. 90(7):2142-2151.