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.

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.

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.

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.

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.

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.

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.

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.

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.

The upper respiratory tract microbiome and its potential role in bovine respiratory disease and otitis media.

The upper respiratory tract (URT) hosts a complex microbial community of commensal microorganisms and potential pathogens. Analyzing the composition and nature of the healthy URT microbiota and how it changes over time will contribute to a better understanding of the pathogenesis of pneumonia and otitis. A longitudinal study was conducted including 174 Holstein calves that were divided in four groups: healthy calves, calves diagnosed with pneumonia, otitis or both diseases. Deep pharyngeal swabs were collected on days 3, 14, 28, and 35 of life, and next-generation sequencing of the 16S rRNA gene as well as quantitative PCR was performed. The URT of Holstein dairy calves aged 3 to 35 days revealed to host a highly diverse bacterial community. The relative abundances of the bacterial genera Mannheimia, Moraxella, and Mycoplasma were significantly higher in diseased versus healthy animals, and the total bacterial load of newborn calves at day 3 was higher for animals that developed pneumonia than for healthy animals. Our results corroborate the existing knowledge that species of Mannheimia and Mycoplasma are important pathogens in pneumonia and otitis. Furthermore, they suggest that species of Moraxella can potentially cause the same disorders (pneumonia and otitis), and that high neonatal bacterial load is a key contributor to the development of pneumonia.

Associations between animal characteristic and environmental risk factors and bovine respiratory disease in Australian feedlot cattle.

A prospective longitudinal study was conducted in a population of Australian feedlot cattle to assess associations between animal characteristic and environmental risk factors and risk of bovine respiratory disease (BRD). Animal characteristics were recorded at induction, when animals were individually identified and enrolled into study cohorts (comprising animals in a feedlot pen). Environmental risk factors included the year and season of induction, source region and feedlot region and summary variables describing weather during the first week of follow-up. In total, 35,131 animals inducted into 170 cohorts within 14 feedlots were included in statistical analyses. Causal diagrams were used to inform model building and multilevel mixed effects logistic regression models were fitted within the Bayesian framework. Breed, induction weight and season of induction were significantly and strongly associated with risk of BRD. Compared to Angus cattle, Herefords were at markedly increased risk (OR: 2.0, 95% credible interval: 1.5-2.6) and tropically adapted breeds and their crosses were at markedly reduced risk (OR: 0.5, 95% credible interval: 0.3-0.7) of developing BRD. Risk of BRD declined with increased induction weight, with cattle in the heaviest weight category (≥480kg) at moderately reduced risk compared to cattle weighing <400kg at induction (OR: 0.6, 95% credible interval: 0.5-0.7). Animals inducted into feedlots during summer (OR: 2.4, 95% credible interval: 1.4-3.8) and autumn (OR: 2.1, 95% credible interval: 1.2-3.2) were at markedly increased risk compared to animals inducted during spring. Knowledge of these risk factors may be useful in predicting BRD risk for incoming groups of cattle in Australian feedlots. This would then provide the opportunity for feedlot managers to tailor management strategies for specific subsets of animals according to predicted BRD risk.

Rapid Communication: Variance component estimates for Charolais-sired fed cattle and relative economic impact of bovine respiratory disease.

Variance components were estimated and relative economic importance of bovine respiratory disease (BRD) was derived from 3 yr of performance, morbidity, and mortality data collected from a single beef cattle finishing operation. One thousand one hundred eighty nine of 12,812 Charolais-sired calves were treated for BRD during the finishing period. Weaning weight (WW), DMI, days to harvest (D2H), HCW, yield grade (YG), and marbling score determined by image analysis (MARB) were collected to quantify the economic impact associated with treatment for BRD. Observed means and (co)variances for carcass and production traits were used to simulate populations of 10,000 healthy and 10,000 BRD treated calves. A bio-economic model was developed to derive the economic value associated with the incidence and number of treatments for BRD during the finishing period. Carcasses from healthy calves were worth $58.28 more on average compared to calves treated at least once for BRD. Heritability estimates for BRD were 0.15 when the trait was measured as number of treatments (0 to 4), and 0.14 when measured as incidence (0 or 1). The model indicated that D2H had the lowest relative economic importance in this system, with a cost of $1.91 per head for each additional day on feed. Furthermore, the relative economic value of BRD morbidity was approximately 10.65 greater than D2H when recording the BRD phenotype as the number of BRD treatments. The economic values of HCW, WW, and DMI were 11.47, 5.15, and 3.61 times more important than D2H, respectively. This indicates BRD morbidity has the second greatest relative economic value in this system, with a one percent increase in morbidity associated with an average loss of $2.08 per head. These results indicate that BRD morbidity can have an equal or greater economic importance when compared to carcass and production traits during the finishing period. Further, this indicates the opportunity exists to increase the genetic merit for profitability during the finishing period by incorporating BRD incidence into terminal-sire selection indexes.

Genomewide association study of lung lesions in cattle using sample pooling.

Bovine respiratory disease complex (BRDC) is the most expensive disease in beef cattle in the United States costing the industry at least US$1 billion annually. Bovine respiratory disease complex causes damage to lung tissue resulting in persistent lung lesions observable at slaughter. Severe lung lesions at harvest have been associated with decreased preharvest ADG and increased clinical BRDC in the feedlot. Our objective was to identify SNP that are associated with severe lung lesions observed at harvest in feedlot cattle. We conducted a genomewide association study (GWAS) using a case-control design for severe lung lesions in fed cattle at slaughter using the Illumina Bovine HD array (approximately 770,000 SNP) and sample pooling. Lung samples were collected from 11,520 young cattle, a portion of which had not been treated with antibiotics (participating in a "natural" marketing program), at a large, commercial beef processing plant in central Nebraska. Lung samples with lesions (cases) and healthy lungs (controls) were collected when both phenotypes were in close proximity on the viscera (offal) table. We constructed 60 case and 60 control pools with 96 animals per pool. Pools were constructed by sampling sequence to ensure that case and control pool pairs were matched by proximity on the processing line. The Bovine HD array (770,000 SNP) was run on all pools. Fourteen SNP on BTA 2, 3, 4, 9, 11, 14, 15, 22, 24, and 25 were significant at the genomewide experiment-wise error rate of 5% ( ≤ 1.49 × 10). Eighty-five SNP on 28 chromosomes achieved a false discovery rate of 5% ( ≤ 5.38 × 10). Significant SNP were near (±100 kb) genes involved in tissue repair and regeneration, tumor suppression, cell proliferation, apoptosis, control of organ size, and immunity. Based on 85 significantly associated SNP in or near a collection of genes with diverse function on 28 chromosomes, we conclude that the genomic footprint of lung lesions is complex. A complex genomic footprint (genes and regulatory elements that affect the trait) is consistent with what is known about the cause of the disease: complex interactions among multiple viral and bacterial pathogens along with several environmental factors including dust, commingling, transportation, and stress. Characterization of sequence variation near significant SNP will enable accurate and cost effective genome-enhanced genetic evaluations for BRDC resistance in AI bulls and seed stock populations.

Genetics of bovine respiratory disease in cattle: can breeding programs reduce the problem?

Genetics is responsible for approximately half the observed change in performance internationally in well-structured cattle breeding programs. Almost all, if not all, individual characteristics, including animal health, have a genetic basis. Once genetic variation exists then breeding for improvement is possible. Although the heritability of most health traits is low to moderate, considerable exploitable genetic variation does exist. From the limited studies undertaken, and mostly from limited datasets, the direct heritability of susceptibility to BRD varied from 0.07 to 0.22 and the maternal heritability (where estimated) varied from 0.05 to 0.07. Nonetheless, considerable genetic variation clearly exists; the genetic standard deviation for the direct component (binary trait), although differing across populations, varied from 0.08 to 0.20 while the genetic standard deviation for the maternal component varied from 0.04 to 0.07. Little is known about the genetic correlation between genetic predisposition to BRD and animal performance; the estimation of these correlations should be prioritized. (Long-term) Breeding strategies to reduce the incidence of BRD in cattle should be incorporated into national BRD eradication or control strategies.

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.

Results of the BRD CAP project: progress toward identifying genetic markers associated with BRD susceptibility.

The Bovine Respiratory Disease Coordinated Agricultural Project (BRD CAP) is a 5-year project funded by the United States Department of Agriculture (USDA), with an overriding objective to use the tools of modern genomics to identify cattle that are less susceptible to BRD. To do this, two large genome wide association studies (GWAS) were conducted using a case:control design on preweaned Holstein dairy heifers and beef feedlot cattle. A health scoring system was used to identify BRD cases and controls. Heritability estimates for BRD susceptibility ranged from 19 to 21% in dairy calves to 29.2% in beef cattle when using numerical scores as a semi-quantitative definition of BRD. A GWAS analysis conducted on the dairy calf data showed that single nucleotide polymorphism (SNP) effects explained 20% of the variation in BRD incidence and 17-20% of the variation in clinical signs. These results represent a preliminary analysis of ongoing work to identify loci associated with BRD. Future work includes validation of the chromosomal regions and SNPs that have been identified as important for BRD susceptibility, fine mapping of chromosomes to identify causal SNPs, and integration of predictive markers for BRD susceptibility into genetic tests and national cattle genetic evaluations.

Pathogen variation across time and space: sequencing to characterize Mannheimia haemolytica diversity.

Bovine respiratory disease complex (BRDC) is a major animal health and economic issue that affects cattle industries worldwide. Within the USA, the beef cattle industry loses up to an estimated 1 billion dollars a year due to BRDC. There are many contributors to BRDC, including environmental stressors and viral and/or bacterial infections. One species of bacteria in particular, Mannheimia haemolytica, is recognized as the major cause of severe fibrinonecrotic pneumonia in cattle. M. haemolytica is an opportunistic pathogen that normally populates the upper respiratory tract of cattle, and invades the lower respiratory tract in stressed and/or virally infected cattle by mechanisms that are not completely understood. However, not all M. haemolytica appear to be equally pathogenic to cattle. Thus, a test could be developed to distinguish M. haemolytica genetic subtypes by their propensity to cause respiratory disease, allowing isolation and/or treatment of cattle harboring strains with an increased propensity to cause disease. To that end, the genomes of over 300 M. haemolytica strains are being sequenced.