Connecting Heat Tolerance and Tenderness in Bos indicus Influenced Cattle

Bos indicus cattle are widely utilized in tropical and subtropical climates. Their heat tolerance and parasite resistance are integral for beef production in these regions; however, a reputation for excitable temperaments, slower growth, and variation in tenderness has limited their use in commercial beef production. This suggests that there is antagonism between heat tolerance and meat production traits. Meat quality characteristics are determined by the properties of skeletal muscle as well as conditions during slaughter and processing. Thus, it is possible that adaptations related to heat tolerance in the living animal affect tenderness and other meat quality attributes. Since muscle represents a large proportion of body mass, relatively small changes at the cellular level could impact overall heat production of the animal. Specifically, protein degradation and mitochondria function are aspects of organ and cellular metabolism that may help limit heat production and also have a connection to tenderness. Protein degradation postmortem is critical to structural changes that enhance tenderness whereas mitochondria may influence tenderness through their roles in energy metabolism, calcium regulation, cell death signaling, and oxidative stress. This review explores potential relationships between cellular metabolism in vivo and beef quality development in Bos indicus and Bos indicus influenced cattle.

The effect of Brahman genes on body temperature plasticity of heifers on pasture under heat stress

Bos taurus indicus cattle have the superior ability for the regulation of body temperature during heat stress due to a number of physiological and cellular level adaptive traits. The objectives of this study were to quantify the change in body temperature in heifers with various proportions of Brahman genes per unit increase in heat stress as measured by temperature-humidity index (THI) and to assess how different breed groups responded to varying intensity and duration of heat stress. A total of 299 two-yr-old heifers from six breed groups ranging from 100% Angus to 100% Brahman were evaluated under hot and humid conditions during 2017 and 2018 summer days. Two strategies were used to estimate the plasticity in body temperature of breed groups in response to environmental challenges: 1) a random regression mixed model was used to estimate reaction norm parameters for each breed group in response to a specified environmental heat stress and 2) a repeated measures mixed model was used to evaluate the response to different environmental heat loads. The reaction norm model estimated an intercept and slope measuring the change in body temperature per unit increase in THI environmental heat stress for different breed groups of animals and allowed the identification of genotypes which are robust, with low slope values indicative of animals that are able to maintain normal body temperature across a range of environments. The repeated measures mixed model showed that Brahman cattle have an advantage under moderate or high heat stress conditions but both Angus and Brahman breed groups are greatly affected when heat stress is severe. A critical factor appears to be the opportunity to cool down during the night hours more than the number of hours with extreme THI. With heat stress conditions predicted to intensify and expand into currently temperate zones, developing effective strategies to ensure sustainable beef production systems are imperative. Effective strategies will require the identification of the genes conferring the superior thermotolerance in Brahman cattle.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle

BACKGROUND

Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions.

RESULTS

The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15.

CONCLUSIONS

Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Thermoregulatory response of Brangus heifers to naturally occurring heat exposure on pasture

Heat stress is a cause of major economic losses to cattle producers, especially in tropical and subtropical environments. The objectives of this study were to assess the phenotypic variability in core body temperature and sweating rate and to evaluate the effect of coat type, temperament, and BW on core body temperature and sweating rate in Brangus heifers. During August and September of 2016, 725 Brangus heifers were evaluated on pasture in four separate groups (n = 200, 189, 197, and 139). Environmental measurements of dry bulb temperature (Tdb) and relative humidity (RH) were measured every 15 min during the entire time of data collection and the temperature-humidity index (THI) was used to quantify heat-stress potential. Coat score, sweating rate, chute score, exit score, and live weight were recorded as the animals passed through the chute. Vaginal temperature was recorded every 5 min for five consecutive days. There was significant variation in vaginal temperature between heifers in the same environmental conditions (σ2u = 0.049), suggesting opportunities for selective improvements. A repeatability of 0.47 and 0.44 was estimated for sweating rate and vaginal temperature, respectively, suggesting that one measurement would be able to adequately describe the sweating capacity or ability to control the body temperature of an individual. Vaginal temperature increased as THI increased, with approximately 1 h lag time in the animal's response. Vaginal temperature (-0.047 °C, P = 0.015) and sweating rate were lower (-5.49 ± 2.12 g/(m2·h), P < 0.01) for heifers that demonstrated a calmer behavior in the chute. Animals with shorter, smoother hair coats had significantly lower vaginal temperatures when compared to animals with longer hair coats (P < 0.01). Also, heavier heifers in this study maintained lower (P < 0.0001) vaginal temperature than the lighter heifers. Our results showed that hair coat, temperament, and weight influenced vaginal temperature regulation.

Determination of the optimum contribution of Brahman genetics in an Angus-Brahman multibreed herd for regulation of body temperature during hot weather

The objective was to evaluate the influence of varying amounts of Brahman genetics on body temperature under pasture conditions during hot weather. Vaginal temperatures were measured at 5-min intervals for 3 to 5 d on four occasions during August and September from a total of 190 pregnant cows that were either Angus, 2/8 Brahman (remainder Angus), Brangus (3/8 Brahman), 4/8 Brahman, 6/8 Brahman or Brahman. Vaginal temperature was higher for the first two replicates than for the second two replicates. In the first two replicates, average vaginal temperature did not differ between genetic groups, but average vaginal temperature from 1500 to 1900 h was lower for Brahman than other groups. In the second two replicates, average vaginal temperature was lower for cows that were 4/8 or higher Brahman than for cows that were 2/8 Brahman or Angus. Average vaginal temperature from 1500 to 1900 h was lower for cows that were 4/8 or higher Brahman than for cows that were 2/8 Brahman or Angus. In addition, Brahman cows had lower vaginal temperatures than cows that were 4/8 Brahman or 3/8 Brahman (i.e., Brangus). In one replicate, a tracking device was used to map cow location. At 1200 to 1300 h, cows that were 6/8 Brahman or Brahman had fewer observations near the tree line (i.e., in shade) than cows that were 4/8 Brahman or less. At 1500 to 1600 h, cows that were 4/8 or higher Brahman experienced fewer observations near the tree line than cows that contained a lower fraction of Brahman genetics. In summary, a minimum of 4/8 Brahman genetics was required to increase the ability to regulate body temperature and at least 6/8 Brahman when heat stress was severe. It is likely, therefore, that using Brahman genetics to optimize adaptation to thermal stress under conditions of severe heat stress requires a preponderance of Brahman genes.

Modeling correlated marker effects in genome-wide prediction via Gaussian concentration graph models

In genome-wide prediction, independence of marker allele substitution effects is typically assumed; however, since early stages in the evolution of this technology it has been known that nature points to correlated effects. In statistics, graphical models have been identified as a useful and powerful tool for covariance estimation in high dimensional problems and it is an area that has recently experienced a great expansion. In particular, Gaussian concentration graph models (GCGM) have been widely studied. These are models in which the distribution of a set of random variables, the marker effects in this case, is assumed to be Markov with respect to an undirected graph G. In this paper, Bayesian (Bayes G and Bayes G-D) and frequentist (GML-BLUP) methods adapting the theory of GCGM to genome-wide prediction were developed. Different approaches to define the graph G based on domain-specific knowledge were proposed, and two propositions and a corollary establishing conditions to find decomposable graphs were proven. These methods were implemented in small simulated and real datasets. In our simulations, scenarios where correlations among allelic substitution effects were expected to arise due to various causes were considered, and graphs were defined on the basis of physical marker positions. Results showed improvements in correlation between phenotypes and predicted additive genetic values and accuracies of predicted additive genetic values when accounting for partially correlated allele substitution effects. Extensions to the multiallelic loci case were described and some possible refinements incorporating more flexible priors in the Bayesian setting were discussed. Our models are promising because they allow incorporation of biological information in the prediction process, and because they are more flexible and general than other models accounting for correlated marker effects that have been proposed previously.

Heritabilities and genetic correlations of pulmonary arterial pressure and performance traits in Angus cattle at high altitude

Pulmonary arterial pressure (PAP) is an indicator trait for pulmonary hypertension and for the risk of developing high-altitude disease (HAD) in cattle. Pulmonary arterial pressures provide a tool for selection of breeding cattle for tolerance to high altitude in mountainous regions of the United States. The objective of this study was to evaluate relationships between growth performance traits and yearling PAP (42.4 ± 9.9 mmHg; = 5,776; elevation 2,150 m) using data from 1993 to 2014 in the John E. Rouse Colorado State University Beef Improvement Center (CSU-BIC) Angus herd. The breeding program used sires ( = 299) from both low- and high-elevation environments. We hypothesized that little to no genetic relationship exists between PAP and birth weight (BWT; direct and maternal), weaning weight (WW; direct and maternal), yearling weight (YW; direct and maternal), and postweaning gain (PWG). Historic selection of natural service sires from within the herd required a PAP of ≤ 42 mmHg. Outside AI sires ( = 156) used in this breeding program were not PAP tested and therefore were used with little knowledge of these sires' high-altitude adaptability. Performance traits (± SD) routinely recorded included BWT (36.2 ± 5.1 kg; = 8,695), WW (213.5 ± 31.8 kg; = 8,010), YW (345.6 ± 83.8 kg; = 5,580), and PWG (122.0 ± 63.7 kg; = 5,449), where PWG represented the total weight gained from weaning to yearling age. Four-trait analyses using REML were conducted with an animal model. The heritability estimates (± SE) for PAP (0.26 ± 0.03), BWT direct (0.42 ± 0.04) and maternal (0.14 ± 0.02), WW direct (0.29 ± 0.04) and maternal (0.19 ± 0.03), YW direct (0.45 ± 0.04) and maternal (0.23 ± 0.03), and PWG (0.14 ± 0.02) were in the range of those reported in previous literature. Estimates of genetic correlations (± SE) revealed weak relationships between PAP and direct and maternal BWT, direct and maternal WW, direct and maternal YW, and PWG of 0.15 ± 0.09, 0.14 ± 0.10, 0.23 ± 0.09, -0.01 ± 0.10, 0.12 ± 0.08, 0.00 ± 0.09, and -0.10 ± 0.10, respectively. The results of this study suggest that selection for lower PAP measures should have minimal influence on the growth performance of yearling Angus bulls and heifers at the CSU-BIC, supporting our hypothesis.

FABP4 is a leading candidate gene associated with residual feed intake in growing Holstein calves

Ecological and economic concerns drive the need to improve feed utilization by domestic animals. Residual feed intake (RFI) is one of the most acceptable measures for feed efficiency (FE). However, phenotyping RFI-related traits is complex and expensive and requires special equipment. Advances in marker technology allow the development of various DNA-based selection tools. To assimilate these technologies for the benefit of RFI-based selection, reliable phenotypic measures are prerequisite. In the current study, we identified single nucleotide polymorphisms (SNPs) associated with RFI phenotypic consistency across different ages and diets (named RFI 1-3), using DNA samples of high or low RFI ranked Holstein calves. Using targeted sequencing of chromosomal regions associated with FE- and RFI-related traits, we identified 48 top SNPs significantly associated with at least one of three defined RFIs. Eleven of these SNPs were harbored by the fatty acid binding protein 4 (FABP4). While 10 significant SNPs found in FABP4 were common for RFI 1 and RFI 3, one SNP (FABP4_5; A<G substitution), in the promoter region of the gene, was significantly associated with all three RFIs. As the three RFI classes reflect changing diets and ages with concomitant RFI phenotypic consistency, the above polymorphisms and in particular FABP4_5, might be considered possible markers for RFI-based selection for FE in the Holstein breed, following a larger-scale validation.

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 ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0106-8) contains supplementary material, which is available to authorized users.

Identification of genomic regions associated with feed efficiency in Nelore cattle

Background

Feed efficiency is jointly determined by productivity and feed requirements, both of which are economically relevant traits in beef cattle production systems. The objective of this study was to identify genes/QTLs associated with components of feed efficiency in Nelore cattle using Illumina BovineHD BeadChip (770 k SNP) genotypes from 593 Nelore steers. The traits analyzed included: average daily gain (ADG), dry matter intake (DMI), feed-conversion ratio (FCR), feed efficiency (FE), residual feed intake (RFI), maintenance efficiency (ME), efficiency of gain (EG), partial efficiency of growth (PEG) and relative growth rate (RGR). The Bayes B analysis was completed with Gensel software parameterized to fit fewer markers than animals. Genomic windows containing all the SNP loci in each 1 Mb that accounted for more than 1.0% of genetic variance were considered as QTL region. Candidate genes within windows that explained more than 1% of genetic variance were selected by putative function based on DAVID and Gene Ontology.

Results

Thirty-six QTL (1-Mb SNP window) were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25 and 26 (UMD 3.1). The amount of genetic variance explained by individual QTL windows for feed efficiency traits ranged from 0.5% to 9.07%. Some of these QTL minimally overlapped with previously reported feed efficiency QTL for Bos taurus. The QTL regions described in this study harbor genes with biological functions related to metabolic processes, lipid and protein metabolism, generation of energy and growth. Among the positional candidate genes selected for feed efficiency are: HRH4, ALDH7A1, APOA2, LIN7C, CXADR, ADAM12 and MAP7.

Conclusions

Some genomic regions and some positional candidate genes reported in this study have not been previously reported for feed efficiency traits in Bos indicus. Comparison with published results indicates that different QTLs and genes may be involved in the control of feed efficiency traits in this Nelore cattle population, as compared to Bos taurus cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0100-0) contains supplementary material, which is available to authorized users.

Accuracy of genomic predictions in Bos indicus (Nellore) cattle

BACKGROUND

Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population.

METHODS

Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group.

RESULTS

Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships.

CONCLUSIONS

Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information.

Subspecies differences in early fetal development and plasma pregnancy-associated glycoprotein concentrations in cattle

Inclusion of Bos indicus genetics improves production traits of cattle maintained in hot climates. Limited information exists detailing pregnancy-specific events as influenced by variable amounts of Bos indicus genetics. Three experiments were completed to examine the effect of Bos taurus and Bos indicus genotypes on fetal size and plasma pregnancy-associated glycoprotein (PAG) concentrations. In all experiments, cows were bred by AI after synchronization of ovulation. Fetal measurements were completed by transrectal ultrasonography and plasma PAG concentrations were quantified from plasma harvested the day of each fetal measurement. In Exp. 1, fetal size and plasma PAG concentrations were measured at d 53 of pregnancy in cows composed of various fractions of Angus and Brahman (n = 9 to 21 cows/group). Fetus size was greater in cows containing >80% Angus genetics compared with cows containing <80% Angus influence (3.40 ± 0.28 vs. 2.86 ± 0.28 cm crown-rump length; P < 0.01). Plasma PAG concentrations were reduced (P < 0.01) in cows containing >80% Angus genetics when compared with their contemporaries (6.0 ± 1.5 ng/mL vs. 9.4 ± 1.5 ng/mL). In Exp. 2, fetal measurements and plasma PAG concentrations were determined at d 35 and 62 of pregnancy in Angus and Brangus cows. Breed did not affect fetus size at d 35, but Angus cows contained larger fetuses than Brangus cows at d 62 [3.0 ± 0.03 vs. 2.8 ± 0.03 cm crown-nose length (CNL; P > 0.01)]. Plasma PAG concentrations were not different between breed at d 35 and 62 (P > 0.1). In Exp. 3, fetal measurements and plasma samples were collected at d 33/34, 40/41, 47/48, and 54/55 post-AI in Angus and Brangus cows. Fetus size was not different (P > 0.05) between genotypes on d 33/34, 40/41, and 47/48. Angus fetuses were larger than Brangus fetuses at d 54/55 (2.1 ± 0.03 vs. 1.9 ± 0.03 cm CNL; P = 0.001). Plasma PAG concentrations were less in Angus than Brangus cows at each time point (average 4.9 ± 0.9 vs. 8.2 ± 0.9 ng/mL; P = 0.005). In conclusion, these studies determined that the Bos taurus × Bos indicus genotype impacts fetal size and rate of fetal development by 7 wk of gestation. Plasma PAG concentrations were increased in cattle with Bos indicus genetics in 2 of 3 studies, suggesting that genotype is one of several determinants of PAG production and secretion in cattle.

Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle

The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identified within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their biological functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsSNP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic variation. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on protein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD11 and UGT3A1 genes. In addition, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (IPA) software (Ingenuity Systems, www.ingenuity.com) indicated that the significant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if validated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency.