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Background The advent of next-generation sequencing enables the opportunity to use denser marker tools, up to whole-genome sequences (WGS), for genomic prediction in livestock. Improvement in genomic prediction (GP) accuracy from using WGS has been observed in simulation studies. In contrast, such advantage has found to be inconsistent once implemented in practice. The benefit of WGS appears to be from markers that are significant for the trait of interest. Thus, the main objective of this study was to investigate the predictive ability of adding preselected markers to the standard-industry 50k genotype for GP of economically important traits in Angus cattle, namely, birth weight (BW), scrotal circumference (SC), carcass weight (CWT) and carcass intramuscular fat (CIMF). Animals were genotyped with either commercial or customised SNP-genotyping arrays; then, the genotypes were imputed to WGS. The 50k genotype was used as the control group. Informative markers associated with the desired traits were extracted from WGS, then were added to the 50k genotype. Several methods were chosen to select different sets of informative markers, including LD-based pruning, top SNP from a genome-wide association study (GWAS), functional annotation based on Gene Ontology, cattle QTL database, and sequence annotation. In total, eight different sets of genotypes were investigated. We applied different statistical models to predict genomic breeding values, including GBLUP, BayesR, and BayesRC, and two-GRM GBLUP constructed separately from the 50k and the preselected genotype set. Results Heritability (h 2 ) estimates were similarly calculated using different sets of genotypes and statistical methods across all traits. The log-likelihood ratio values revealed that two-GRM GBLUP was more suitable than the single-GRM GBLUP. There was no significant difference in accuracy and bias among the different sets of genotypes compared to the control group or the statistical methods, except for BW. For BW, the Bayesian models slightly outperformed GBLUP. Conclusions The findings suggest that potential improvements may be achieved by using preselected SNPs from the GWAS, a method that has proven within the population. The performance of preselected markers on GP influenced by several factors, including population structure, method used to select significant markers, and genetic architecture of traits.

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 (h 2 ) 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 h 2 , 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 h 2 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 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 ZMEAN, 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 ZMEAN 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 ZMEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (rg) between ZMEAN and IDEX. While a moderately positive rg was estimated between Cell-IR and Ab-IR (rg = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.80 ± 0.05) and between IDEX and Ab-IR (rg = 0.85 ± 0.04). We obtained a moderately negative rg between IC traits and growth including an rg = −0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an rg = −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.

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 (h2 = 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 Genetic strategies aimed at improving general immune competence (IC) have the potential to reduce the incidence and severity of disease in beef production systems, with resulting benefits of improved animal health and welfare and reduced reliance on antibiotics to prevent and treat disease. Implementation of such strategies first requires that methodologies be developed to phenotype animals for IC and demonstration that these phenotypes are associated with health outcomes. We have developed a methodology to identify IC phenotypes in beef steers during the yard weaning period, which is both practical to apply on-farm and does not restrict the future sale of tested animals. In the current study, a total of 838 Angus steers, previously IC phenotyped at weaning, were categorized as low (n = 98), average (n = 653), or high (n = 88) for the IC phenotype. Detailed health and productivity data were collected on all steers during feedlot finishing, and associations between IC phenotype, health outcomes, and productivity were investigated. A favorable association between IC phenotype and number of mortalities during feedlot finishing was observed with higher mortalities recorded in low IC steers (6.1%) as compared with average (1.2%, P < 0.001) or high (0%, P = 0.018) IC steers. Disease incidence was numerically highest in low IC steers (15.3 cases/100 animals) and similar in average IC steers (10.1 cases/100 animals) and high IC steers (10.2 cases/100 animals); however, differences between groups were not significant. No significant influence of IC phenotype on average daily gain was observed, suggesting that selection for improved IC is unlikely to incur a significant penalty to production. The potential economic benefits of selecting for IC in the feedlot production environment were calculated. Health-associated costs were calculated as the sum of lost production costs, lost capital investment costs, and disease treatment costs. Based on these calculations, health-associated costs were estimated at AUS$103/head in low IC steers, AUS$25/head in average IC steers, and AUS$4/head in high IC steers, respectively. These findings suggest that selection for IC has the potential to reduce mortalities during feedlot finishing and, as a consequence, improve the health and welfare of cattle in the feedlot production environment and reduce health-associated costs incurred by feedlot operators.

Abstract 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 (h2 = 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.

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 (h2 = 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.

A key principle of brain organization is the functional integration of brain regions into interconnected networks. Functional MRI scans acquired at rest offer insights into functional integration via patterns of coherent fluctuations in spontaneous activity, known as functional connectivity. These patterns have been studied intensively and have been linked to cognition and disease. However, the field is fractionated. Diverging analysis approaches have segregated the community into research silos, limiting the replication and clinical translation of findings. A primary source of this fractionation is the diversity of approaches used to reduce complex brain data into a lower-dimensional set of features for analysis and interpretation, which we refer to as brain representations. In this Primer, we provide an overview of different brain representations, lay out the challenges that have led to the fractionation of the field and that continue to form obstacles for convergence, and propose concrete guidelines to unite the field.In this Primer article, Bijsterbosch and colleagues provide an accessible discussion of the challenges faced in analytical representations of functional brain organization and provide clear recommendations to unite a fractionated field.

Background Non-small cell lung cancers (NSCLC) account for 85–90% of all lung cancers. As drug resistance critically impairs chemotherapy effectiveness, there is great need to identify new therapeutic targets. The aims of this study were to investigate the prognostic and therapeutic potential of the copper-metabolism-domain-protein, COMMD4, in NSCLC. Methods The expression of COMMD4 in NSCLC was investigated using bioinformatic analysis, immunoblotting of immortalised human bronchial epithelial (HBEC) and NSCLC cell lines, qRT-PCR and immunohistochemistry of tissue microarrays. COMMD4 function was additionally investigated in HBEC and NSCLC cells depleted of COMMD4, using small interfering RNA sequences. Results Bioinformatic analysis and in vitro analysis of COMMD4 transcripts showed that COMMD4 levels were upregulated in NSCLC and elevated COMMD4 was associated with poor prognosis in adenocarcinoma (ADC). Immunoblotting demonstrated that COMMD4 expression was upregulated in NSCLC cells and siRNA-depletion of COMMD4, decreased cell proliferation and reduced cell viability. Cell death was further enhanced after exposure to DNA damaging agents. COMMD4 depletion caused NSCLC cells to undergo mitotic catastrophe and apoptosis. Conclusions Our data indicate that COMMD4 may function as a prognostic factor in ADC NSCLC. Additionally, COMMD4 is a potential therapeutic target for NSCLC, as its depletion induces cancer cell death.