1a. Objectives (from AD-416)
OBJECTIVE 1. Characterize quantitative and molecular genetic variation between and within breeds for traits that affect life-cycle efficiency of beef cattle. Sub-objective 1A. Characterize direct and maternal breed and heterosis effects among diverse breeds of cattle, and genetic variances and covariances within breeds for calving ease, survival, rate and efficiency of growth, carcass composition, meat quality, age and weight at puberty, reproduction, maternal performance, cow size, and herd life. Sub-objective 1B. Identify and fine map QTL regions that affect quality of beef and efficiency of production. Sub-objective 1C. Determine the efficiency of feed use among mature cows during the production interval from parturition until weaning. Sub-objective 1D. Identify genetic components associated with bovine disease resistance. Sub-objective 1E. Characterize genomic diversity among a broad sample of highly influential germplasm in the U.S. beef industry. OBJECTIVE 2. Examine potential interactions of genetically diverse breeds of cattle with climatic or nutritional environments. OBJECTIVE 3. Evaluate breeds to create an easy-care maternal line of hair sheep for use in low-input production systems. Sub-objective 3A. Evaluate wool and hair breeds in intensive and low-input production systems during traditional fall breeding and for fertility during challenging spring breeding. Sub-objective 3B. Evaluate life-cycle productivity of reciprocal crosses between the Romanov and Rambouillet breeds. Sub-objective 3C. Create an easy-care maternal line of hair sheep. OBJECTIVE 4. Evaluate power of experimental designs to estimate quantitative and molecular genetic parameters. OBJECTIVE 5. Develop statistical theory and computational algorithms to incorporate DNA information and multi-breed comparisons into genetic evaluations of beef cattle.
1b. Approach (from AD-416)
Genetic variation among and within breeds, including allelic variation, provides a foundation for genetic improvement through selection and for management of genetic effects through crossbreeding (or mating) systems. Improvement of production efficiency and sustainability of beef cattle and sheep production systems are dependent on greater knowledge of genetic effects on fundamental traits affecting life-cycle efficiency such as fertility, prolificacy, maternal ability, offspring survival, health, longevity, and adaptation to production environments. Two broad approaches will be pursued: 1) large-scale animal experimentation and 2) development and application of statistical theory and software to support discovery and estimation of genetic effects. The first three objectives use experimental populations to provide genotypic and phenotypic data for traits known to affect life-cycle efficiency and for matching genetic resources with specific marketing and production situations. Large-scale beef cattle and sheep experiments using both quantitative and molecular approaches are planned to provide genotypic and phenotypic data for estimation of genetic effects on fundamental traits. Cattle research will emphasize multi-breed genetic evaluation, estimation of genetic parameters within breed, and structuring of populations to facilitate genomic research leading to development of DNA tests for economically important traits. A population of cattle is being developed for QTL identification that has recent ties to industry genetics, several half-sib families large enough to contribute to identifying QTL through linkage, and many smaller families and several potential origins of QTL allowing fine mapping, association analyses, and marker validation. Potential interactions of temperate and tropically-adapted cattle breeds with temperate and subtropical environments will be investigated through evaluation of F1 cows consistent with commercial production systems in the subtropical environment of Louisiana and the temperate environment of Nebraska. Sheep experimentation will focus on breed evaluation, leading to creation and development of an easy-care maternal line of hair sheep. The animal experiments will be complemented by research to develop and apply statistical technologies required for discovery, estimation, and use of genetic effects, including incorporation of genetic markers into multibreed genetic evaluations for beef cattle. The fourth objective addresses designs of experimental populations for estimation of genetic effects. Various mating plans will be simulated and evaluated for their power to detect QTL effects of various sizes, power of detecting breed-specific heterosis, and for the standard errors of other genetic effects. The final objective focuses on the development and application of statistical theory required for analysis of data and exploitation of genetic effects by livestock industries. Whole genome selection will be investigated as a method to reduce bias and improve accuracy of genetic prediction.
3. Progress Report
Markers from the Illumina BovineSNP50 Beadchip were associated with feed intake, feed efficiency and carcass traits in crossbred steers formed through crosses of 2-breed crossbred sires and dams sired by the 7 beef breeds with the most registrations. Genotypes for 770,000 genomic markers have been obtained for over 300 sires, dams, and grandsires of this population and individual animal sequencing has been initiated on 96 sires and grandsires. This increased density of genomic information should make the associations discovered more applicable across breeds. Nearly 1,400 terminal steers and heifers produced from 2-breed crossbred sires of the same 7 breeds as well as Brahman were measured for disease resistance phenotypes and genotyped for 50,000 genomic markers. Additional animals in this population continue to be phenotyped for vaccination response, treatment and diagnostic records, lung lesions at slaughter, and blood counts to build a disease resistance resource. About 180 highly influential bulls were newly sampled from the beef industry to produce progeny in the Germplasm Evaluation Project. The South Devon and Tarentaise breeds were added for the first time since the 1970s. Cows were mated to sires sampled from the 18 largest beef breed associations with genetic evaluations using artificial insemination: Angus, Hereford, Simmental, Charolais, Limousin, Red Angus, Gelbvieh, Shorthorn, Brangus, Beefmaster, Maine-Anjou, Brahman, Chiangus, Santa Gertrudis, Salers, and Braunvieh, South Devon and Tarentaise. Since its beginning, the project has produced 2,000 2-breed cross calves and 800 backcross calves. The project also produced 96 0.875-blood calves representing an important milestone toward the objective of grading up to purebreds of each breed in the project. Steer and heifer progeny from artificial insemination mating to these sire breeds were measured for feed intake. Carcass data and beef tenderness were collected on the steers. Heifers were retained for reproductive performance assessment and to continue producing calves that will contribute to estimation of breed differences, heterosis, and genomic marker effects. Pooled DNA samples from animals with extreme phenotypes are being used to detect marker associations for reproductive traits and disease resistance traits (lung lesions, pneumonia treatment records, and bloat treatment records). These procedures, already applied in human case control studies, have the potential to improve marker association testing on large phenotypic databases with minimal costs. An experiment was completed to compare productivity of Rambouillet x Romanov reciprocal crossbred ewes through four years of age when mated to two terminal sire breeds. We continued to increase flocks of Katahdin and Polypay sheep as industry standards for easy-care maternal breeds of prolific hair and wool sheep, respectively. Over 1,950 lambs of an easy-care maternal line of prolific hair sheep (0.5 Romanov, 0.25 White Dorper, 0.25 Katahdin) were produced. Rams in this line were genotyped and selected to increase resistance to scrapie and ovine progressive pneumonia.
1. Predicting breed composition of crossbred beef cattle. The breed composition of crossbred beef cattle is often unknown, yet such knowledge would be useful to aid management decisions. ARS scientists at Clay Center, Nebraska accurately estimated breed composition of crossbred cattle using BovineSNP50 genotype markers and allele frequencies estimated from a sample of bulls of 16 breeds. The use of genetic markers could accurately determine if a specific breed contributed 0, 25, 50, or 75% to the genetic makeup of an individual animal. Determination of breed composition is important for verification of product brand and source. This methodology is being applied by the Animal and Plant Inspection Service in disease trace back cases.
2. Genomic prediction of economically important traits in beef cattle. Traditional methods of improving beef cattle by selection, based on measuring performance, have limitations that might be eased by use of DNA markers. Equations for deriving molecular breeding values, a prediction of genetic merit for growth and carcass traits based on an animal’s DNA, were developed by ARS scientists at Clay Center, Nebraska using over 4,000 crossbred animals and over 50,000 DNA markers. These equations were assessed for accuracy, found to be 20 to 40% accurate and have been released to the industry via the U.S. Meat Animal Research Center (USMARC) website. Further increases in accuracy will require more traditional and molecular genetics research. Molecular breeding values for the bulls in the 2,000 bull project were sent to respective breed associations.
3. Testing the effectiveness of selection using DNA technology. To demonstrate the efficacy of utilizing genomic tools in selection programs in beef cattle, ARS scientists at Clay Center, Nebraska cooperated with cattle breeders in a collaboration titled the “Weight Trait Project.” The purpose of this collaboration was to determine whether a genomic marker panel derived for weight traits, which all of the participating producers collect, could accurately predict progeny performance. Predictions derived from over 2,000 influential bulls of 16 prominent beef cattle breeds, resulted in accuracies ranging from 33 to 54% depending on the trait (11 to 29% of the genetic variance).
4. Increasing profitability for sheep producers. The use of Romanov crossbred ewes is increasing in the United States because the Romanov breed is the most prolific breed available. Romanov crossbred sheep may differ in performance when produced using Romanov rams or Romanov ewes because Romanov ewes produce much larger litters than ewes of other breeds. Therefore, the relative performance of Romanov crossbred ewes sired by Romanov rams compared to those born to Romanov ewes is an important industry issue. ARS researchers at Clay Center, Nebraska determined that Romanov crossbred ewes produced by either method were similar in their high levels of productivity. Consequently, producers can mate Romanov rams to ewes of locally-adapted breeds to lower the cost of producing Romanov crossbreds. This practical information will further increase use of Romanov superior genetics, resulting in greater profitability for sheep producers.
Kuehn, L.A., Keele, J.W., Bennett, G.L., Mcdaneld, T.G., Smith, T.P., Snelling, W.M., Sonstegard, T.S., Thallman, R.M. 2011. Predicting breed composition using breed frequencies of 50,000 markers from the U.S. Meat Animal Research Center 2,000 bull project. Journal of Animal Science. 89:1742-1750.