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United States Department of Agriculture

Agricultural Research Service

2009 Annual Report

1a.Objectives (from AD-416)
Objective 1: Develop methods and strategies for measuring feed intake and related phenotypes of steers, replacement heifers, and mature cows.

Objective 2: Determine breed and within-breed genetic effects on feed efficiency, growth, and fertility of cattle.

Sub-objective 2.A. Determine breed and within-breed genetic effects on nutrient utilization.

Sub-objective 2.B. Determine breed and within-breed genetic effects on reproductive efficiency.

Objective 3: Discover QTL and estimate genomic effects for traits contributing to differences in efficiency among cattle.

Objective 4: Fine map identified QTL for reproductive rate in cattle.

Objective 5: Enhance existing simulation models to investigate genetic-by-environmental interactions on beef life-cycle efficiency and integrate into decision support software.

Objective 6: Identify nutritional effects on expression of genes and subsequent phenotypes, and integrate this information with our current understanding of physiology to enhance management decisions.

1b.Approach (from AD-416)
Major challenges of the beef cattle industry are to improve efficiency and reduce negative environmental impacts of animal production. Provision of nutrients (feed) constitutes about 65 to 75% of the cost of beef cattle production. Less than 20% of the nutrients consumed are converted to useful products. The incomplete and inefficient utilization of nutrients has an adverse effect on efficiency of production and a negative effect on the environment. Traditional approaches have resulted in successful alteration of production traits such as weight at slaughter, growth rate, mature weight, and body composition, but have not altered feed efficiency. Those approaches do not provide the ability to economically identify animals with high genetic merit for feed efficiency on a timely basis, because the required phenotypic data are impractical to obtain in normal genetic evaluation programs. Available evidence suggests feed consumption and related traits are likely to be moderately heritable. These traits are extremely important components in any strategy for the permanent, cumulative, and sustainable genetic improvement of biological and economic efficiencies of beef production. Application of quantitative trait loci (QTL) technology provides opportunities to improve feed efficiency in beef production. The identification of QTL would make it possible to utilize the relatively large amount of observed variation and moderate heritability in improving feed efficiency. However, currently there are no tools (EPD, QTL, or markers for QTL) that facilitate direct selection to modify feed consumption, feed efficiency, or nutrient requirements in the growing-finishing animal or productive female.

Research in this project is being undertaken to study genetic and environmental factors that lead to variation in efficiency in beef production. This project addresses measures of efficiency at different phases of the production system to identify those factors that have additive merit and antagonistic relationships across the different phases of production. The initial component of the project is to develop facilities and methodologies to efficiently collect economically and biologically important phenotypic data relevant to efficiency. After developing capabilities to measure the phenotypes, the contribution of genetics and environment/management to variation in efficiency of production will be determined. Genetic variation will be evaluated using both quantitative genetics and QTL discovery. Information gained from both the genetic and environmental studies will be used to parameterize simulation models that provide decision support software to allow producers to simulate potential outcomes to optimize production efficiency when different combinations of animal genetics and management strategies are used.

3.Progress Report
Phenotypic data for feed intake and weight stasis were collected on mature cows (n = ~250), and genomic scans were conducted using the Illumina BovineSNP50 BeadChip. Phenotypic measures of milk production, mammary gland soundness, and feet and leg structural quality were collected on two-year-old cows (n = ~250). Reproductive success and calf performance were determined. Analyses were performed in steers (~1,250) to identify SNP associated with feed intake, growth, and behavior. Using published data on contributions of biological mechanisms to variation in residual feed intake, residual feed intake estimates of 1,212 steers were partitioned into 3 component traits: a) digestibility, 12%, b) efficiency of protein accretion, 39%, and c) maintenance, 49%. Using the Decision Evaluator for the Cattle Industry (DECI), maintenance was subdivided into a weight maintenance component and a production maintenance component. Methodology was developed and computer programs were written and integrated into the DECI model to estimate phenotypes of 1,212 steers for digestibility, efficiency of protein accretion, weight maintenance and production maintenance. Ovarian ultrasonography was conducted on 600 heifers to evaluate antral follicle count, and 100 of these heifers were also given a full reproductive tract score evaluation. An additional 200 cows were phenotyped to understand how follicle numbers change as cows age. Heifers have been phenotyped for antral follicle count, and they have had 50K SNP genomic scans. In total, we have phenotyped ~1,000 heifers and 600 cows. Ovarian follicles, corpora lutea, ova, and embryos were collected, processed, and evaluated for Low- and-High-fertility cows. Ovarian follicular and corpus luteum measurements and estrogen and progesterone concentrations were determined on 120 pubertal heifers fed to achieve 53% (Low) versus 65% (High) of their mature body weight at breeding. Nutritional treatments were imposed on 184 heifers to determine the effects of peripuberal nutrition on subsequent feed and production efficiency. Reproductive data were collected on 144 heifers that had received nutritional treatments in the previous year. Nutritional treatments were applied to ~200 cows to determine the effect of uterine nutrient environment on the subsequent production efficiency of daughters and the carcass quality on sons. Growth, puberty, and pregnancy data were collected on ~100 heifers that were the result of the previous year’s uterine nutrient environment study.

1. Simulation models more accurately predict feed efficiency than simple regression models. Relative phenotypic ranking of steers for feed efficiency varies with the model used to estimate predicted values. The inconsistency in ranking may result in falsely identifying an animal as being efficient. Estimates of residual feed intake for 1,212 steers were obtained using predictions of expected feed intake obtained with three computer models (Decision Evaluator for the Cattle Industry, Cornell Value Discovery System, and the National Research Council beef cattle model 2000 update), and a linear statistical model. Some slow growing animals that had very low feed intakes were identified as efficient with the linear model. However, these animals were identified as inefficient with the DECI model suggesting that estimates of residual feed intake obtained with the DECI model would contain less noise compared with the other models. Estimating feed efficiency with DECI can improve the accuracy of selecting efficient individuals for subsequent breeding programs.

2. Antral follicle count in heifers is associated with a decreased reproductive rate. Reproductive failure in heifers increases the number of heifers that must be developed each year as replacements. The increased number of heifers developed each year increases production cost. Yearling heifers with fewer antral follicle counts have decreased heifer pregnancy rates and a trend toward more immature reproductive tracts, as evidenced by the reproductive tract scores. Identifying heifers with greater antral follicle counts offers a strategy to decrease selection of low fertility heifers resulting in a decrease in the number of heifers that are needed each year.

3. Size of the bovine ovarian ovulatory follicle influences fertility and corpus luteum formation. Beef cattle conception to a single breeding is less than 75%. Major causes of poor fertility are failure to conceive and embryonic mortality. The size of the ovulatory follicle is related to the probability that a cow will successfully have a calf. At the time that cows are bred, the ovulatory follicle has a diameter range from 12 to 30 mm. Fertility was greatest for cows with ovulatory follicles ranging from 14 to 18 mm in diameter; and cows with follicles greater than 21 mm, did not conceive. Progesterone is required to maintain pregnancy, and during breeding and early pregnancy, progesterone is produced by the corpus luteum. Corpora lutea originate from ovulatory follicles, and typically progesterone concentrations increase with increased corpus luteum size; however, the quality of the corpora lutea may decrease as cows age. While the size of both follicles and corpus luteum are smaller in young females that have not had a calf compared to older cows, their progesterone concentrations are greater. Screening cows for ovulatory follicle size is a potential tool to allow producers to evaluate the fertility of individual cows.

6.Technology Transfer

Number of Other Technology Transfer3

Review Publications
Calegare, L., Alencar, M.M., Packer, I.U., Ferrell, C.L., Lanna, D.P. 2009. Cow/calf preweaning efficiency of Nellore and Bos taurus x Bos indicus crosses. Journal of Animal Science. 87(2):740-747.

Calegare, L., Alencar, M.M., Packer, I.U., Leme, P.R., Ferrell, C.L., Lanna, D.P. 2009. Preweaning Performance and Body Composition of Calves from Straightbred Nellore and Bos taurus x Nellore Crosses. Journal of Animal Science. 87(5):1814-1820.

Cushman, R.A., Allan, M.F., Kuehn, L.A. 2009. Achievements of Research in Reproduction Sciences. In: Rosati, A., Tewolde, A., Mosconi, C., editors. Animal Production and Animal Science Worldwide - WAAP Book of the Year 2007. The Netherlands: Wageningen Academic Publishers. p. 59-65.

Allan, M.F., Kuehn, L.A., Cushman, R.A., Snelling, W.M., Echternkamp, S.E., Thallman, R.M. 2009. Confirmation of quantitative trait loci using a low-density single nucleotide polymorphism map for twinning and ovulation rate on bovine chromosome 5. Journal of Animal Science. 87(1):46-56.

Puchala, R., Tovar-Luna, I., Sahlu, T., Freetly, H.C., Goetsch, A. 2009. Technical Note: The Relationship between Heart Rate and Energy Expenditure in Growing Crossbred Boer and Spanish Wethers. Journal of Animal Science. 87(5):1714-1721.

Cushman, R.A., Allan, M.F., Kuehn, L.A., Snelling, W.M., Cupp, A.S., Freetly, H.C. 2009. Evaluation of Antral Follicle Count and Ovarian Morphology in Crossbred Beef Cows: Investigation of Influence of Stage of the Estrous Cycle, Age, and Birth Weight. Journal of Animal Science. 87(6):1971-1980.

Matukumalli, L.K., Lawley, C.T., Schnabel, R.D., Taylor, J.F., Allan, M.F., Heaton, M.P., O'Connell, J., Moore, S.S., Smith, T.P., Sonstegard, T.S., Van Tassell, C.P. 2009. Development and Characterization of a High Density SNP Genotyping Assay for Cattle. PLoS One. 4(4):e5350. Available:

Ngwa, A.T., Dawson, L.J., Puchala, R., Detweiler, G., Merkel, R.C., Wang, Z., Tesfai, K., Sahlu, T., Ferrell, C.L., Goetsch, A.L. 2009. Effects of Stage of Lactation and Dietary Forage Level on Body Composition of Alpine Dairy Goats. Journal of Dairy Science. 92(7):3374-3385.

Cushman, R.A., Allan, M.F., Kuehn, L.A. 2008. Characterization of biological types of cattle: Indicator traits of fertility in beef cows. Brazilian Journal of Animal Science. 37(Special Supplement):116-121.

Last Modified: 4/17/2014
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