Identification of Susceptibility Genes Underlying Bovine Respiratory Disease in Xinjiang Brown Cattle Based on DNA Methylation.

DNA methylation is a form of epigenetic regulation, having pivotal parts in controlling cellular expansion and expression levels within genes. Although blood DNA methylation has been studied in humans and other species, its prominence in cattle is largely unknown. This study aimed to methodically probe the genomic methylation map of Xinjiang brown (XJB) cattle suffering from bovine respiratory disease (BRD), consequently widening cattle blood methylome ranges. Genome-wide DNA methylation profiling of the XJB blood was investigated through whole-genome bisulfite sequencing (WGBS). Many differentially methylated regions (DMRs) obtained by comparing the cases and controls groups were found within the CG, CHG, and CHH (where H is A, T, or C) sequences (16,765, 7502, and 2656, respectively), encompassing 4334 differentially methylated genes (DMGs). Furthermore, GO/KEGG analyses showed that some DMGs were involved within immune response pathways. Combining WGBS-Seq data and existing RNA-Seq data, we identified 71 significantly differentially methylated (DMGs) and expressed (DEGs) genes (p < 0.05). Next, complementary analyses identified nine DMGs (LTA, STAT3, IKBKG, IRAK1, NOD2, TLR2, TNFRSF1A, and IKBKB) that might be involved in the immune response of XJB cattle infected with respiratory diseases. Although further investigations are needed to confirm their exact implication in the involved immune processes, these genes could potentially be used for a marker-assisted selection of animals resistant to BRD. This study also provides new knowledge regarding epigenetic control for the bovine respiratory immune process.

Use of nCounter mRNA profiling to identify at-arrival gene expression patterns for predicting bovine respiratory disease in beef cattle.

BACKGROUND: Transcriptomics has identified at-arrival differentially expressed genes associated with bovine respiratory disease (BRD) development; however, their use as prediction molecules necessitates further evaluation. Therefore, we aimed to selectively analyze and corroborate at-arrival mRNA expression from multiple independent populations of beef cattle. In a nested case-control study, we evaluated the expression of 56 mRNA molecules from at-arrival blood samples of 234 cattle across seven populations via NanoString nCounter gene expression profiling. Analysis of mRNA was performed with nSolver Advanced Analysis software (p < 0.05), comparing cattle groups based on the diagnosis of clinical BRD within 28 days of facility arrival (n = 115 Healthy; n = 119 BRD); BRD was further stratified for severity based on frequency of treatment and/or mortality (Treated_1, n = 89; Treated_2+, n = 30). Gene expression homogeneity of variance, receiver operator characteristic (ROC) curve, and decision tree analyses were performed between severity cohorts. RESULTS: Increased expression of mRNAs involved in specialized pro-resolving mediator synthesis (ALOX15, HPGD), leukocyte differentiation (LOC100297044, GCSAML, KLF17), and antimicrobial peptide production (CATHL3, GZMB, LTF) were identified in Healthy cattle. BRD cattle possessed increased expression of CFB, and mRNA related to granulocytic processes (DSG1, LRG1, MCF2L) and type-I interferon activity (HERC6, IFI6, ISG15, MX1). Healthy and Treated_1 cattle were similar in terms of gene expression, while Treated_2+ cattle were the most distinct. ROC cutoffs were used to generate an at-arrival treatment decision tree, which classified 90% of Treated_2+ individuals. CONCLUSIONS: Increased expression of complement factor B, pro-inflammatory, and type I interferon-associated mRNA hallmark the at-arrival expression patterns of cattle that develop severe clinical BRD. Here, we corroborate at-arrival mRNA markers identified in previous transcriptome studies and generate a prediction model to be evaluated in future studies. Further research is necessary to evaluate these expression patterns in a prospective manner.

Validating loci associated with bovine respiratory disease complex in pre-weaned Holstein calves.

Bovine respiratory disease (BRD) is considered one of the most economically important diseases in the cattle industry. Ultimately, the selection of cattle that are less susceptible to disease will allow producers to reduce the prevalence of BRD and lessen its economic impact. The objective of this study was to validate previously identified loci associated with susceptibility to BRD in an independent population of 140 pre-weaned Holstein calves from Wisconsin (WI). Using the McGuirk health scoring system, calves were classified as either clinically affected with BRD (n = 35) or healthy (n = 105). Additive genotypic tests were performed for genomic regions previously associated with susceptibility to BRD in calves from California (CA) and New Mexico (NM). Using this method, 4 loci (P < 0.01) consisting of 10 SNP were validated in the WI population, including 2 loci from CA, 1 locus from NM, and 1 locus from a combined CA + NM population. Most of the positional candidate genes and transcription factor binding site motifs associated with these loci have functions related to innate and adaptive immune responses. The validation of loci associated with susceptibility to BRD in independent populations allows producers to more reliably select cattle that are less susceptible to BRD, improving animal welfare, decreasing the annual revenue losses, and lowering the prevalence of the disease.

Genomic analysis of bovine respiratory disease and lung consolidation in preweaned Holstein calves using clinical scoring and lung ultrasound.

Bovine respiratory disease (BRD) is a leading cause of morbidity and mortality in dairy calves, with detrimental long-term effects that include stunted growth, increased age at first calving, and decreased milk production in first lactation. The objectives of this study were to establish a protocol for objective and efficient assessment of BRD phenotypes in preweaned dairy calves, develop a genomic reference population with well-defined clinical and subclinical phenotypes, identify chromosomal regions associated with BRD in a genome-wide association study, estimate genetic parameters of BRD, and predict genomic breeding values of dairy calves. A total of 1,107 Holstein calves from 6 dairy farms in southern Wisconsin were examined using clinical respiratory scoring and lung ultrasound at 3 and 6 wk of age. The clinical respiratory score was based on visual appraisal of eyes, nose, ears, cough, and temperature. Lung ultrasound scores were assigned based on the amount of consolidation present. Calves were genotyped with a commercially available SNP array and after quality control and imputation to higher density, 690,291 SNP markers and 1,014 individuals remained. Single-step genome-wide association study and single-step genomic best linear unbiased prediction were applied to binary 3- and 6-wk phenotypes considered as overall respiratory healthy versus affected (RESP3, RESP6) or as presence or absence of lung consolidation (CON3, CON6). Lung ultrasound combined with a clinical scoring system allowed for efficient and objective assessment for the prevalence of BRD. Proportions of variance attributed to 1-Mb non-overlapping windows suggested genomic regions that may contain putative candidate genes, most notably regions on Bos taurus autosomes 1, 6, 7, 10, 11, 12, 15, 17, 18, 27, and 28 that explained 0.70 to 1.45% of the genetic variance. Heritability estimates were higher at 3 wk (0.214 and 0.241 for CON3 and RESP3, respectively) than 6 wk (0.084 and 0.111 for CON6 and RESP6, respectively), and mean reliabilities of genomic estimated breeding vales for calves with genotypes and phenotypes ranged from 0.12 for CON6 to 0.30 for RESP3.

QTL-mapping and genomic prediction for bovine respiratory disease in U.S. Holsteins using sequence imputation and feature selection.

BACKGROUND: National genetic evaluations for disease resistance do not exist, precluding the genetic improvement of cattle for these traits. We imputed BovineHD genotypes to whole genome sequence for 2703 Holsteins that were cases or controls for Bovine Respiratory Disease and sampled from either California or New Mexico to construct and compare genomic prediction models. The sequence variation reference dataset comprised variants called for 1578 animals from Run 5 of the 1000 Bull Genomes Project, including 450 Holsteins and 29 animals sequenced from this study population. Genotypes for 9,282,726 variants with minor allele frequencies ≥5% were imputed and used to obtain genomic predictions in GEMMA using a Bayesian Sparse Linear Mixed Model. RESULTS: Variation explained by markers increased from 13.6% using BovineHD data to 14.4% using imputed whole genome sequence data and the resolution of genomic regions detected as harbouring QTL substantially increased. Explained variation in the analysis of the combined California and New Mexico data was less than when data for each state were separately analysed and the estimated genetic correlation between risk of Bovine Respiratory Disease in California and New Mexico Holsteins was - 0.36. Consequently, genomic predictions trained using the data from one state did not accurately predict disease risk in the other state. To determine if a prediction model could be developed with utility in both states, we selected variants within genomic regions harbouring: 1) genes involved in the normal immune response to infection by pathogens responsible for Bovine Respiratory Disease detected by RNA-Seq analysis, and/or 2) QTL identified in the association analysis of the imputed sequence variants. The model based on QTL selected variants is biased but when trained in one state generated BRD risk predictions with positive accuracies in the other state. CONCLUSIONS: We demonstrate the utility of sequence-based and biology-driven model development for genomic selection. Disease phenotypes cannot be routinely recorded in most livestock species and the observed phenotypes may vary in their genomic architecture due to variation in the pathogen composition across environments. Elucidation of trait biology and genetic architecture may guide the development of prediction models with utility across breeds and environments.

Identification of SNPs located on BTA 6 and BTA 20 significantly associated with bovine respiratory disease in crossbred cattle.

The objective of the present study was to evaluate single nucleotide polymorphisms (SNPs) located in two quantitative trait locus (QTL) regions (BTA 6 and BTA 20) that are associated with bovine respiratory disease (BRD). A population of 323 crossbred steers sired by five purebred sire breeds during 2010-2013 (Angus, Braford, Braunvieh, Charolais, and Simmental) were evaluated for BRD susceptibility during the finishing process at a commercial feedlot. A total of 21 animals representing all sire breeds were affected with BRD at some time during the finishing process over the 4-year period. Although multiple sire breeds were evaluated in the present study, no sire breed effects were detected. A total of 82 SNPs were evaluated (58 on BTA 6 and 24 on BTA 20) in the present study for potential associations with BRD incidence. When evaluating the previously described QTL regions on BTA 6, three SNPs (rs42968895, rs42823614, and rs43448463) were significantly (P < 0.05) associated with BRD incidence. Another three SNPs (rs42477340, rs42512588, and rs42524468) were identified as significantly associated with BRD on the previously described BTA 6 QTL region. For both of these regions, animals inheriting different genotypes differed in BRD incidence during the finishing period. Although multiple SNPs were identified as being significantly associated with BRD incidence in the present study, these SNP associations should be validated in larger and more diverse populations.

Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned holstein calves.

BACKGROUND: Bovine respiratory disease complex (BRDC) is an infectious disease of cattle that is caused by a combination of viral and/or bacterial pathogens. Selection for cattle with reduced susceptibility to respiratory disease would provide a permanent tool for reducing the prevalence of BRDC. The objective of this study was to identify BRDC susceptibility loci in pre-weaned Holstein calves as a prerequisite to using genetic improvement as a tool for decreasing the prevalence of BRDC. High density SNP genotyping with the Illumina BovineHD BeadChip was conducted on 1257 male and 757 female Holstein calves from California (CA), and 767 calves identified as female from New Mexico (NM). Of these, 1382 were classified as BRDC cases, and 1396 were classified as controls, with all phenotypes assigned using the McGuirk health scoring system. During the acquisition of blood for DNA isolation, two deep pharyngeal and one mid-nasal diagnostic swab were obtained from each calf for the identification of bacterial and viral pathogens. Genome-wide association analyses were conducted using four analytical approaches (EIGENSTRAT, EMMAX-GRM, GBLUP and FvR). The most strongly associated SNPs from each individual analysis were ranked and evaluated for concordance. The heritability of susceptibility to BRDC in pre-weaned Holstein calves was estimated. RESULTS: The four statistical approaches produced highly concordant results for 373 top ranked SNPs that defined 126 chromosomal regions for the CA population. Similarly, in NM, 370 SNPs defined 138 genomic regions that were identified by all four approaches. When the two populations were combined (i.e., CA + NM) and analyzed, 324 SNPs defined 116 genomic regions that were associated with BRDC across all analytical methods. Heritability estimates for BRDC were 21% for both CA and NM as individual populations, but declined to 13% when the populations were combined. CONCLUSIONS: Four analytical approaches utilizing both single and multi-marker association methods revealed common genomic regions associated with BRDC susceptibility that can be further characterized and used for genomic selection. Moderate heritability estimates were observed for BRDC susceptibility in pre-weaned Holstein calves, thereby supporting the application of genomic selection to reduce the prevalence of BRDC in U.S. Holsteins.

Comprehensive time-course gene expression evaluation of high-risk beef cattle to establish immunological characteristics associated with undifferentiated bovine respiratory disease.

Bovine respiratory disease (BRD) remains the leading infectious disease in beef cattle production systems. Host gene expression upon facility arrival may indicate risk of BRD development and severity. However, a time-course approach would better define how BRD development influences immunological and inflammatory responses after disease occurrences. Here, we evaluated whole blood transcriptomes of high-risk beef cattle at three time points to elucidate BRD-associated host response. Sequenced jugular whole blood mRNA from 36 cattle (2015: n = 9; 2017: n = 27) across three time points (n = 100 samples; days [D]0, D28, and D63) were processed through ARS-UCD1.2 reference-guided assembly (HISAT2/Stringtie2). Samples were categorized into BRD-severity cohorts (Healthy, n = 14; Treated 1, n = 11; Treated 2+, n = 11) via frequency of antimicrobial clinical treatment. Assessment of gene expression patterns over time within each BRD cohort was modeled through an autoregressive hidden Markov model (EBSeq-HMM; posterior probability ≥ 0.5, FDR < 0.01). Mixed-effects negative binomial models (glmmSeq; FDR < 0.05) and edgeR (FDR < 0.10) identified differentially expressed genes between and across cohorts overtime. A total of 2,580, 2,216, and 2,381 genes were dynamically expressed across time in Healthy, Treated 1, and Treated 2+ cattle, respectively. Genes involved in the production of specialized resolving mediators (SPMs) decreased at D28 and then increased by D63 across all three cohorts. Accordingly, SPM production and alternative complement were differentially expressed between Healthy and Treated 2+ at D0, but not statistically different between the three groups by D63. Magnitude, but not directionality, of gene expression related to SPM production, alternative complement, and innate immune response signified Healthy and Treated 2+ cattle. Differences in gene expression at D63 across the three groups were related to oxygen binding and carrier activity, natural killer cell-mediated cytotoxicity, cathelicidin production, and neutrophil degranulation, possibly indicating prolonged airway pathology and inflammation weeks after clinical treatment for BRD. These findings indicate genomic mechanisms indicative of BRD development and severity over time.

Identification of DNA methylation markers for age and Bovine Respiratory Disease in dairy cattle: A pilot study based on Reduced Representation Bisulfite Sequencing.

Methylation profiles of animals are known to differ by age and disease status. Bovine respiratory disease (BRD), a complex infectious disease, primarily affects calves and has significant impact on animal welfare and the cattle industry, due to production losses, increased veterinary costs as well as animal losses. BRD susceptibility is multifactorial, influenced by both environmental and genetic factors. We have performed a pilot study to investigate the epigenetic profile of BRD susceptibility in six calves (three healthy versus three diagnosed with BRD) and age-related methylation differences between healthy calves and adult dairy cows (three calves versus four adult cows) using Reduced Representation Bisulfite Sequencing (RRBS). We identified 2537 genes within differentially methylated regions between calves and adults. Functional analysis revealed enrichment of developmental pathways including cell fate commitment and tissue morphogenesis. Between healthy and BRD affected calves, 964 genes were identified within differentially methylated regions. Immune and vasculature regulatory pathways were enriched and key candidates in BRD susceptibility involved in complement cascade regulation, vasoconstriction and respiratory cilia structure and function were identified. Further studies with a greater sample size are needed to validate these findings and formulate integration into breeding programmes aiming to increase animal longevity and disease resistance.

Genomic estimated breeding values for bovine respiratory disease resistance in Angus feedlot cattle.

Bovine respiratory disease (BRD) causes major losses in feedlot cattle worldwide. A genetic component for BRD resistance in feedlot cattle and calves has been reported in a number of studies, with heritabilities ranging from 0.04 to 0.2. These results suggest selection could be used to reduce the incidence of BRD. Genomic selection could be an attractive approach for breeding for BRD resistance, given the phenotype is not likely to be recorded on breeding animals. In this study, we derived GEBVs for BRD resistance and assessed their accuracy in a reasonably large data set recorded for feedlot treatment of BRD (1213 Angus steers, in two feedlots). In fivefold cross validation, genomic predictions were moderately accurate (0.23 ±â€…0.01) when a BayesR approach was used. Expansion of this approach to include more animals and a diversity of breeds is recommended to successfully develop a GEBV for BRD resistance in feedlots for the beef industry.

Bovine respiratory disease (BRD) is the major cause of losses in feedlot cattle worldwide. Previous studies have demonstrated that there is a genetic component to resistance to BRD, suggesting that this trait could be improved by selection. Genomic selection, whereby genome wide DNA markers capture most of the genetic variation from the trait, would enable identification of resistant animals early in life through DNA testing, accelerating genetic gains. In this study, we have demonstrated a panel of 50k DNA markers can be used to predict BRD resistance with reasonable accuracy in Angus cattle, enabling early selection for BRD resistance in this breed.

Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain.

Bovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development. Gene expression counts of previously published RNA-Seq data from 23 cattle (2017; n = 11 Healthy, n = 12 BRD) were used to construct gene co-expression modules and correlation patterns with complete blood count (CBC) and clinical datasets. Modules were further evaluated for cross-populational preservation of expression with RNA-Seq data from 24 cattle in an independent population (2019; n = 12 Healthy, n = 12 BRD). Genes within well-preserved modules were subject to functional enrichment analysis for significant Gene Ontology terms and pathways. Genes which possessed high module membership and association with BRD development, regardless of module preservation ("hub genes"), were utilized for protein-protein physical interaction network and clustering analyses. Five well-preserved modules of co-expressed genes were identified. One module ("steelblue"), involved in alpha-beta T-cell complexes and Th2-type immunity, possessed significant correlation with increased erythrocytes, platelets, and BRD development. One module ("purple"), involved in mitochondrial metabolism and rRNA maturation, possessed significant correlation with increased eosinophils, fecal egg count per gram, and weight gain over time. Fifty-two interacting hub genes, stratified into 11 clusters, may possess transient function involved in BRD development not previously described in literature. This study identifies co-expressed genes and coordinated mechanisms associated with BRD, which necessitates further investigation in BRD-prediction research.

Association of single nucleotide polymorphisms in the ANKRA2 and CD180 genes with bovine respiratory disease and presence of Mycobacterium avium subsp. paratuberculosis(1).

The objective was to determine whether single nucleotide polymorphisms (SNPs) in the ANKRA2 and CD180 genes are associated with incidence of bovine respiratory disease (BRD) and presence of Mycobacterium avium subsp. paratuberculosis (MAP) in cattle. Two independent populations were used. The first population (BRD-affected; N = 90) was composed of 31 half-sib progeny, from a Brahman × Angus sire, that were treated for BRD. Untreated offspring from the sire were selected to serve as controls. The second population (MAP-infected) of 330 animals of unknown parentage was evaluated for the presence of MAP in ileocecal lymph node and classified as positive or negative. Markers in both genes were assessed for association in these two populations. In the BRD-affected population, five SNPs in the ANKRA2 gene were significantly associated (P < 0.05), and two SNPs were highly associated (P < 0.01) with incidence of BRD. In addition, two SNPs in the CD180 gene were found to be associated with this trait. In the MAP-infected population, one SNP in the ANKRA2 gene was significantly associated (P < 0.05) with the presence or absence of MAP, and a SNP in the CD180 gene was highly associated (P < 0.01) with the trait. Haplotypes, using significant markers, showed a positive association with both incidence of BRD (P = 0.0001) and with the presence of MAP (P = 0.0032). Markers in the ANKRA2 and CD180 genes are associated with the ability of the animal to cope with pathogens.

Short communication: genetic parameters for measures of calf health in a population of Holstein calves in New York State.

The objectives of this study were to estimate the genetic parameters of preweaning undifferentiated bovine respiratory disease (BRD), umbilical diseases (UMB), and bloat (BLT) for a population of Holstein calves from New York State, as well as to associate the estimated breeding values determined in the current study with traits from ongoing genetic evaluations used in Canada and the United States. Data were recorded for 7,372 heifer calves at a commercial rearing facility in New York State, from arrival at 1 to 7d of age for the duration of stay at the facility. Performance and disease up to weaning and mortality before and after weaning were recorded. The 3 traits of interest, BRD, UMB, and BLT, were scored as 0 or 1 and analyzed using a multivariate linear sire model. The model included fixed effects of arrival weight, serum total protein, weaning weight, and season and year of birth; herd and sire were included as random effects. The heritabilities of the 3 health traits of interest were estimated at 0.09 for BRD, 0.14 for UMB, and 0.04 for BLT. The genetic correlation between the calf health traits BRD and BLT was 0.62. Correlations between BRD and UMB and between BLT and UMB were close to zero. Breeding values were estimated for the 3 calf health traits and correlated with routinely evaluated traits from Canadian and US genetic evaluations (correlations ranged from -0.42 to 0.32). Significant differences existed among Holstein sires for calf health during the preweaning period.

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology.

Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms. Our objective was to apply ML models to lung and immunological tissue datasets acquired from previous clinical BRD experiments to identify genes that classify disease with high accuracy. Raw mRNA sequencing reads from 151 bovine datasets (n = 123 BRD, n = 28 control) were downloaded from NCBI-GEO. Quality filtered reads were assembled in a HISAT2/Stringtie2 pipeline. Raw gene counts for ML analysis were normalized, transformed, and analyzed with MLSeq, utilizing six ML models. Cross-validation parameters (fivefold, repeated 10 times) were applied to 70% of the compiled datasets for ML model training and parameter tuning; optimized ML models were tested with the remaining 30%. Downstream analysis of significant genes identified by the top ML models, based on classification accuracy for each etiological association, was performed within WebGestalt and Reactome (FDR ≤ 0.05). Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation models identified 154 and 195 significant genes for IBR and BRSV, respectively; from these genes, the two ML models discriminated IBR and BRSV with 100% accuracy compared to sham controls. Significant genes classified by the top ML models in IBR (154) and BRSV (195), but not BVDV (74), were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not homogenized lung tissue. Genes identified in Mannheimia haemolytica infections (97) were involved in activating classical and alternative pathways of complement. Novel findings, including expression of genes related to reduced mitochondrial oxygenation and ATP synthesis in consolidated lung tissue, were discovered. Genes identified in each analysis represent distinct genomic events relevant to understanding and predicting clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support the prediction and understanding of clinical BRD.

The epidemiology of bovine respiratory disease: What is the evidence for predisposing factors?

Bovine respiratory disease (BRD) is the most costly disease of beef cattle in North America. It is multi-factorial, with a variety of physical and physiological stressors combining to predispose cattle to pneumonia. However, efforts to discern which factors are most important have frequently failed to establish definitive answers. Calves are at highest risk shortly after transport. Risk factors include purchasing from sale barns and commingling. It is unclear whether or not these practices increase susceptibility, increase exposure, or are proxies for poor management. Lighter-weight calves appear to be at greater risk, although this has not been consistent. Persistent infection (PI) with bovine virus diarrhea virus increases BRD occurrence, but it is unclear if PI calves affect other cattle in the feedlot. The complexity of BRD has made it difficult to define involvement of individual factors. Stressors may play a role as "necessary but not sufficient" components, requiring additive effects to cause disease.

Improving resistance of cattle to BRD through genomics.

Bovine respiratory disease (BRD) is of considerable economic importance to the dairy industry, specifically among young animals. Several studies have demonstrated that BRD has a significant genetic component, with heritabilities ranging from 0.04 up to 0.22, which could be utilized to select more resistant animals. Taking advantage of available genomic data will allow more accurate genetic predictions to be made earlier in an animal's life. The availability of genomic data does not negate the necessity of quality phenotypes, in this case, records of BRD incidence. Evidence has shown that genetic selection is possible through the use of producer-recorded health information. The national dairy cooperator database currently has minimal records on respiratory problems. There is an existing pipeline for these data to flow from events recorded by producers on the farm to the national database used for genetic evaluation. Additional data could also be collected through the expansion of currently utilized termination codes and used in conjunction with the records of direct health events. Selection for animals with improved BRD resistance is possible at the national level; however, collection of additional phenotypes remains a significant hurdle.

Genomics: the host's genotype and its relevance to bovine respiratory disease.

Genomic variation exists in cattle that affects their susceptibility to the complex of pathogens responsible for bovine respiratory disease (BRD). Heritability estimates and genome-wide association analyses (GWAA) support the role of host genomic variation in BRD susceptibility. Heritability estimates for BRD susceptibility range from 0.02 to 0.29 depending on the population, the definition of the disease, and the accuracy of diagnosis. GWAA have identified genomic regions (loci) associated with BRD in beef and dairy cattle based on a variety of BRD diagnostic criteria. National standards need to be developed for BRD diagnostics and reporting to facilitate selection. Commercial genotyping is available to predict BRD susceptibility in dairy cattle and for the selection of replacement animals. Disease pathogen profiles vary by region and can result in genetic heterogeneity where different loci are important for susceptibility to different BRD pathogens. Although the identification of the BRD pathogens may not be critical for treatment, it is of paramount importance in identifying loci that render cattle susceptible to the disease. Identification of loci associated with host susceptibility to BRD provides a foundation for genomic selection to reduce disease and opens the possibilities to a better understanding of how the host defends itself.

Bovine Respiratory Disease Diagnosis: What Progress Has Been Made in Infectious Diagnosis?

When it is desired to identify infectious agents involved in an outbreak of bovine respiratory disease, a variety of possible sampling methods may be used. For field use, the deep nasopharyngeal swab, transtracheal wash, and nonendoscopic bronchoalveolar lavage are most feasible. At present, bacterial culture and polymerase chain reaction testing are most commonly used to identify infectious agents. Interpretation of test results can be challenging, particularly for opportunistic pathogens. Evidence-based guidelines for precise interpretation of microbiologic tests results are lacking; however, approaches that have been practically useful for the management of bovine respiratory disease outbreaks are presented.

Respiratory function in cattle: impact of breed, heritability and external factors.

Bovine respiratory disease complex (BRDC) is the most common and costly disease of cattle. The important prevalence of this multifactorial syndrome results from interactions between different pathogens, physical constitution of the host and environmental factors. Because of the strong economical impact of BRDC, it is recommended to complete classical preventive and therapeutic measures by selection of heritable traits improving resistance against respiratory disease and by alternatives based on improved control of environmental factors. The transport of oxygen between the atmospheric air and the mitochondria essentially includes four steps, i.e. (1) respiratory function, including pulmonary ventilation, perfusion and respiratory mechanics, (2) blood circulation and oxygen transport, (3) capillary-cell diffusion and (4) oxygen combustion by mitochondria. Each step should be considered when factors improving resistance against respiratory disease are investigated. This review aims (1) to summarise briefly the anatomical, histological and physiological peculiarities of the bovine respiratory system and (2) to consider the effect of breed, heritability and external factors at each step of the oxygen transport chain, by focussing essentially on respiratory function.

Feedlot entry characteristics and climate: their relationship with cattle growth rate, bovine respiratory disease and mortality.

OBJECTIVE: To examine the relationship between the feedlot entry characteristics of breed, gender, entry weight and the presence or absence of permanent incisors, with growth rate, the incidence of bovine respiratory disease (BRD), and mortalities of cattle destined for the Australian domestic market. The relationship between climate data and the occurrence of BRD was also investigated. DESIGN: Two thousand four hundred and sixty eight cattle were individually identified at feedlot entry, and lot number, body weight, property identification code, breed, gender, and the presence or absence of permanent incisors were recorded for each animal. Daily climate data were collected for the duration of the experiment. Univariate correlations, multivariate analysis and survival analysis techniques were used to examine the relationship between these feedlot entry characteristics and the outcomes of BRD and growth rate. RESULTS: The feedlot entry description of breed had a significant effect on average daily gain. The presence of permanent incisors at feedlot entry was associated with an increase in average daily gain of 0.1 kg/animal/d. Growth rate decreased by 0.702 kg/animal/d in cattle treated for BRD and by 0.302 kg/animal/d in cattle identified with anorexia. Treatment for BRD was ten times more likely with Hereford cattle. There was a moderate correlation between minimum daily temperature and the occurrence of BRD. CONCLUSIONS: This study indicates that breed can affect growth rate and health, specifically the occurrence of BRD, in Australian domestic feedlot cattle. The moderate correlation between minimum daily temperature and the occurrence of BRD indicates potential associations between climate and BRD incidence in Australian feedlots.