Genomic prediction for tuberculosis resistance in dairy cattle

Genome-Wide Association Study Reveals Quantitative Trait Loci and Candidate Genes Associated with High Interferon-gamma Production in Holstein Cattle Naturally Infected with Mycobacterium Bovis

Mycobacterium bovis (Mb) is the causative agent of bovine tuberculosis (bTb). Genetic selection aiming to identify less susceptible animals has been proposed as a complementary measure in ongoing programs toward controlling Mb infection. However, individual animal phenotypes for bTb based on interferon-gamma (IFNɣ) and its use in bovine selective breeding programs have not been explored. In the current study, IFNɣ production was measured using a specific IFNɣ ELISA kit in bovine purified protein derivative (bPPD)-stimulated blood samples collected from Holstein cattle. DNA isolated from the peripheral blood samples collected from the animals included in the study was genotyped with the EuroG Medium Density bead Chip, and the genotypes were imputed to whole-genome sequences. A genome-wide association analysis (GWAS) revealed that the IFNɣ in response to bPPD was associated with a specific genetic profile (heritability = 0.23) and allowed the identification of 163 SNPs, 72 quantitative trait loci (QTLs), 197 candidate genes, and 8 microRNAs (miRNAs) associated with this phenotype. No negative correlations between this phenotype and other phenotypes and traits included in the Spanish breeding program were observed. Taken together, our results define a heritable and distinct immunogenetic profile associated with strong production of IFNɣ in response to Mb.

Selective breeding can contribute to bovine tuberculosis control and eradication

Bovine tuberculosis (bTB) persists in many countries having a significant impact on public health and livestock industry finances. The incidence and prevalence of new cases in parts of the UK and elsewhere over the past decades warrant intensified efforts towards achieving Officially Tuberculosis Free (OTF) status in the respective regions. Genetic selection aiming to identify and remove inherently susceptible animals from breeding has been proposed as an additional measure in ongoing programmes towards controlling the disease. The presence of genetic variation among individual animals in their capacity to respond to Mycobacterium bovis exposure has been documented and heritability estimates of 0.06-0.18 have been reported. Despite their moderate magnitude, these estimates suggest that host resistance to bTB is amenable to improvement with selective breeding. Although relatively slow, genetic progress can be constant, cumulative and permanent, thereby complementing ongoing disease control measures. Importantly, mostly no antagonistic genetic correlations have been found between bTB resistance and other animal traits suggesting that carefully incorporating the former in breeding decisions should not adversely affect bovine productivity. Simulation studies have demonstrated the potential impact of genetic selection on reducing the probability of a breakdown to occur or the duration and severity of a breakdown that has already been declared. Furthermore, research on the bovine genome has identified multiple genomic markers and genes associated with bTB resistance. Nevertheless, the combined outcomes of these studies suggest that host resistance to bTB is a complex, polygenic trait, with no single gene alone explaining the inherent differences between resistant and susceptible animals. Such results support the development of accurate genomic breeding values that duly capture the collective effect of multiple genes to underpin selective breeding programmes. In addition to improving host resistance to bTB, scientists and practitioners have considered the possibility of reducing host infectivity. Ongoing studies have suggested the presence of genetic variation for infectivity and confirmed that bTB eradication would be accelerated if selective breeding considered both host resistance and infectivity traits. In conclusion, research activity on bTB genetics has generated knowledge and insights to support selective breeding as an additional measure towards controlling and eradicating the disease.

Expanding the application of haplotype-based genomic predictions to the wild: A case of antibody response against Teladorsagia circumcincta in Soay sheep

BACKGROUND

Genomic prediction of breeding values (GP) has been adopted in evolutionary genomic studies to uncover microevolutionary processes of wild populations or improve captive breeding strategies. While recent evolutionary studies applied GP with individual single nucleotide polymorphism (SNP), haplotype-based GP could outperform individual SNP predictions through better capturing the linkage disequilibrium (LD) between the SNP and quantitative trait loci (QTL). This study aimed to evaluate the accuracy and bias of haplotype-based GP of immunoglobulin (Ig) A (IgA), IgE, and IgG against Teladorsagia circumcincta in lambs of an unmanaged sheep population (Soay breed) based on Genomic Best Linear Unbiased Prediction (GBLUP) and five Bayesian [BayesA, BayesB, BayesCπ, Bayesian Lasso (BayesL), and BayesR] methods.

RESULTS

The accuracy and bias of GPs using SNP, haplotypic pseudo-SNP from blocks with different LD thresholds (0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.00), or the combinations of pseudo-SNPs and non-LD clustered SNPs were obtained. Across methods and marker sets, higher ranges of genomic estimated breeding values (GEBV) accuracies were observed for IgA (0.20 to 0.49), followed by IgE (0.08 to 0.20) and IgG (0.05 to 0.14). Considering the methods evaluated, up to 8% gains in GP accuracy of IgG were achieved using pseudo-SNPs compared to SNPs. Up to 3% gain in GP accuracy for IgA was also obtained using the combinations of the pseudo-SNPs with non-clustered SNPs in comparison to fitting individual SNP. No improvement in GP accuracy of IgE was observed using haplotypic pseudo-SNPs or their combination with non-clustered SNPs compared to individual SNP. Bayesian methods outperformed GBLUP for all traits. Most scenarios yielded lower accuracies for all traits with an increased LD threshold. GP models using haplotypic pseudo-SNPs predicted less-biased GEBVs mainly for IgG. For this trait, lower bias was observed with higher LD thresholds, whereas no distinct trend was observed for other traits with changes in LD.

CONCLUSIONS

Haplotype information improves GP performance of anti-helminthic antibody traits of IgA and IgG compared to fitting individual SNP. The observed gains in the predictive performances indicate that haplotype-based methods could benefit GP of some traits in wild animal populations.

Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches

The efficiency of genomic selection strongly depends on the prediction accuracy of the genetic merit of candidates. Numerous papers have shown that the composition of the calibration set is a key contributor to prediction accuracy. A poorly defined calibration set can result in low accuracies, whereas an optimized one can considerably increase accuracy compared to random sampling, for a same size. Alternatively, optimizing the calibration set can be a way of decreasing the costs of phenotyping by enabling similar levels of accuracy compared to random sampling but with fewer phenotypic units. We present here the different factors that have to be considered when designing a calibration set, and review the different criteria proposed in the literature. We classified these criteria into two groups: model-free criteria based on relatedness, and criteria derived from the linear mixed model. We introduce criteria targeting specific prediction objectives including the prediction of highly diverse panels, biparental families, or hybrids. We also review different ways of updating the calibration set, and different procedures for optimizing phenotyping experimental designs.

Host Serum Proteins as Potential Biomarkers of Bovine Tuberculosis Resistance Phenotype

Eradication of bovine tuberculosis (bTB) continues to be a worldwide challenge. The lack of reliable vaccines dampens the control and eradication programs of Mycobacterium bovis infection and spread. Selection and breeding of cattle resistant to M. bovis infection would greatly enhance the effectiveness of bTB eradication programs. Here, we have evaluated the potential of serum proteins as biomarkers of cattle resistance to bTB in Holstein-Friesian cows, 6-8-year-old, born and raised in similar conditions in herds with bTB prevalence >30%. Serum proteins obtained from uninfected cows (bTB-resistant; R) were compared to those from infected cows (bTB-susceptible; S), defined by a negative or positive bTB diagnosis, respectively. bTB diagnosis included: (i) single intradermal (caudal fold) tuberculin test, (ii) whole blood IFN-gamma test, (iii) gross visible lesions in lymph nodes and lungs by inspection at the abattoir, and (iv) a bacteriological culture for M. bovis. Using 2D-GE and LC-ESI-MS/MS, we found higher expression levels of primary amine oxidase (AO), complement component 5 (C5), and serotransferrin (TF) in R cattle than S cattle. In-house developed and standardized ELISAs for these novel biomarkers showed the best sensitivities of 72, 77, 77%, and specificities of 94, 94, 83%, for AO, C5, and TF, respectively. AUC-ROC (95% CI) values of 0.8935 (0.7906-0.9964), 0.9290 (0.8484-1.010), and 0.8580 (0.7291-0.9869) were obtained at cut-off points of 192.0, 176.5 ng/ml, and 2.1 mg/ml for AO, C5, and TF, respectively. These proteins are involved in inflammatory/immunomodulatory responses to infections and may provide a novel avenue of research to determine the mechanisms of protection against bTB. Overall, our results indicate that these proteins could be novel biomarkers to help identify cattle resistant to bTB, which in turn could be used to strengthen the effectiveness of existing eradication programs against bTB.

Genetic Diversity of Cameroon Cattle and a Putative Genomic Map for Resistance to Bovine Tuberculosis

Bovine Tuberculosis (bTB) caused by Mycobacterium bovis is a livestock disease of global economic and public health importance. There are currently no effective vaccines available for livestock and so control relies on animal level surveillance and pasteurization of dairy products. A new alternative control approach is to exploit the genetic variability of the host; recent studies have demonstrated that breeding European taurine cattle, such as Holsteins for increased resistance to bTB is feasible. The utility of such an approach is still unknown for African cattle populations. This study aims to assess genetic variation in bTB resistance and the underlying genomic architecture of cattle in Cameroon. We conducted a cross-sectional study of 2,346 slaughter cattle in Cameroon. Retropharyngeal lymph node samples were collected and cultured on Lowenstein Jensen media and the BACTEC MGIT 960 system, and M. bovis was identified using the Hain® Genotype kits. A total of 153 cattle were positive for M. bovis and were archived along with a random selection of negative samples. In this study, we genotyped archived samples from 212 cattle. Their genomic diversity was characterized using PCA, hierarchical clustering and admixture analysis. We assessed genetic variation in bTB resistance using heritability analysis and compared quantitative trait loci. Previous research on this study population have shown that Fulani cattle are more susceptible to bTB than mixed breeds. However, here we show that these apparent phenotypic differences in breeds are not reflected by clear genomic differences. At the genetic level, both the Fulani and mixed cattle show similar patterns of admixture with evidence of both taurine and indicine ancestry. There was little European taurine introgression within the studied population. Hierarchical clustering showed clusters of cattle that differed in their susceptibility to bTB. Our findings allude to bTB resistance being polygenic in nature. This study highlights the potential for genetic control of bTB in Africa and the need for further research into the genetics of bTB resistance within African cattle populations.

Characterization of potential superspreader farms for bovine tuberculosis: A review

Background

Variation in host attributes that influence their contact rates and infectiousness can lead some individuals to make disproportionate contributions to the spread of infections. Understanding the roles of such ‘superspreaders’ can be crucial in deciding where to direct disease surveillance and controls to greatest effect. In the epidemiology of bovine tuberculosis (bTB) in Great Britain, it has been suggested that a minority of cattle farms or herds might make disproportionate contributions to the spread of Mycobacterium bovis, and hence might be considered ‘superspreader farms’.

Objectives and Methods

We review the literature to identify the characteristics of farms that have the potential to contribute to exceptional values in the three main components of the farm reproductive number ‐ R_f: contact rate, infectiousness and duration of infectiousness, and therefore might characterize potential superspreader farms for bovine tuberculosis in Great Britain.

Results

Farms exhibit marked heterogeneity in contact rates arising from between‐farm trading of cattle. A minority of farms act as trading hubs that greatly augment connections within cattle trading networks. Herd infectiousness might be increased by high within‐herd transmission or the presence of supershedding individuals, or infectiousness might be prolonged due to undetected infections or by repeated local transmission, via wildlife or fomites.

Conclusions

Targeting control methods on putative superspreader farms might yield disproportionate benefits in controlling endemic bovine tuberculosis in Great Britain. However, real‐time identification of any such farms, and integration of controls with industry practices, present analytical, operational and policy challenges.

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning

Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and protein concentration, and is also a robust predictor of several other economically important traits including individual fatty acids and body energy. This study predicted bTB status of UK dairy cows using their MIR spectral profiles collected as part of routine milk recording. Bovine tuberculosis data were collected as part of the national bTB testing program for Scotland, England, and Wales; these data provided information from over 40,500 bTB herd breakdowns. Corresponding individual cow life-history data were also available and provided information on births, movements, and deaths of all cows in the study. Data relating to single intradermal comparative cervical tuberculin (SICCT) skin-test results, culture, slaughter status, and presence of lesions were combined to create a binary bTB phenotype labeled 0 to represent nonresponders (i.e., healthy cows) and 1 to represent responders (i.e., bTB-affected cows). Contemporaneous individual milk MIR spectral data were collected as part of monthly routine milk recording and matched to bTB status of individual animals on the single intradermal comparative cervical tuberculin test date (±15 d). Deep learning, a sub-branch of machine learning, was used to train artificial neural networks and develop a prediction pipeline for subsequent use in national herds as part of routine milk recording. Spectra were first converted to 53 × 20-pixel PNG images, then used to train a deep convolutional neural network. Deep convolutional neural networks resulted in a bTB prediction accuracy (i.e., the number of correct predictions divided by the total number of predictions) of 71% after training for 278 epochs. This was accompanied by both a low validation loss (0.71) and moderate sensitivity and specificity (0.79 and 0.65, respectively). To balance data in each class, additional training data were synthesized using the synthetic minority over sampling technique. Accuracy was further increased to 95% (after 295 epochs), with corresponding validation loss minimized (0.26), when synthesized data were included during training of the network. Sensitivity and specificity also saw a 1.22- and 1.45-fold increase to 0.96 and 0.94, respectively, when synthesized data were included during training. We believe this study to be the first of its kind to predict bTB status from milk MIR spectral data. We also believe it to be the first study to use milk MIR spectral data to predict a disease phenotype, and posit that the automated prediction of bTB status at routine milk recording could provide farmers with a robust tool that enables them to make early management decisions on potential reactor cows, and thus help slow the spread of bTB.

Accurate Genomic Predictions for Chronic Wasting Disease in U.S. White-Tailed Deer

The geographic expansion of chronic wasting disease (CWD) in U.S. white-tailed deer (Odocoileus virginianus) has been largely unabated by best management practices, diagnostic surveillance, and depopulation of positive herds. Using a custom Affymetrix Axiom single nucleotide polymorphism (SNP) array, we demonstrate that both differential susceptibility to CWD, and natural variation in disease progression, are moderately to highly heritable (h2=0.337±0.079─0.637±0.070) among farmed U.S. white-tailed deer, and that loci other than PRNP are involved. Genome-wide association analyses using 123,987 quality filtered SNPs for a geographically diverse cohort of 807 farmed U.S. white-tailed deer (n = 284 CWD positive; n = 523 CWD non-detect) confirmed the prion gene (PRNP; G96S) as a large-effect risk locus (P-value < 6.3E-11), as evidenced by the estimated proportion of phenotypic variance explained (PVE ≥ 0.05), but also demonstrated that more phenotypic variance was collectively explained by loci other than PRNP. Genomic best linear unbiased prediction (GBLUP; n = 123,987 SNPs) with k-fold cross validation (k = 3; k = 5) and random sampling (n = 50 iterations) for the same cohort of 807 farmed U.S. white-tailed deer produced mean genomic prediction accuracies ≥ 0.81; thereby providing the necessary foundation for exploring a genomically-estimated CWD eradication program.

Optimizing Low-Cost Genotyping and Imputation Strategies for Genomic Selection in Atlantic Salmon

Genomic selection enables cumulative genetic gains in key production traits such as disease resistance, playing an important role in the economic and environmental sustainability of aquaculture production. However, it requires genome-wide genetic marker data on large populations, which can be prohibitively expensive. Genotype imputation is a cost-effective method for obtaining high-density genotypes, but its value in aquaculture breeding programs which are characterized by large full-sibling families has yet to be fully assessed. The aim of this study was to optimize the use of low-density genotypes and evaluate genotype imputation strategies for cost-effective genomic prediction. Phenotypes and genotypes (78,362 SNPs) were obtained for 610 individuals from a Scottish Atlantic salmon breeding program population (Landcatch, UK) challenged with sea lice, Lepeophtheirus salmonis The genomic prediction accuracy of genomic selection was calculated using GBLUP approaches and compared across SNP panels of varying densities and composition, with and without imputation. Imputation was tested when parents were genotyped for the optimal SNP panel, and offspring were genotyped for a range of lower density imputation panels. Reducing SNP density had little impact on prediction accuracy until 5,000 SNPs, below which the accuracy dropped. Imputation accuracy increased with increasing imputation panel density. Genomic prediction accuracy when offspring were genotyped for just 200 SNPs, and parents for 5,000 SNPs, was 0.53. This accuracy was similar to the full high density and optimal density dataset, and markedly higher than using 200 SNPs without imputation. These results suggest that imputation from very low to medium density can be a cost-effective tool for genomic selection in Atlantic salmon breeding programs.

Genome-Wide Association Study in Mexican Holstein Cattle Reveals Novel Quantitative Trait Loci Regions and Confirms Mapped Loci for Resistance to Bovine Tuberculosis

Bovine tuberculosis (bTB) is a disease of cattle that represents a risk to public health and causes severe economic losses to the livestock industry. Recently, genetic studies, like genome-wide association studies (GWAS) have greatly improved the investigation of complex diseases identifying thousands of disease-associated genomic variants. Here, we present evidence of genetic variants associated with resistance to TB in Mexican dairy cattle using a case-control approach with a selective DNA pooling experimental design. A total of 154 QTLRs (quantitative trait loci regions) at 10% PFP (proportion of false positives), 42 at 5% PFP and 5 at 1% PFP have been identified, which harbored 172 annotated genes. On BTA13, five new QTLRs were identified in the MACROD2 and KIF16B genes, supporting their involvement in resistance to bTB. Six QTLRs harbor seven annotated genes that have been previously reported as involved in immune response against Mycobacterium spp: BTA (Bos taurus autosome) 1 (CD80), BTA3 (CTSS), BTA 3 (FCGR1A), BTA 23 (HFE), BTA 25 (IL21R), and BTA 29 (ANO9 and SIGIRR). We identified novel QTLRs harboring genes involved in Mycobacterium spp. immune response. This is a first screening for resistance to TB infection on Mexican dairy cattle based on a dense SNP (Single Nucleotide Polymorphism) chip.

Atypical granuloma formation in Mycobacterium bovis-infected calves

Bovine tuberculosis is a chronic inflammatory disease that causes granuloma formation. Characterization of granulomatous lesions of Mycobacterium bovis (M. bovis) experimentally infected cattle has helped to better understand the pathogenesis of this disease. However, few studies have described granulomas found in M. bovis naturally infected cattle. The aim of this work was to examine granulomas from Holstein-Friesian cattle naturally infected with M. bovis from a dairy basin located in the central region of Mexico. Tissue samples from thirty-two cattle with lesions suggestive of tuberculosis were collected post-mortem. Fifteen of the 32 sampled animals (46.8%) were 4 months of age or younger (calves), whereas the rest (53.2%, 17/32) were over one year old (adults). Macroscopic lesions suggestive of tuberculosis were found in the mediastinal lymph node chain of all animals (32/32). From the 1,143 granulomatous lesions that were microscopically analyzed, 34.6% (396/1143) were collected from adult animals and subsequently classified according to the nomenclature suggested by Wangoo et al., 2005. Surprisingly, lesions from calf tissues showed an atypical pattern which could not be fitted into the established developmental stages of this classification. Granulomatous lesions found in calves covered most of the affected organ, histologically showed large necrotic areas with central calcification, absence of a connective tissue capsule, and few giant cells. Also, there was a higher percentage of lesions with acid-fast bacilli (AFB) when compared to studied granulomas in adults. Growth of Mycobacterium spp was detected in 11 bacteriological tissue cultures. Genotypic identification of M. bovis was performed by DNA extraction from bacterial isolates, formalin-fixed and paraffin-embedded (FFPE) tissues and samples without bacterial isolation. M. bovis was detected by PCR in 84.3% (27/32) of the studied cases; whereas other AFB were observed in tissues of the remaining sampled animals (5/32). Our results describe atypical granuloma formation in calves 4 months of age or younger, naturally infected with M. bovis. These findings contribute to better understanding the physiopathology of M. bovis infection in cattle.

Optimizing Genomic Prediction of Host Resistance to Koi Herpesvirus Disease in Carp

Genomic selection (GS) is increasingly applied in breeding programs of major aquaculture species, enabling improved prediction accuracy and genetic gain compared to pedigree-based approaches. Koi Herpesvirus disease (KHVD) is notifiable by the World Organization for Animal Health and the European Union, causing major economic losses to carp production. GS has potential to breed carp with improved resistance to KHVD, thereby contributing to disease control. In the current study, Restriction-site Associated DNA sequencing (RAD-seq) was applied on a population of 1,425 common carp juveniles which had been challenged with Koi herpes virus, followed by sampling of survivors and mortalities. GS was tested on a wide range of scenarios by varying both SNP densities and the genetic relationships between training and validation sets. The accuracy of correctly identifying KHVD resistant animals using GS was between 8 and 18% higher than pedigree best linear unbiased predictor (pBLUP) depending on the tested scenario. Furthermore, minor decreases in prediction accuracy were observed with decreased SNP density. However, the genetic relationship between the training and validation sets was a key factor in the efficacy of genomic prediction of KHVD resistance in carp, with substantially lower prediction accuracy when the relationships between the training and validation sets did not contain close relatives.

Enhancing genetic disease control by selecting for lower host infectivity and susceptibility

Infectious diseases have a huge impact on animal health, production and welfare, and human health. Understanding the role of host genetics in disease spread is important for developing disease control strategies that efficiently reduce infection incidence and risk of epidemics. While heritable variation in disease susceptibility has been targeted in livestock breeding, emerging evidence suggests that there is additional genetic variation in host infectivity, but the potential benefits of including infectivity into selection schemes are currently unknown. A Susceptible-Infected-Recovered epidemiological model incorporating polygenic genetic variation in both susceptibility and infectivity was combined with quantitative genetics selection theory to assess the non-linear impact of genetic selection on field measures of epidemic risk and severity. Response to 20 generations of selection was calculated in large simulated populations, exploring schemes differing in accuracy and intensity. Assuming moderate genetic variation in both traits, 50% selection on susceptibility required seven generations to reduce the basic reproductive number R₀ from 7.64 to the critical threshold of <1, below which epidemics die out. Adding infectivity in the selection objective accelerated the decline towards R₀ < 1, to 3 generations. Our results show that although genetic selection on susceptibility reduces disease risk and prevalence, the additional gain from selection on infectivity accelerates disease eradication and reduces more efficiently the risk of new outbreaks, while it alleviates delays generated by unfavourable correlations. In conclusion, host infectivity was found to be an important trait to target in future genetic studies and breeding schemes, to help reducing the occurrence and impact of epidemics.

Can We Breed Cattle for Lower Bovine TB Infectivity?

Host resistance and infectivity are genetic traits affecting infectious disease transmission. This Perspective discusses the potential exploitation of genetic variation in cattle infectivity, in addition to resistance, to reduce the risk, and prevalence of bovine tuberculosis (bTB). In bTB, variability in M. bovis shedding has been previously reported in cattle and wildlife hosts (badgers and wild boars), but the observed differences were attributed to dose and route of infection, rather than host genetics. This article addresses the extent to which cattle infectivity may play a role in bTB transmission, and discusses the feasibility, and potential benefits from incorporating infectivity into breeding programmes. The underlying hypothesis is that bTB infectivity, like resistance, is partly controlled by genetics. Identifying and reducing the number of cattle with high genetic infectivity, could reduce further a major risk factor for herds exposed to bTB. We outline evidence in support of this hypothesis and describe methodologies for detecting and estimating genetic parameters for infectivity. Using genetic-epidemiological prediction models we discuss the potential benefits of selection for reduced infectivity and increased resistance in terms of practical field measures of epidemic risk and severity. Simulations predict that adding infectivity to the breeding programme could enhance and accelerate the reduction in breakdown risk compared to selection on resistance alone. Therefore, given the recent launch of genetic evaluations for bTB resistance and the UK government's goal to eradicate bTB, it is timely to consider the potential of integrating infectivity into breeding schemes.

Impact of Genetic Selection for Increased Cattle Resistance to Bovine Tuberculosis on Disease Transmission Dynamics

Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to Mycobacterium bovis infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to infection in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent to which genetic selection could contribute to bTB eradication is unknown. The objective of this study was to quantify the impact of genetic selection for bTB resistance on cattle-to-cattle disease transmission dynamics and prevalence by developing a stochastic genetic epidemiological model. The model was used to implement genetic selection in a simulated cattle population. The model considered various levels of selection intensity over 20 generations assuming genetic heterogeneity in host resistance to infection. Our model attempted to represent the dairy cattle population structure and current bTB control strategies in the UK, and was informed by genetic and epidemiological parameters inferred from data collected from UK bTB infected dairy herds. The risk of a bTB breakdown was modeled as the percentage of herds where initially infected cows (index cases) generated secondary cases by infecting herd-mates. The model predicted that this risk would be reduced by half after 4, 6, 9, and 15 generations for selection intensities corresponding to genetic selection of the 10, 25, 50, and 70% most resistant sires, respectively. In herds undergoing bTB breakdowns, genetic selection reduced the severity of breakdowns over generations by reducing both the percentage of secondary cases and the duration over which new secondary cases were detected. Selection of the 10, 25, 50, and 70% most resistant sires reduced the percentage of secondary cases to <1% in 4, 5, 7, and 11 generations, respectively. Similarly, the proportion of long breakdowns (breakdowns in which secondary cases were detected for more than 365 days) was reduced by half in 2, 2, 3, and 4 generations, respectively. Collectively, results suggest that genetic selection could be a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.

Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing

BACKGROUND

European sea bass (Dicentrarchus labrax) is one of the most important species for European aquaculture. Viral nervous necrosis (VNN), commonly caused by the redspotted grouper nervous necrosis virus (RGNNV), can result in high levels of morbidity and mortality, mainly during the larval and juvenile stages of cultured sea bass. In the absence of efficient therapeutic treatments, selective breeding for host resistance offers a promising strategy to control this disease. Our study aimed at investigating genetic resistance to VNN and genomic-based approaches to improve disease resistance by selective breeding. A population of 1538 sea bass juveniles from a factorial cross between 48 sires and 17 dams was challenged with RGNNV with mortalities and survivors being recorded and sampled for genotyping by the RAD sequencing approach.

RESULTS

We used genome-wide genotype data from 9195 single nucleotide polymorphisms (SNPs) for downstream analysis. Estimates of heritability of survival on the underlying scale for the pedigree and genomic relationship matrices were 0.27 (HPD interval 95%: 0.14-0.40) and 0.43 (0.29-0.57), respectively. Classical genome-wide association analysis detected genome-wide significant quantitative trait loci (QTL) for resistance to VNN on chromosomes (unassigned scaffolds in the case of 'chromosome' 25) 3, 20 and 25 (P < 1e06). Weighted genomic best linear unbiased predictor provided additional support for the QTL on chromosome 3 and suggested that it explained 4% of the additive genetic variation. Genomic prediction approaches were tested to investigate the potential of using genome-wide SNP data to estimate breeding values for resistance to VNN and showed that genomic prediction resulted in a 13% increase in successful classification of resistant and susceptible animals compared to pedigree-based methods, with Bayes A and Bayes B giving the highest predictive ability.

CONCLUSIONS

Genome-wide significant QTL were identified but each with relatively small effects on the trait. Tests of genomic prediction suggested that incorporating genome-wide SNP data is likely to result in higher accuracy of estimated breeding values for resistance to VNN. RAD sequencing is an effective method for generating such genome-wide SNPs, and our findings highlight the potential of genomic selection to breed farmed European sea bass with improved resistance to VNN.

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens

Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle.

An analysis of effects of heterozygosity in dairy cattle for bovine tuberculosis resistance

Genetic selection of cattle more resistant to bovine tuberculosis (bTB) may offer a complementary control strategy. Hypothesising underlying non-additive genetic variation, we present an approach using genome-wide high density markers to identify genomic loci with dominance effects on bTB resistance and to test previously published regions with heterozygote advantage in bTB. Our data comprised 1151 Holstein-Friesian cows from Northern Ireland, confirmed bTB cases and controls, genotyped with the 700K Illumina BeadChip. Genome-wide markers were tested for associations between heterozygosity and bTB status using marker-based relationships. Results were tested for robustness against genetic structure, and the genotypic frequencies of a significant locus were tested for departures from Hardy-Weinberg equilibrium. Genomic regions identified in our study and in previous publications were tested for dominance effects. Genotypic effects were estimated through ASReml mixed models. A SNP (rs43032684) on chromosome 6 was significant at the chromosome-wide level, explaining 1.7% of the phenotypic variance. In the controls, there were fewer heterozygotes for rs43032684 (P < 0.01) with the genotypic values suggesting that heterozygosity confers a heterozygote disadvantage. The region surrounding rs43032684 had a significant dominance effect (P < 0.01). SNP rs43032684 resides within a pseudogene with a parental gene involved in macrophage response to infection and within a copy-number-variation region previously associated with nematode resistance. No dominance effect was found for the region on chromosome 11, as indicated by a previous candidate region bTB study. These findings require further validation with large-scale data.

Fine-mapping host genetic variation underlying outcomes to Mycobacterium bovis infection in dairy cows

BACKGROUND

Susceptibility to Mycobacterium bovis infection in cattle is governed in part by host genetics. However, cattle diagnosed as infected with M. bovis display varying signs of pathology. The variation in host response to infection could represent a continuum since time of exposure or distinct outcomes due to differing pathogen handling. The relationships between host genetics and variation in host response and pathological sequelae following M. bovis infection were explored by genotyping 1966 Holstein-Friesian dairy cows at 538,231 SNPs with three distinct phenotypes. These were: single intradermal cervical comparative tuberculin (SICCT) test positives with visible lesions (VLs), SICCT-positives with undetected visible lesions (NVLs) and matched controls SICCT-negative on multiple occasions.

RESULTS

Regional heritability mapping identified three loci associated with the NVL phenotype on chromosomes 17, 22 and 23, distinct to the region on chromosome 13 associated with the VL phenotype. The region on chromosome 23 was at genome-wide significance and candidate genes overlapping the mapped window included members of the bovine leukocyte antigen class IIb region, a complex known for its role in immunity and disease resistance. Chromosome heritability analysis attributed variance to six and thirteen chromosomes for the VL and NVL phenotypes, respectively, and four of these chromosomes were found to explain a proportion of the phenotypic variation for both the VL and NVL phenotype. By grouping the M. bovis outcomes (VLs and NVLs) variance was attributed to nine chromosomes. When contrasting the two M. bovis infection outcomes (VLs vs NVLs) nine chromosomes were found to harbour heritable variation. Regardless of the case phenotype under investigation, chromosome heritability did not exceed 8% indicating that the genetic control of bTB resistance consists of variants of small to moderate effect situated across many chromosomes of the bovine genome.

CONCLUSIONS

These findings suggest the host genetics of M. bovis infection outcomes is governed by distinct and overlapping genetic variants. Thus, variation in the pathology of M. bovis infected cattle may be partly genetically determined and indicative of different host responses or pathogen handling. There may be at least three distinct outcomes following M. bovis exposure in dairy cattle: resistance to infection, infection resulting in pathology or no detectable pathology.

Genomic regions underlying susceptibility to bovine tuberculosis in Holstein-Friesian cattle

BACKGROUND

The significant social and economic loss as a result of bovine tuberculosis (bTB) presents a continuous challenge to cattle industries in the UK and worldwide. However, host genetic variation in cattle susceptibility to bTB provides an opportunity to select for resistant animals and further understand the genetic mechanisms underlying disease dynamics.

METHODS

The present study identified genomic regions associated with susceptibility to bTB using genome-wide association (GWA), regional heritability mapping (RHM) and chromosome association approaches. Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires and pertained to three bTB indicator traits: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin tests with positive post-mortem examination results (phenotype 3). Genotypes based on the 50 K SNP DNA array were available and a total of 34,874 SNPs remained per animal after quality control.

RESULTS

The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWA analysis identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB.

CONCLUSION

Genomic regions and candidate genes identified in the present study provide an opportunity to further understand pathways critical to cattle susceptibility to bTB and enhance genetic improvement programmes aiming at controlling and eradicating the disease.

Occurrence and distribution of bovine TB pathology by age, sex, and breed of cattle slaughtered in Gusau Abattoir, Zamfara State Nigeria

This study was aimed to record gross lesions suggestive of bovine tuberculosis amongst cattle slaughtered in Gusau abattoir Zamfara State, Nigeria. A total of 3690 bovine carcasses were inspected from April to June, 2014. The results of the postmortem inspection detected tuberculosis-like lesions in 226 (6.1%) carcasses; 126 (56%) of the lesions observed were restricted to the organs/tissues of thoracic cavity and its associated lymph nodes, while 100 (44%) were seen in the organs/tissues of the abdominal cavity and reproductive tract of the carcasses. The organ encountered with most lesions was lungs; 90 (39.82%) out of the 226 lungs from carcasses observed with lesions. The individual animal prevalence was significantly affected by both age (χ2 = 4.723, p = 0.000) and sex (χ2 = 4.457, p = 0.000). For animal level risk, a strong statistically significant association was recorded between age (OR = 2.614, C.I. = 1.223 – 3.831) and sex (OR = 2.164, C.I. = 1.223 – 3.831); age and sex were predictive of bovine TB pathology. Breed prevalence was found to be 129 (57.1%) for White Fulani, 78 (34.5%) for Sokoto Gudali, and 19 (8.4%) for Red Bororo respectively. This study has for the first time recorded macroscopic lesions compatible with bovine TB; which suggests its possible prevalence in the study area. Postmortem inspection could be applied in the control and eradication of bovine TB and prevent its transmission to humans; in depth study is needed to better ascertain the true cause(s) of TB-like lesions in the area.

Genetic evaluation for bovine tuberculosis resistance in dairy cattle

Genetic evaluations for resistance to bovine tuberculosis (bTB) were calculated based on British national data including individual animal tuberculin skin test results, postmortem examination (presence of bTB lesions and bacteriological culture for Mycobacterium bovis), animal movement and location information, production history, and pedigree records. Holstein cows with identified sires in herds with bTB breakdowns (new herd incidents) occurring between the years 2000 and 2014 were considered. In the first instance, cows with a positive reaction to the skin test and a positive postmortem examination were defined as infected. Values of 0 and 1 were assigned to healthy and infected animal records, respectively. Data were analyzed with mixed models. Linear and logit function heritability estimates were 0.092 and 0.172, respectively. In subsequent analyses, breakdowns were split into 2-mo intervals to better model time of exposure and infection in the contemporary group. Intervals with at least one infected individual were retained and multiple intervals within the same breakdown were included. Healthy animal records were assigned values of 0, and infected records a value of 1 in the interval of infection and values reflecting a diminishing probability of infection in the preceding intervals. Heritability and repeatability estimates were 0.115 and 0.699, respectively. Reliabilities and across time stability of the genetic evaluation were improved with the interval model. Subsequently, 2 more definitions of "infected" were analyzed with the interval model: (1) all positive skin test reactors regardless of postmortem examination, and (2) all positive skin test reactors plus nonreactors with positive postmortem examination. Estimated heritability was 0.085 and 0.089, respectively; corresponding repeatability estimates were 0.701 and 0.697. Genetic evaluation reliabilities and across time stability did not change. Correlations of genetic evaluations for bTB with other traits in the current breeding goal were mostly not different from zero. Correlation with the UK Profitable Lifetime Index was moderate, significant, and favorable. Results demonstrated the feasibility of a national genetic evaluation for bTB resistance. Selection for enhanced resistance will have a positive effect on profitability and no antagonistic effects on current breeding goal traits. Official genetic evaluations are now based on the interval model and the last bTB trait definition.

Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT)

BACKGROUND

Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control. The aim of this study was to conduct a quantitative genetic analysis of SICCT measurements collected during bTB herd testing. Genetic selection for bTB resistance will be partially informed by SICCT-based diagnosis; therefore it is important to know whether, in addition to increasing bTB resistance, this might also alter genetically the epidemiological characteristics of SICCT.

RESULTS

Our main findings are that: (1) the SICCT test is robust at the genetic level, since its hierarchy and comparative nature provide substantial protection against random genetic changes that arise from genetic drift and from correlated responses among its components due to either natural or artificial selection; (2) the comparative nature of SICCT provides effective control for initial skin thickness and age-dependent differences; and (3) continuous variation in SICCT is only lowly heritable and has a weak correlation with SICCT positivity among healthy animals which was not significantly different from zero (P > 0.05). These emerging results demonstrate that genetic selection for bTB resistance is unlikely to change the probability of correctly identifying non-infected animals, i.e. the test's specificity, while reducing the overall number of cases.

CONCLUSIONS

This study cannot exclude all theoretical risks from selection on resistance to bTB infection but the role of SICCT in disease control is unlikely to be rapidly undermined, with any adverse correlated responses expected to be weak and slow, which allow them to be monitored and managed.

Exome Capture with Heterologous Enrichment in Pig (Sus scrofa)

The discovery of new protein-coding DNA variants related to carcass traits is very important for the Italian pig industry, which requires heavy pigs with higher thickness of subcutaneous fat for Protected Designation of Origin (PDO) productions. Exome capture techniques offer the opportunity to focus on the regions of DNA potentially related to the gene and protein expression. In this research a human commercial target enrichment kit was used to evaluate its performances for pig exome capture and for the identification of DNA variants suitable for comparative analysis. Two pools of 30 pigs each, crosses of Italian Duroc X Large White (DU) and Commercial hybrid X Large White (HY), were used and NGS libraries were prepared with the SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent). A total of 140.2 M and 162.5 M of raw reads were generated for DU and HY, respectively. Average coverage of all the exonic regions for Sus scrofa (ENSEMBL Sus_scrofa.Sscrofa10.2.73.gtf) was 89.33X for DU and 97.56X for HY; and 35% of aligned bases uniquely mapped to off-target regions. Comparison of sequencing data with the Sscrofa10.2 reference genome, after applying hard filtering criteria, revealed a total of 232,530 single nucleotide variants (SNVs) of which 20.6% mapped in exonic regions and 49.5% within intronic regions. The comparison of allele frequencies of 213 randomly selected SNVs from exome sequencing and the same SNVs analyzed with a Sequenom MassARRAY® system confirms that this “human-on-pig” approach offers new potentiality for the identification of DNA variants in protein-coding genes.

Selective breeding: the future of TB management in African buffalo?

The high prevalence of bovine tuberculosis (BTB) in African buffalo (Syncerus caffer) in regions of southern African has a negative economic impact on the trade of animals and animal products, represents an ecological threat to biodiversity, and poses a health risk to local communities through the wildlife-cattle-human interface. Test and cull methods may not be logistically feasible in many free-range wildlife systems, and with the presence of co-existing BTB hosts and the limited effectiveness of the BCG vaccine in buffalo, there is a need for alternative methods of BTB management. Selective breeding for increased resistance to BTB in buffalo may be a viable method of BTB management in the future, particularly if genetic information can be incorporated into these schemes. To explore this possibility, we discuss the different strategies that can be employed in selective breeding programmes, and consider the implementation of genetic improvement schemes. We reflect on the suitability of applying this strategy for enhanced BTB resistance in African buffalo, and address the challenges of this approach that must be taken into account. Conclusions and the implications for management are presented.

Genetic resistance to infections in sheep

This paper considers genetic resistance to infectious disease in sheep, with appropriate comparison with goats, and explores how such variation may be used to assist in disease control. Many studies have attempted to quantify the extent to which host animals differ genetically in their resistance to infection or in the disease side-effects of infection, using either recorded animal pedigrees or information from genetic markers to quantify the genetic variation. Across all livestock species, whenever studies are sufficiently well powered, then genetic variation in disease resistance is usually seen and such evidence is presented here for three infections or diseases of importance to sheep, namely mastitis, foot rot and scrapie. A further class of diseases of importance in most small ruminant production systems, gastrointestinal nematode infections, is outside the scope of this review. Existence of genetic variation implies the opportunity, at least in principle, to select animals for increased resistance, with such selection ideally used as part of an integrated control strategy. For each of the diseases under consideration, evidence for genetic variation is presented, the role of selection as an aid to disease control is outlined and possible side effects of selection in terms of effects in performance, effects on resistance to other diseases and potential parasite/pathogen coevolution risks are considered. In all cases, the conclusion is drawn that selection should work and it should be beneficial, with the main challenge being to define cost effective selection protocols that are attractive to sheep farmers.

Genomics and disease resistance studies in livestock

This paper considers the application of genetic and genomic techniques to disease resistance, the interpretation of data arising from such studies and the utilisation of the research outcomes to breed animals for enhanced resistance. Resistance and tolerance are defined and contrasted, factors affecting the analysis and interpretation of field data presented, and appropriate experimental designs discussed. These general principles are then applied to two detailed case studies, infectious pancreatic necrosis in Atlantic salmon and bovine tuberculosis in dairy cattle, and the lessons learnt are considered in detail. It is concluded that the rate limiting step in disease genetic studies will generally be provision of adequate phenotypic data, and its interpretation, rather than the genomic resources. Lastly, the importance of cross-disciplinary dialogue between the animal health and animal genetics communities is stressed.