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Context: Angus SteerSELECT is a genomic tool designed to provide genomic estimated breeding values (GEBV) for nine traits related to growth, feedlot performance, carcase characteristics and immune competence. At present, GEBV for carcase characteristics are based on a reference population of 3766 Australian Angus steers. Aims: We aimed to investigate the potential benefit of incorporating commercial data into the existing reference population of the Angus SteerSELECT. To this aim, we employ a population of 2124 genotyped commercial Angus steers with carcase performance data from four commercial feedlot operators. Methods: The benefit of incorporating the commercial data (COMM) into the reference (REFE) population was assessed in terms of quality and integrity of the COMM data and meta-data to model the phenotypes adequately. We computed bias, dispersion, and accuracy of GEBV for carcase weight (CWT) and marbling (MARB) before and after including the COMM data, in whole or in partial, into the REFE population. Key results: The genomic estimate of the Angus content in the COMM population averaged 96.9% and ranged from 32.87% to 100%. For CWT, the estimates of heritability were 0.419 ± 0.026 and 0.368 ± 0.038 for the REFE and COMM populations respectively, and with a genetic correlation of 0.756 ± 0.068. For MARB, the same three parameter estimates were 0.357 ± 0.027, 0.340 ± 0.038 and 0.879 ± 0.073 respectively. The ACC of CWT GEBV increased significantly (P < 0.0001) from 0.475 when the COMM population was not part of the REFE to 0.546 (or 15%) when a random 50% of the COMM population was included in the REFE. Similarly significant increases in ACC were observed for MARB GEBV (0.470–0.521 or 11%). Conclusions: The strong genomic relationship between the REFE and the COMM populations, coupled with the significant increases in GEBV accuracies, demonstrated the potential benefits of including the COMM population into the reference population of a future improved version of the Angus SteerSELECT genomic tool. Implications: Commercial feedlot operators finishing animals with a strong Angus breed component will benefit from having their data represented in the reference population of the Angus SteerSELECT genomic tool. The present study highlighted the potential benefits of incorporating commercial data from Angus-based beef supply chain, which are independent of the Angus Australia reference population, into the existing reference population of Angus SteerSELECT genomic tool. The results help demonstrate to commercial beef producers the opportunity to apply genomic tools within commercial populations as part of routine management, since higher accuracies translate into an improved ability to predict performance, reducing the risk of steers not performing to expectation during feedlot regimes. [ABSTRACT FROM AUTHOR]

Intake by grazing animals is difficult to reliably measure in the field, particularly in more diverse grazing systems where pastures vary greatly across time and space in resource availability, which in turn leads to greater variation in animal time budgets and intake patterns. Advances in remote livestock monitoring (e.g., on-animal sensors, walk -over-weighing), and advanced analytics such as machine learning algorithms can contribute to the development of robust, adaptable tools for better understanding of animal performance and behavior in grazing systems. Many existing tools for predicting livestock production require estimates of feed intake, and while estimates based on forage sward characteristics have been developed and used for temperate, relatively homogenous pastures, they are less well defined for more diverse rangelands. These diverse pastures are more difficult to characterize due to their greater variation in quantity and quality; consequently, animal selectivity is greater in more variable pastures. However, such feedback loops between pasture diversity and animal behavior may not yet be adequately represented in biophysical models. On-animal sensors such as accelerometers and GPS devices can be used to develop new ways of assessing relative intake by providing accurate estimates of animal location and behavior profiles, such as the use of machine learning algorithms to detect how much time is spent grazing, walking, ruminating, or resting. Measurements of animal behavior could then be combined with other animal-based methods such as walk-over-weighing and fecal NIR to improve estimates of intake and production for a wide range of extensive grazing environments. Sensor-derived measurements of animal movement could also be used to improve estimates of the energetic costs of grazing, thereby improving estimates of energy available for growth. As an example, data on recent activity and paddock use from on-animal sensors could be entered into a model to estimate current feeding requirements, then combined with weather and pasture quality forecasts. The ensuing baseline could then be used to explore the potential variability of these projections and generate a range for possible expected performance over the next month or season. This approach could be repeated over time, and animal performance and behavior measures used to update model estimates and improve forward projections. These methods could also be used in conjunction with estimates of animal energy requirements to provide real-time prediction of relative feed intake, which would provide a step-change in modelling livestock production in extensive grazing systems. For these approaches to be successful, additional calibration data are needed across a wide variety of environments and species, and the tools must be cost-effective to implement. In summary, on-animal measurements provide an adaptable, data-driven approach that could be integrated with existing tools to improve our understanding of feed intake, behavior, and performance of grazing animals. [ABSTRACT FROM AUTHOR]

Context: Immune competence is a proxy trait for general disease resistance and is based on combined measures of an animal's ability to mount both a cell-mediated immune response (Cell-IR) and an antibody-mediated immune response (Ab-IR). On the basis of previously described arithmetic, we combined these measures into a single proxy trait for immune competence, named ImmuneDEX (IDEX). Aims: Using a population of 3715 Australian Angus steers (n = 2395) and heifers (n = 1320) with genotypes for 45 364 single-nucleotide polymorphisms, we provide the latest genomic estimates of heritability and genetic correlations for IDEX and the components Cell-IR and Ab-IR immune competence phenotypes. Accuracy and bias of genomic predictions of breeding values are also presented and discussed. Methods: Measures of Cell-IR, Ab-IR and IDEX were analysed jointly in a tri-variate genomic restricted maximum-likelihood model that contained the fixed effects of contemporary group with 80 levels, the linear covariates of age at measurement and change in skin thickness at control site, and the random polygenic (genomic estimated breeding value, GEBV) and residual effects. Following Method LR procedures, we estimate accuracy, bias and dispersion of genomic predictions using a cross-validation scheme based on five year-of-birth cohorts. Key results: We report genomic restricted maximum-likelihood model estimates of heritability of 0.247 ± 0.040 for Cell-IR, 0.326 ± 0.059 for Ab-IR, 0.275 ± 0.046 for IDEX. While a small positive genetic correlation (rg) was estimated between Cell-IR and Ab-IR (rg = 0.138 ± 0.095), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.740 ± 0.044) and between IDEX and Ab-IR (rg = 0.741 ± 0.036). Averaged across the five validation sets, the accuracy of GEBV for Cell-IR, Ab-IR and IDEX was 0.405, 0.443 and 0.411 respectively. Also, some significant bias or dispersion can be expected depending on the cohort used as the validation population. Conclusions: Consistent with previous findings, immune competence phenotypes are moderately heritable and accurate GEBV can be generated to allow the selection of cattle with an improved ability to mount a general immune response. Implications: Our analyses suggest that ImmuneDEX will provide a tool to underpin long-term genetic strategies aimed at improving the immune competence of Australian Angus cattle in production systems, which, in turn, is expected to reduce the incidence of disease and our reliance on antibiotics to treat disease. [ABSTRACT FROM AUTHOR]

Context. Genomic-based technologies are allowing commercial beef producers to predict the genetic merit of individual animals of unknown pedigree with increased ease and accuracy. Genomic selection tools that can accurately predict the feedlot and carcass performance of steers have the potential to improve profitability for the beef supply chain. Aims. To validate the ability of the Angus SteerSELECT genomic product to predict differences in performance of Australian Angus steers, in terms of carcass weight, marbling score, ossification score and carcass value, using a short-fed (100 days) or long-fed (270 days) finishing protocol at a commercial feedlot. Methods. A reference population of 2763 Australian Angus steers was used to generate genomic prediction equations for three carcass traits, namely, carcass weight, marbling score and ossification. The accuracy and bias of genomic predictions of breeding values were then evaluated using a validation population of 522 Angus steers, either short- or long-fed at a commercial feedlot, by comparing breeding values to measured phenotypes. The potential economic benefits for feedlot operators when using Angus SteerSELECT were estimated on the basis of the ability of the tool to predict the carcass value of steers in the validation population. Key results. The accuracy of genomic predictions of breeding values for carcass weight, marbling score and ossification score were 0.752, 0.723 and 0.734 respectively. When steers were ranked in quartiles for predicted carcass value, calculated using genomic predictions of breeding values for carcass weight and marbling score, the least-square mean carcass value for steers in each quartile, from bottom 25% predicted performers to top 25% predicted performers, were estimated at A$1794, A$1977, A$2021 and A$2148 for short-fed steers and A$3546, A$3780, A$3864 and A $4258 for long-fed steers. Differences in the carcass value least-squares mean between the bottom and top quartile were highly significant (P < 0.001) for both short-fed and long-fed steers. Conclusions. Genomic prediction equations used in Angus SteerSELECT can predict differences in carcass weight, marbling score, ossification score and carcass value in both short-fed and long-fed Australian Angus steers. Implications. Genomic selection tools that can predict differences in performance, in terms of growth and carcass characteristics, of commercial feedlot cattle have the potential to significantly increase profitability for the beef supply chain by improving the quality and consistency of the beef products they produce. [ABSTRACT FROM AUTHOR]

Background: Improving feedlot performance, carcase weight and quality is a primary goal of the beef industry worldwide. Here, we used data from 3408 Australian Angus steers from seven years of birth (YOB) cohorts (2011–2017) with a minimal level of sire linkage and that were genotyped for 45,152 SNPs. Phenotypic records included two feedlot and five carcase traits, namely average daily gain (ADG), average daily dry matter intake (DMI), carcase weight (CWT), carcase eye muscle area (EMA), carcase Meat Standard Australia marbling score (MBL), carcase ossification score (OSS) and carcase subcutaneous rib fat depth (RIB). Using a 7-way cross-validation based on YOB cohorts, we tested the quality of genomic predictions using the linear regression (LR) method compared to the traditional method (Pearson's correlation between the genomic estimated breeding value (GEBV) and its associated adjusted phenotype divided by the square root of heritability); explored the factors, such as heritability, validation cohort, and phenotype that affect estimates of accuracy, bias, and dispersion calculated with the LR method; and suggested a novel interpretation for translating differences in accuracy into phenotypic differences, based on GEBV quartiles (Q1Q4). Results: Heritability (h2) estimates were generally moderate to high (from 0.29 for ADG to 0.53 for CWT). We found a strong correlation (0.73, P-value < 0.001) between accuracies using the traditional method and those using the LR method, although the LR method was less affected by random variation within and across years and showed a better ability to discriminate between extreme GEBV quartiles. We confirmed that bias of GEBV was not significantly affected by h2, validation cohort or trait. Similarly, validation cohort was not a significant source of variation for any of the GEBV quality metrics. Finally, we observed that the phenotypic differences were larger for higher accuracies. Conclusions: Our estimates of h2 and GEBV quality metrics suggest a potential for accurate genomic selection of Australian Angus for feedlot performance and carcase traits. In addition, the Q1Q4 measure presented here easily translates into possible gains of genomic selection in terms of phenotypic differences and thus provides a more tangible output for commercial beef cattle producers. [ABSTRACT FROM AUTHOR]

In animal breeding and genetics, the ability to cope with disease, here defined as immune competence (IC), with minimal detriment to growth and fertility is a desired objective which addresses both animal production and welfare considerations. However, defining and objectively measuring IC phenotypes using testing methods which are practical to apply on-farm has been challenging. Based on previously described protocols, we measured both cell-mediated immune response (Cell-IR) and antibody-mediated immune response (Ab-IR) and combined these measures to determine an animal's IC. Using a population of 2,853 Australian Angus steers and heifers, we compared 2 alternative methods to combine both metrics into a single phenotype to be used as a tool for the genetic improvement of IC. The first method, named Z MEAN, is obtained by taking the average of the individual metrics after subjecting each to a Z -score standardization. The second, ImmuneDEX (IDEX), is a weighted average that considers the correlation between Cell-IR and Ab-IR, as well as the difference in ranking of individuals by each metric, and uses these as weights in the averaging. Both simulation and real data were used to understand the behavior of Z MEAN and IDEX. To further ascertain the relationship between IDEX and other traits of economic importance, we evaluated a range of traits related to growth, feedlot performance, and carcass characteristics. We report estimates of heritability of 0.31 ± 0.06 for Cell-IR, 0.42 ± 0.06 for Ab-IR, 0.42 ± 0.06 for Z MEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (r g) between Z MEAN and IDEX. While a moderately positive r g was estimated between Cell-IR and Ab-IR (r g = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (r g = 0.80 ± 0.05) and between IDEX and Ab-IR (r g = 0.85 ± 0.04). We obtained a moderately negative r g between IC traits and growth including an r g = −0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an r g = −0.03 ± 0.12 between IDEX and marbling. Given that breeding with a sole focus on production might inadvertently increase susceptibility to disease and associated antibiotic use, our analyses suggest that ImmuneDEX will provide a basis to breed animals that are both highly productive and with an enhanced ability to resist disease. [ABSTRACT FROM AUTHOR]

Selection for production traits with little or no emphasis on health-related traits has the potential to increase susceptibility to disease in food-producing animals. A possible genetic strategy to mitigate such effects is to include both production and health traits in the breeding objective when selecting animals. For this to occur, reliable methodologies are required to assess beneficial health traits, such as the immune capacity of animals. We describe here a methodology to assess the immune competence of beef cattle which is both practical to apply on farm and does not restrict the future sale of tested animals. The methodology also accommodates variation in prior vaccination history of cohorts of animals being tested. In the present study, the immune competence phenotype of 1,100 Angus calves was assessed during yard weaning. Genetic parameters associated with immune competence traits were estimated and associations between immune competence, temperament, and stress-coping ability traits were investigated. Results suggested that immune competence traits, related to an animal's ability to mount both antibody and cell-mediated immune responses, are moderately heritable (h 2 = 0.32 ± 0.09 and 0.27 ± 0.08, respectively) and favorably genetically correlated with the temperament trait, flight time (r = 0.63 ± 0.31 and 0.60 ± 0.29 with antibody and cell-mediated immune responses, respectively). Development of methodologies to assess the immune competence phenotype of beef cattle is a critical first step in the establishment of genetic selection strategies aimed at improving the general disease resistance of beef herds. Strategies aimed at reducing the incidence of disease in beef cattle are expected to significantly improve animal health and welfare, reduce reliance on the use of antibiotics to treat disease, and reduce disease-associated costs incurred by producers. [ABSTRACT FROM AUTHOR]

Our capacity to measure performance- and efficiency-related phenotypes in grazing livestock in a timely manner, ideally in real-time without human interference, has been severely limited. Future demands and constraints on grazing livestock production will require a step change beyond our current approaches to obtaining phenotypic data. Animal phenomics is a relatively new term that describes the next generation of animal trait measurement, including methodologies and equipment used to acquire data on traits, and computational approaches required to turn data into phenotypic information. Phenomics offers a range of emerging opportunities to define new traits specific to grazing livestock, including intake and efficiency at pasture, and to measure many traits simultaneously or at a level of detail previously unachievable in the grazing environment. Application of this approach to phenotyping can improve the precision with which nutritional and other management strategies are applied, enable development of predictive biological traits, and accelerate the rate at which genetic gain is achieved for existing and new traits. In the present paper, we briefly outline the potential for livestock phenomics and describe (1) on-animal sensory-based approaches to develop traits diagnostic of productivity and efficiency, as well as resilience, health and welfare and (2) on-farm methods for data collection that drive management solutions to reduce input costs and accelerate genetic gain. The technological and analytical challenges associated with these objectives are also briefly considered, along with a brief overview of a promising field of work in which phenomics will affect animal agriculture, namely efficiency at pasture. [ABSTRACT FROM AUTHOR]

Background Muscle development and remodelling, mitochondrial physiology and inflammation are thought to be inter-related and to have implications for metabolism in both health and disease. However, our understanding of their molecular control is incomplete. Results In this study we have confirmed that the ring finger 14 protein (RNF14), a poorly understood transcriptional regulator, influences the expression of both mitochondrial and immune-related genes. The prediction was based on a combination of network connectivity and differential connectivity in cattle (a non-model organism) and mice data sets, with a focus on skeletal muscle. They assigned similar probability to mammalian RNF14 playing a regulatory role in mitochondrial and immune gene expression. To try and resolve this apparent ambiguity we performed a genome-wide microarray expression analysis on mouse C2C12 myoblasts transiently transfected with two Rnf14 transcript variants that encode 2 naturally occurring but different RNF14 protein isoforms. The effect of both constructs was significantly different to the control samples (untransfected cells and cells transfected with an empty vector). Cluster analyses revealed that transfection with the two Rnf14 constructs yielded discrete expression signatures from each other, but in both cases a substantial set of genes annotated as encoding proteins related to immune function were perturbed. These included cytokines and interferon regulatory factors. Additionally, transfection of the longer transcript variant 1 coordinately increased the expression of 12 (of the total 13) mitochondrial proteins encoded by the mitochondrial genome, 3 of which were significant in isolated pair-wise comparisons (Mt-coxII, Mt-nd2 and mt-nd4l). This apparent additional mitochondrial function may be attributable to the RWD protein domain that is present only in the longer RNF14 isoform. Conclusions RNF14 influences the expression of both mitochondrial and immune related genes in a skeletal muscle context, and has likely implications for the inter-relationship between bioenergetic status and inflammation. [ABSTRACT FROM AUTHOR]

Long (6- to 9-mo) bouts of estivation in green-striped burrowing frogs lead to 28% atrophy of cruralis oxidative fibers (P < 0.05) and some impairment of in vitro gastrocnemius endurance (P < 0.05) but no significant deficit in maximal twitch force production. These data suggest the preferential atrophy of oxidative fibers at a rate slower than, but comparable to, laboratory disuse models. We tested the hypothesis that the frog limits atrophy by modulating oxidative stress. We assayed various proteins at the transcript level and verified these results for antioxidant enzymes at the biochemical level. Transcript data for NADH ubiquinone oxidoreductase subunit 1 (71% downregulated, P < 0.05) and ATP synthase (67% downregulated, P < 0.05) are consistent with mitochondrial quiescence and reduced oxidant production. Meanwhile, uncoupling protein type 2 transcription (P = 0.31), which is thought to reduce mitochondrial leakage of reactive oxygen species, was maintained. Total antioxidant defense of water-soluble (22.3 ± 1.7 and 23.8 ± 1.5 μM/μg total protein in control and estivator, respectively, P = 0.53) and membrane-bound proteins (31.5 ± 1.9 and 42.1 ± 7.3 μM/μg total protein in control and estivator, respectively, P = 0.18) was maintained, equivalent to a bolstering of defense relative to oxygen insult. This probably decelerates muscle atrophy by preventing accumulation of oxidative damage in static protein reserves. Transcripts of the mitochondrially encoded antioxidant superoxide dismutase type 2 (67% downregulated, P < 0.05) paralleled mitochondrial activity, whereas nuclear-encoded catalase and glutathione peroxidase were maintained at control values (P = 0.42 and P = 0.231), suggesting a dissonance between mitochondrial and nuclear antioxidant expression. Pyruvate dehydrogenase kinase 4 transcription was fourfold lower in estivators (P = 0.11), implying that, in contrast to mammalian hibernators, this enzyme does not drive the combustion of lipids that helps spare hypometabolic muscle. [ABSTRACT FROM AUTHOR]

Correction to: Genet Sel Evol (2021) 53: 77 https://doi.org/10.1186/s12711-021-00673-8 After the publication of the original article [[1]], the authors noticed that there was an error. Reference 1 Alexandre PA, Li Y, Hine BC, Duff CJ, Ingham AB, Porto-Neto LR, Reverter A. Bias dispersion and accuracy of genomic predictions for feedlot and carcase traits in Australian Angus steers. [Extracted from the article]