Genotype by environment interactions for growth in Red Angus

Citation: Fennewald, D. J., Weaber, R. L., & Lamberson, W. R. (2017). Genotype by environment interactions for growth in Red Angus. Journal of Animal Science, 95(2), 538-544. doi:10.2527/jas2016.0846Accuracy of sire selection is limited by how well animals are characterized for their environment. The objective of this study was to evaluate the presence of genotype x environment interactions (GxE) for birth weight (BiW) and weaning weight (WW) for Red Angus in the United States. Adjusted weights were provided by the Red Angus Association of America. Environments were defined as 9 regions within the continental United States with similar temperature-humidity indices. Mean weights of calves were determined for each region and for each sire's progeny within each region. A reaction norm (RN) for each bull was estimated by regressing the sire means on the region means weighted for the number of progeny of each sire. The range for BiW and WW RN was -1.3 to 4.0 and -1.7 to 2.8, respectively. The heritabilities of BiW and WW RN were 0.40 and 0.39, respectively. Phenotypic and genetic correlations between BiW and WW RN were 0.19 and 0.54, respectively. The phenotypic correlation of the progeny mean to the RN was -0.20 (P < 0.05) and suggests that sires with higher means are more stable in progeny performance across environments. Weights in different regions were considered separate traits and genetic correlations were estimated between all pairs of regions as another method to determine GxE. Genetic correlations < 0.80 indicate GxE at a level for concern, but existed for only 2 of 36 estimates for BiW and 12 of 36 estimates for WW. Genetic correlations between different regions ranged from 0.74 to 0.96 for BiW and 0.62 to 0.99 for WW and indicate that sires tend to rank similarly across environments for these traits

Novel analysis of global DNA methylation in the limbic system of the bovine brain

Citation: Cantrell, B. A., McKay, S. D., Weaber, R. L., Funston, R. N., & Lachance, H. (2016). Novel analysis of global DNA methylation in the limbic system of the bovine brain. Journal of Animal Science, 94, 43-43. doi:10.2134/jas2016.94supplement443xThere has been limited research focusing on the genetic-environmental interactions in bovine brains. Global DNA methylation has been measured in brains of several species, but has yet to be examined in bovine. The objective of this study was to characterize global DNA methylation in 9 regions of the limbic system in the bovine brain: amygdala, bed nucleus of the stria terminalis, cingulate gyrus, dorsal raphe, hippocampus, hypothalamus, nucleus accumbens, periaqueductal gray, and prefrontal cortex. DNA was extracted from brain and blood samples of 6 Red Angus × Simmental steers (less than 20 mo of age), using the DNA Extraction Kit from Agilent Technologies (Santa Clara, CA) and a phenol chloroform extraction. Percent of global DNA methylation was determined using the MethylFlash Methylated DNA Quantification Kit (Colormetric) from Epigentek (Farmingdale, NY). Varying amounts of global DNA methylation were observed among the 9 functionally distinct regions of the bovine limbic system. Amygdala, bed nucleus of the stria terminalis, cingulate gyrus, dorsal raphe, periaqueductal gray, prefrontal cortex, and nucleus accumbens are all significantly different (P < 0.05) from 1 or more brain tissue type, using a paired t test in SPSS (IBM, Armonk, NY). Conversely, global DNA methylation of blood was not significantly different (P < 0.05) from any brain tissue type. This study shows significant differences in global DNA methylation among different tissue types in the limbic system of the bovine brain. Understanding the differences in global DNA methylation within different tissues in the brain will facilitate future research involving the effects of differential methylation with regard to economically important traits

Food defense : protecting the food supply from intentional harm (2009)

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Phenotypic relationships between docility and reproduction in Angus heifers

Citation: White, K. L., Bormann, J. M., Olson, K. C., Jaeger, J. R., Johnson, S., Downey, B., . . . Weaber, R. L. (2016). Phenotypic relationships between docility and reproduction in Angus heifers. Journal of Animal Science, 94(2), 483-489. doi:10.2527/jas2015-9327The objective of this study was to elucidate the phenotypic relationships between docility and first-service AI conception rate in heifers. Data (n = 337) collected from 3 cooperator herds in Kansas at the start of synchronization protocol included exit velocity (EV), chute score (CS), fecal cortisol (FC), and blood serum cortisol (BC). Data were analyzed using logistic regression with 30-d pregnancy rate as the dependent variable. The model included the fixed effect of contemporary group and the covariates FC, BC, EV, CS, BW, and age. Correlation coefficients were calculated between all continuous traits. Pregnancy rate ranged from 34% to 60% between herds. Blood cortisol positively correlated with EV (r = 0.22, P < 0.01), negatively correlated with age (r = -0.12, P < 0.03), and tended to be negatively correlated with BW (r = -0.10, P = 0.09). Exit velocity was positively correlated with CS (r = 0.24, P < 0.01) and negatively correlated with BW (r = -0.15, P < 0.01) and age (r = -0.12, P < 0.03). Chute score negatively correlated with age (r = -0.14, P < 0.01), and age and BW were moderately positively correlated (r = 0.42, P < 0.01), as expected. Older, heavier animals generally had better temperament, as indicated by lower BC, EV, and CS. The power of our test could detect no significant predictors of 30-d pregnancy for the combined data from all ranches. When the data were divided by ranch, CS (P < 0.03) and BW (P < 0.01) were both significant predictors for 30-d pregnancy for ranch 1. The odds ratio estimate for CS has an inverse relationship with pregnancy, meaning that a 1-unit increase in average CS will reduce the probability of pregnancy at ranch 1 by 48.1%. Weight also has a negative impact on pregnancy because a 1-kg increase in BW will decrease the probability of pregnancy by 2.2%. Fertility is a complex trait that depends on many factors; our data suggest that docility is 1 factor that warrants further investigation

Genetic relationships among temperament, immune function, and carcass merit

Cattle producers historically have selected for docile temperaments simply for management convenience because calmer animals are conducive to safe environments for their peers as well as their handlers. As many producers would acknowledge, there seems to be a relationship between temperament and health, and calmer cattle tend to frequent the working chute for treatment of disease less often. Positive correlations have been found in cattle between temperament traits (chute scores, pen scores, and chute exit velocities) and cortisol concentration in the blood, suggesting that more excitable cattle are easily stressed (Curley et al., 2006; Cooke et al., 2009). In addition, Curley et al. (2007) found that easily excitable animals sustain elevated cortisol concentrations for a longer duration and had greater pituitary and adrenal responses following a stressor than calm cattle. Temperamental cattle have significantly higher mean temperament responses at all points (Oliphint, 2006). Higher basal serum cortisol concentrations may suggest that easily excitable cattle are chronically stressed (Curley et al., 2007), possibly resulting in a compromised immune system, illness, and decreased fat and protein deposition. Common measures of cattle temperament are pen scores, chute scores, and exit velocities. Temperament appears to be moderately heritable, with estimates ranging from 0.15 to 0.44 (Burrow and Corbet, 2000; Kadel et al., 2006; Schrode and Hammack, 1971; Stricklin et al., 1980; Fordyce et al., 1988). If genetic correlations are found between temperament and production traits or immunological factors, they may aid cattle breeders in producing profitable cattle. Such relationships have been found between exit velocity and hot carcass weight (r = -0.54), exit velocity and marbling score (r = 0.10), exit velocity and yield grade (r = -0.22) (Nkrumah et al., 2007), and post-weaning weight gain and exit velocity (Weaber et al., 2006). Bovine respiratory disease (BRD) susceptibility has been estimated to be lowly heritable (Muggli-Cockett et al., 1992; Snowder et al., 2005, 2006, 2007; Schneider et al., 2008). This study was conducted to further investigate the genetic relationships between cattle temperament measured by chute score and exit velocity, immunological factors, and a range of economically relevant performance traits

Genetic parameters estimated at receiving for circulating cortisol, immunoglobulin G, interleukin 8, and incidence of bovine respiratory disease in feedlot beef steers

Citation: Cockrum, R. R., Speidel, S. E., Salak-Johnson, J. L., Chase, C. C. L., Peel, R. K., Weaber, R. L., . . . Enns, R. M. (2016). Genetic parameters estimated at receiving for circulating cortisol, immunoglobulin G, interleukin 8, and incidence of bovine respiratory disease in feedlot beef steers. Journal of Animal Science, 94(7), 2770-2778. doi:10.2527/jas2015-0222Bovine respiratory disease complex (i.e., shipping fever and bacterial bronchopneumonia) is a multifaceted respiratory illness influenced by numerous environmental factors and microorganisms. Bovine respiratory disease (BRD) is just one component of BRD complex. Because BRD is moderately heritable, it may be possible to reduce the incidence of BRD through genetic selection. The objectives of this study were to determine the heritability and associative genetic relationships among immune system traits (i.e., cortisol, total IgG, IgG isotypes, and IL-8) in cattle monitored for BRD incidence. At an average of 83 d after weaning (219 d age and mean = 221.7 kg [SD 4.34]), crossbred Bos taurus steer calves (n = 2,869) were received at a commercial feedlot in southeastern Colorado over a 2-yr period. At receiving, jugular blood samples were collected at 212 (yr 1) and 226 d (yr 2) of age for immune trait analyses. The BRD phenotype was defined as a binomial variable (0 = no and 1 = yes) and compared with immune system traits measured at receiving (prior to illness onset). An animal identified as BRD positive exhibited ? 2 clinical signs (i.e., eye or nasal discharge, cough, lethargy, rapid breathing, acute interstitial pneumonia, or acute upper respiratory syndrome and/or a rectal temperature &gt; 39.7°C). Heritability and genetic correlation estimates for categorical variable BRD, cortisol, IgG, IgG1, IgG2, and IL-8 were estimated from a sire model using ASREML. Heritability estimates were low to moderate for BRD (0.17 ± 0.08), cortisol (0.13 ± 0.05), IgG (0.15 ± 0.05), IgG1 (0.11 ± 0.05), IgG2 (0.24 ± 0.06), and IL-8 (0.30 ± 0.06). A moderate negative genetic correlation was determined between BRD and cortisol (rg = ?0.19 ± 0.32). Moderate positive correlations were found between BRD with IgG (0.42 ± 0.28), IgG1 (0.36 ± 0.32), and IL-8 (rg = 0.26 ± 0.26). Variation in the BRD phenotype and immune system traits suggested herd health improvement may be achieved through genetic selection. © 2016 American Society of Animal Science. All rights reserved

National Program for Genetic Improvement of Feed Efficiency in Beef Cattle

Our goal is to sustainably reduce feed resources required to produce beef via the rapid development and deployment of novel nutritional, genomic and genetic improvement technologies. We will strengthen the international competitiveness of US agriculture and enable increased food production by increasing the animal protein produced without additional feed inputs and with a reduced greenhouse gas footprint

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.Results: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n is about 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesC[pi]) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.Conclusions: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.Peer reviewedAnimal Scienc

Environmental effects on water intake and water intake prediction in growing beef cattle

Water is an essential nutrient, but there are few recent studies that evaluate how much water individual beef cattle consume and how environmental factors affect an individual’s water intake (WI). Most studies have focused on WI of whole pens rather than WI of individual animals. Thus, the objective of this study was to evaluate the impact of environmental parameters on individual-animal WI across different seasons and develop prediction equations to estimate WI, including within different environments and management protocols. Individual daily feed intake and WI records were collected on 579 crossbred steers for a 70-d period following a 21-d acclimation period for feed and water bunk training. Steers were fed in 5 separate groups over a 3-yr period from May 2014 to March 2017. Individual weights were collected every 14 d and weather data were retrieved from the Oklahoma Mesonet’s Stillwater station. Differences in WI as a percent of body weight (WI%) were analyzed accounting for average temperature (TAVG), relative humidity (HAVG), solar radiation (SRAD), and wind speed (WSPD). Seasonal (summer vs. winter) and management differences (ad libitum vs. slick bunk) were examined. Regression analysis was utilized to generate 5 WI prediction equations (overall, summer, winter, slick, and ad libitum). There were significant (P \u3c 0.05) differences in WI between all groups when no environmental parameters were included in the model. Although performance was more similar after accounting for all differences in weather variables, significant (P \u3c 0.05) seasonal and feed management differences were still observed for WI%, but were less than 0.75% of steer body weight. The best linear predictors of daily WI (DWI) were dry mater intake (DMI), metabolic body weights (MWTS), TAVG, SRAD, HAVG, and WSPD. Slight differences in the coefficient of determinations for the various models were observed for the summer (0.34), winter (0.39), ad libitum (0.385), slick bunk (0.41), and overall models (0.40). Based on the moderate R2 values for the WI prediction equations, individual DWI can be predicted with reasonable accuracy based on the environmental conditions that are present, MWTS, and DMI consumed, but substantial variation exists in individual animal WI that is not accounted for by these models