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.United States Department of Agriculture (USDA) (017-67007-26143)Florida Agricultural Experiment Station Hatch (FLA-ANS-005548

Genetic parameters for hair characteristics and core body temperature in a multibreed Brahman-Angus herd

Thermal stress in hot humid conditions limits cattle production. The objectives for this study were to estimate genetic parameters for hair characteristics and core body temperature under low and high temperature humidity index (THI) conditions. Hair samples were collected and measured for length and diameter. Core body temperature was measured as vaginal temperature every 15 min over a 5-d period using an iButton temperature measuring device implanted in a blank CIDR in 336 heifers from the University of Florida multibreed herd (ranging from 100% Angus to 100% Brahman). Restricted maximum likelihood procedures were used to estimate heritabilities from multiple bivariate animal models using the WOMBAT program. Estimates of heritability for hair diameter, undercoat length, topcoat length, body temperature under low THI conditions, and body temperature under high THI conditions were 0.50, 0.67, 0.42, 0.32, and 0.26, respectively. The genetic parameters estimated in this study indicate a large, exploitable genetic variance which can be selected upon to improve tolerance in cattle. Breed effects for differing compositions of Brahman and Angus were also estimated. As Brahman breed composition increased by 25% undercoat length, topcoat length, body temperature under low THI conditions, and body temperature under high THI conditions decreased by 1.32 mm, 2.94 mm, 0.11 degrees C, and 0.14 degrees C, respectively. Under both low and high THI conditions, cattle with 25% Brahman breed composition or greater maintained a significantly lower body temperature than the 100% Angus breed group. The incorporation of Brahman germplasm is recommended for herds that often experience heat stress conditions in order to increase resilience to heat stress.United States Department of Agriculture (USDA

Structural Equation Modeling and Whole-Genome Scans Uncover Chromosome Regions and Enriched Pathways for Carcass and Meat Quality in Beef

Structural equation models involving latent variables are useful tools for formulating hypothesized models defined by theoretical variables and causal links between these variables. The objectives of this study were: (1) to identify latent variables underlying carcass and meat quality traits and (2) to perform whole-genome scans for these latent variables in order to identify genomic regions and individual genes with both direct and indirect effects. A total of 726 steers from an Angus-Brahman multibreed population with records for 22 phenotypes were used. A total of 480 animals were genotyped with the GGP Bovine F-250. The single-step genomic best linear unbiased prediction method was used to estimate the amount of genetic variance explained for each latent variable by chromosome regions of 20 adjacent SNP-windows across the genome. Three types of genetic effects were considered: (1) direct effects on a single latent phenotype; (2) direct effects on two latent phenotypes simultaneously; and (3) indirect effects. The final structural model included carcass quality as an independent latent variable and meat quality as a dependent latent variable. Carcass quality was defined by quality grade, fat over the ribeye and marbling, while the meat quality was described by juiciness, tenderness and connective tissue, all of them measured through a taste panel. From 571 associated genomic regions (643 genes), each one explaining at least 0.05% of the additive variance, 159 regions (179 genes) were associated with carcass quality, 106 regions (114 genes) were associated with both carcass and meat quality, 242 regions (266 genes) were associated with meat quality, and 64 regions (84 genes) were associated with carcass quality, having an indirect effect on meat quality. Three biological mechanisms emerged from these findings: postmortem proteolysis of structural proteins and cellular compartmentalization, cellular proliferation and differentiation of adipocytes, and fat deposition

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

Genetic and genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield, and four mastitis-related traits (milk somatic cell count, California Mastitis Test score, total viable bacterial count in milk and clinical mastitis presence) were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism (SNP) array. We performed targeted genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis traits. Environmental factors appeared to favour both milk production and udder health. There were no overlapping of SNPs associated with mastitis resistance and milk yield in Chios sheep. Furthermore, four distinct Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations other than those previously identified to affect mastitis resistance. Five genes (DNAJA1, GHR, LYPLA1, NUP35 and OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of two of these genes (NUP35 and OXCT1) was enriched in immune tissues implying a potentially pleiotropic effect or likely role in milk production during udder infection, which needs to be further elucidated in future studies. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable

Population Structure and Genomic Breed Composition in an Angus–Brahman Crossbred Cattle Population

Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information

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.Agriculture and Food Research Initiative of USDA-NIFA (2013-68004-20365)Southeast Milk Inc. Milk Checkoff ProgramL.E. "Red" Larson Endowmen

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits

RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef.

RNA sequencing (RNA-seq) has allowed for transcriptional profiling of biological systems through the identification of differentially expressed (DE) genes and pathways. A total of 80 steers with extreme phenotypes were selected from the University of Florida multibreed Angus-Brahman herd. The average slaughter age was 12.91±8.69 months. Tenderness, juiciness and connective tissue assessed by sensory panel, along with marbling, Warner-Bratzler Shear Force (WBSF) and cooking loss, were measured in longissimus dorsi muscle. Total RNA was extracted from muscle and one RNA-seq library per sample was constructed, multiplexed, and sequenced based on protocols by Illumina HiSeq-3000 platform to generate 2×101 bp paired-end reads. The overall read mapping rate using the Btau_4.6.1 reference genome was 63%. A total of 8,799 genes were analyzed using two different methodologies, an expression association and a DE analysis. A gene and exon expression association analysis was carried out using a meat quality index on all 80 samples as a continuous response variable. The expression of 208 genes and 3,280 exons from 1,565 genes was associated with the meat quality index (p-value ≤ 0.05). A gene and isoform DE evaluation was performed analyzing two groups with extreme WBSF, tenderness and marbling. A total of 676 (adjusted p-value≤0.05), 70 (adjusted p-value≤0.1) and 198 (adjusted p-value≤0.1) genes were DE for WBSF, tenderness and marbling, respectively. A total of 106 isoforms from 98 genes for WBSF, 13 isoforms from 13 genes for tenderness and 43 isoforms from 42 genes for marbling (FDR≤0.1) were DE. Cytoskeletal and transmembrane anchoring genes and pathways were identified in the expression association, DE and the gene enrichment analyses; these proteins can have a direct effect on meat quality. Cytoskeletal proteins and transmembrane anchoring molecules can influence meat quality by allowing cytoskeletal interaction with myocyte and organelle membranes, contributing to cytoskeletal structure and architecture maintenance postmortem