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Psoriasis is a debilitating inflammatory condition that affects physiological and psychological states of millions around the world. Conventional biologic and nonbiologic therapies are fraught with profound adverse side effect profiles, frequent injection requirements, suboptimal outcomes, and other detriments. An enhanced understanding of the role of cytokines in psoriasis, particularly interleukins 12, 17, and 23, has afforded improved therapeutic strategies. Herein, we described the role of cytokines in psoriasis as well as current and prospective therapeutic approaches to treat this debilitating disease., Competing Interests: None disclosed.

Background: Historically recalcitrant to treatment, infection of the nail unit is a pervasive clinical condition affecting approximately 10% to 20% of the US population; patients present with both cosmetic symptomatology and pain, with subsequent dystrophic morphology. To date, the presumptive infectious etiologies include classically reported fungal dermatophytes, nondermatophyte molds, and yeasts. Until now, the prevalence and potential contribution of bacteria to the clinical course of dystrophic nails had been relatively overlooked, if not dismissed. Previously, diagnosis had largely been made by means of clinical presentation, although microscopic examinations (potassium hydroxide) of nail scrapings to identify fungal agents and, more recently, panel-specific polymerase chain reaction assays have been used to elucidate causative infectious agents. Each of these tools suffers from test-specific limitations., Methods: Molecular-age medicine now includes DNA-based tools to universally assess any microbe or pathogen with a known DNA sequence. This affords clinicians with rapid DNA sequencing technologies at their disposal. These sequencing-based diagnostic tools confer the accuracy of DNA-level certainty, and concurrently obviate cultivation or microbial phenotypical biases., Results: Using DNA sequencing-based diagnostics, the results in this article document the first identification and quantification of significant bacterial, rather than mycotic, pathogens to the clinical manifestation of dystrophic nails., Conclusions: In direct opposition to the prevailing and presumptive mycotic-based causes, the results in this article invoke questions about the very basis for our current standards of care, including effective treatment regimens.

Genetic resistance to infectious pancreatic necrosis virus (IPNV) in Atlantic salmon is a rare example of a trait where a single locus (QTL) explains almost all of the genetic variation. Genetic marker tests based on this QTL on salmon chromosome 26 have been widely applied in selective breeding to markedly reduce the incidence of the disease. In the current study, whole genome sequencing and functional annotation approaches were applied to characterise genes and variants in the QTL region. This was complemented by an analysis of differential expression between salmon fry of homozygous resistant and homozygous susceptible genotypes challenged with IPNV. These analyses pointed to the NEDD-8 activating enzyme 1 (nae1) gene as a putative functional candidate underlying the QTL effect. The role of nae1 in IPN resistance was further assessed via CRISPR-Cas9 knockout of the nae1 gene and chemical inhibition of the nae1 protein activity in Atlantic salmon cell lines, both of which resulted in highly significant reduction in productive IPNV replication. In contrast, CRISPR-Cas9 knockout of a candidate gene previously purported to be a cellular receptor for the virus (cdh1) did not have a major impact on productive IPNV replication. These results suggest that nae1 is the causative gene underlying the major QTL affecting resistance to IPNV in salmon, provide further evidence for the critical role of neddylation in host-pathogen interactions, and highlight the value in combining high-throughput genomics approaches with targeted genome editing to understand the genetic basis of disease resistance., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Individuals differ widely in their contribution to the spread of infection within and across populations. Three key epidemiological host traits affect infectious disease spread: susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection to others) and recoverability (propensity to recover quickly). Interventions aiming to reduce disease spread may target improvement in any one of these traits, but the necessary statistical methods for obtaining risk estimates are lacking. In this paper we introduce a novel software tool called SIRE (standing for "Susceptibility, Infectivity and Recoverability Estimation"), which allows for the first time simultaneous estimation of the genetic effect of a single nucleotide polymorphism (SNP), as well as non-genetic influences on these three unobservable host traits. SIRE implements a flexible Bayesian algorithm which accommodates a wide range of disease surveillance data comprising any combination of recorded individual infection and/or recovery times, or disease diagnostic test results. Different genetic and non-genetic regulations and data scenarios (representing realistic recording schemes) were simulated to validate SIRE and to assess their impact on the precision, accuracy and bias of parameter estimates. This analysis revealed that with few exceptions, SIRE provides unbiased, accurate parameter estimates associated with all three host traits. For most scenarios, SNP effects associated with recoverability can be estimated with highest precision, followed by susceptibility. For infectivity, many epidemics with few individuals give substantially more statistical power to identify SNP effects than the reverse. Importantly, precise estimates of SNP and other effects could be obtained even in the case of incomplete, censored and relatively infrequent measurements of individuals' infection or survival status, albeit requiring more individuals to yield equivalent precision. SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission., Competing Interests: The authors have declared that no competing interests exist. Author Stephen C. Bishop was unable to confirm their authorship contributions. On their behalf, the corresponding author has reported their contributions to the best of their knowledge.

The molecular processes by which some human ductal carcinoma in situ (DCIS) lesions advance to the more aggressive form, while others remain indolent, are largely unknown. Experiments utilizing a patient-derived (PDX) DCIS Mouse INtraDuctal (MIND) animal model combined with ChIP-exo and RNA sequencing revealed that the formation of protein complexes between B Cell Lymphoma-9 (BCL9), phosphoserine 727 STAT3 (PS-727-STAT3) and non-STAT3 transcription factors on chromatin enhancers lead to subsequent transcription of key drivers of DCIS malignancy. Downregulation of two such targets, integrin β3 and its associated metalloproteinase, MMP16, resulted in a significant inhibition of DCIS invasive progression. Finally, in vivo targeting of BCL9, using rosemary extract, resulted in significant inhibition of DCIS malignancy in both cell line and PDX DCIS MIND animal models. As such, our studies provide compelling evidence for future testing of rosemary extract as a chemopreventive agent in breast cancer., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2020.)

Markov chain Monte Carlo (MCMC) is widely used for Bayesian inference in models of complex systems. Performance, however, is often unsatisfactory in models with many latent variables due to so-called poor mixing, necessitating the development of application-specific implementations. This paper introduces 'posterior-based proposals' (PBPs), a new type of MCMC update applicable to a huge class of statistical models (whose conditional dependence structures are represented by directed acyclic graphs). PBPs generate large joint updates in parameter and latent variable space, while retaining good acceptance rates (typically 33%). Evaluation against other approaches (from standard Gibbs/random walk updates to state-of-the-art Hamiltonian and particle MCMC methods) was carried out for widely varying model types: an individual-based model for disease diagnostic test data, a financial stochastic volatility model, a mixed model used in statistical genetics and a population model used in ecology. While different methods worked better or worse in different scenarios, PBPs were found to be either near to the fastest or significantly faster than the next best approach (by up to a factor of 10). PBPs, therefore, represent an additional general purpose technique that can be usefully applied in a wide variety of contexts., Competing Interests: We declare we have no competing interests., (© 2019 The Authors.)

The lanthanides (Ln3+), or rare earth elements, have proven to be useful tools for biomolecular NMR, X-ray crystallographic, and fluorescence analyses due to their unique 4f orbitals. However, their utility in biological applications has been limited because site-specific incorporation of a chelating element is required to ensure efficient binding of the free Ln3+ ion. Additionally, current Ln3+ chelator syntheses complicate efforts to directly incorporate Ln3+ chelators into proteins as the multi-step processes and a reliance on organic solvents promote protein denaturation and aggregation which are generally incompatible with direct incorporation into the protein of interest. To overcome these limitations, herein we describe a two-step aqueous synthesis of a small molecule lanthanide chelating agent amenable to site-specific incorporation into a protein using copper-free click chemistry with unnatural amino acids. The bioconjugate combines a diethylenetriaminepentaacetic acid (DTPA) chelating moiety with a clickable dibenzylcyclooctyne-amine (DBCO-amine) to facilitate the reaction with an azide containing unnatural amino acid. Incorporating the DBCO-amine avoids the use of the cytotoxic Cu2+ ion as a catalyst. The clickable lanthanide chelator (CLC) reagent reacted readily with p-azidophenylalanine (paF) without the need of a copper catalyst, thereby demonstrating proof-of-concept. Implementation of the orthogonal click chemistry reaction has the added advantage that the chelator can be used directly in a protein labeling reaction, without the need of extensive purification. Given the inherent advantages of Cu2+-free click chemistry, aqueous synthesis, and facile labeling, we believe that the CLC will find abundant use in both structural and biophysical studies of proteins and their complexes., Competing Interests: The authors have declared that no competing interests exist.

Goniodysgenesis is a developmental abnormality of the anterior chamber of the eye. It is generally considered to be congenital in dogs ( Canis lupus familiaris ), and has been associated with glaucoma and blindness. Goniodysgenesis and early-onset glaucoma initially emerged in Border Collies in Australia in the late 1990s and have subsequently been found in this breed in Europe and the USA. The objective of the present study was to determine the genetic basis of goniodysgenesis in Border Collies. Clinical diagnosis was based on results of examinations by veterinary ophthalmologists of affected and unaffected dogs from eleven different countries. Genotyping using the Illumina high density canine single nucleotide variant genotyping chip was used to identify a candidate genetic region. There was a highly significant peak of association over chromosome 17, with a p -value of 2 × 10 -13 Expression profiles and evolutionary conservation of candidate genes were assessed using public databases. Whole genome sequences of three dogs with glaucoma, three severely affected by goniodysgenesis and three unaffected dogs identified a missense variant in the olfactomedin like 3 ( OLFML3 ) gene in all six affected animals. This was homozygous for the risk allele in all nine cases with glaucoma and 12 of 14 other severely affected animals. Of 67 reportedly unaffected animals, only one was homozygous for this variant (offspring of parents both with goniodysgenesis who were also homozygous for the variant). Analysis of pedigree information was consistent with an autosomal recessive mode of inheritance for severe goniodysgenesis (potentially leading to glaucoma) in this breed. The identification of a candidate genetic region and putative causative variant will aid breeders to reduce the frequency of goniodysgenesis and the risk of glaucoma in the Border Collie population., (Copyright © 2019 Pugh et al.)

Balancing selection provides a plausible explanation for the maintenance of deleterious alleles at moderate frequency in livestock, including lethal recessives exhibiting heterozygous advantage in carriers. In the current study, a leg weakness syndrome causing mortality of piglets in a commercial line showed monogenic recessive inheritance, and a region on chromosome 15 associated with the syndrome was identified by homozygosity mapping. Whole genome resequencing of cases and controls identified a mutation causing a premature stop codon within exon 3 of the porcine Myostatin (MSTN) gene, similar to those causing a double-muscling phenotype observed in several mammalian species. The MSTN mutation was in Hardy-Weinberg equilibrium in the population at birth, but significantly distorted amongst animals still in the herd at 110 kg, due to an absence of homozygous mutant genotypes. In heterozygous form, the MSTN mutation was associated with a major increase in muscle depth and decrease in fat depth, suggesting that the deleterious allele was maintained at moderate frequency due to heterozygous advantage (allele frequency, q = 0.22). Knockout of the porcine MSTN by gene editing has previously been linked to problems of low piglet survival and lameness. This MSTN mutation is an example of putative balancing selection in livestock, providing a plausible explanation for the lack of disrupting MSTN mutations in pigs despite many generations of selection for lean growth., Competing Interests: No authors have competing interests. GAW and AEH are both employed by JSR Genetics Limited who historically marketed the genetic line used in this study as a sireline boar product to commercial farmers. The line has since has been culled and JSR Genetics Limited no longer receive any revenue from the product.

Coccidiosis in poultry, caused by protozoan parasites of the genus Eimeria , is an intestinal disease with substantial economic impact. With the use of anticoccidial drugs under public and political pressure, and the comparatively higher cost of live-attenuated vaccines, an attractive complementary strategy for control is to breed chickens with increased resistance to Eimeria parasitism. Prior infection with Eimeria maxima leads to complete immunity against challenge with homologous strains, but only partial resistance to challenge with antigenically diverse heterologous strains. We investigate the genetic architecture of avian resistance to E. maxima primary infection and heterologous strain secondary challenge using White Leghorn populations of derived inbred lines, C.B12 and 15I, known to differ in susceptibility to the parasite. An intercross population was infected with E. maxima Houghton (H) strain, followed 3 weeks later by E. maxima Weybridge (W) strain challenge, while a backcross population received a single E. maxima W infection. The phenotypes measured were parasite replication (counting fecal oocyst output or qPCR for parasite numbers in intestinal tissue), intestinal lesion score (gross pathology, scale 0-4), and for the backcross only, serum interleukin-10 (IL-10) levels. Birds were genotyped using a high density genome-wide DNA array (600K, Affymetrix). Genome-wide association study located associations on chromosomes 1, 2, 3, and 5 following primary infection in the backcross population, and a suggestive association on chromosome 1 following heterologous E. maxima W challenge in the intercross population. This mapped several megabases away from the quantitative trait locus (QTL) linked to the backcross primary W strain infection, suggesting different underlying mechanisms for the primary- and heterologous secondary- responses. Underlying pathways for those genes located in the respective QTL for resistance to primary infection and protection against heterologous challenge were related mainly to immune response, with IL-10 signaling in the backcross primary infection being the most significant. Additionally, the identified markers associated with IL-10 levels exhibited significant additive genetic variance. We suggest this is a phenotype of interest to the outcome of challenge, being scalable in live birds and negating the requirement for single-bird cages, fecal oocyst counts, or slaughter for sampling (qPCR).

Background: Coccidiosis is a major contributor to losses in poultry production. With emerging constraints on the use of in-feed prophylactic anticoccidial drugs and the relatively high costs of effective vaccines, there are commercial incentives to breed chickens with greater resistance to this important production disease. To identify phenotypic biomarkers that are associated with the production impacts of coccidiosis, and to assess their covariance and heritability, 942 Cobb500 commercial broilers were subjected to a defined challenge with Eimeria tenella (Houghton). Three traits were measured: weight gain (WG) during the period of infection, caecal lesion score (CLS) post mortem, and the level of a serum biomarker of intestinal inflammation, i.e. circulating interleukin 10 (IL-10), measured at the height of the infection., Results: Phenotypic analysis of the challenged chicken cohort revealed a significant positive correlation between CLS and IL-10, with significant negative correlations of both these traits with WG. Eigenanalysis of phenotypic covariances between measured traits revealed three distinct eigenvectors. Trait weightings of the first eigenvector, (EV1, eigenvalue = 59%), were biologically interpreted as representing a response of birds that were susceptible to infection, with low WG, high CLS and high IL-10. Similarly, the second eigenvector represented infection resilience/resistance (EV2, 22%; high WG, low CLS and high IL-10), and the third eigenvector tolerance (EV3, 19%; high WG, high CLS and low IL-10), respectively. Genome-wide association studies (GWAS) identified two SNPs that were associated with WG at the suggestive level., Conclusions: Eigenanalysis separated the phenotypic impact of a defined challenge with E. tenella on WG, caecal inflammation/pathology, and production of IL-10 into three major eigenvectors, indicating that the susceptibility-resistance axis is not a single continuous quantitative trait. The SNPs identified by the GWAS for body weight were located in close proximity to two genes that are involved in innate immunity (FAM96B and RRAD).

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., (© 2018 The Authors. Animal Genetics published by John Wiley & Sons Ltd on behalf of Stichting International Foundation for Animal Genetics.)

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.

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.

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., (The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

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.

In reproducing ewes, a periparturient breakdown of immunity is often observed to result in increased fecal egg excretion, making them the main source of infection for their immunologically naive lambs. In this study, we expanded a simulation model previously developed for growing lambs to explore the impact of the genotype (performance and resistance traits) and host nutrition on the performance and parasitism of both growing lambs and reproducing ewes naturally infected with Teladorsagia circumcincta. Our model accounted for nutrient-demanding phases, such as gestation and lactation, and included a supplementary module to manage the age structure of the ewe flock. The model was validated by comparison with published data. Because model parameters were unknown or poorly estimated, detailed sensitivity analysis of the model was performed for the sheep mortality and the level of infection, following a preliminary screening step. The parameters with the greatest effect on parasite-related outputs were those driving animal growth and milk yield. Our model enables different parasite-control strategies (host nutrition, breeding for resistance and anthelmintic treatments) to be assessed on the long term in a sheep flock. To optimize in silico exploration, the parameters highlighted by the sensitivity analysis should be refined with real data.

A dynamic, deterministic model was developed to investigate the consequences of parasitism with Ostertagia ostertagi, the most prevalent and economically important gastrointestinal parasite of cattle in temperate regions. Interactions between host and parasite were considered to predict the level of parasitism and performance of an infected calf. Key model inputs included calf intrinsic growth rate, feed quality and mode and level of infection. The effects of these varied inputs were simulated on a daily basis for key parasitological (worm burden, total egg output and faecal egg count) and performance outputs (feed intake and bodyweight) over a 6 month grazing period. Data from published literature were used to parameterise the model and its sensitivity was tested for uncertain parameters by a Latin hypercube sensitivity design. For the latter each parameter tested was subject to a 20% coefficient of variation. The model parasitological outputs were most sensitive to the immune rate parameters that affected overall worm burdens. The model predicted the expected larger worm burdens along with disproportionately greater body weight losses with increasing daily infection levels. The model was validated against published literature using graphical and statistical comparisons. Its predictions were quantitatively consistent with the parasitological outputs of published experiments in which calves were subjected to different infection levels. The consequences of model weaknesses are discussed and point towards model improvements. Future work should focus on developing a stochastic model to account for calf variation in performance and immune response; this will ultimately be used to test the effectiveness of different parasite control strategies in naturally infected calf populations., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

Targeted selective treatment (TST) requires the ability to identify the animals for which anthelmintic treatment will result in the greatest benefit to the entire flock. Various phenotypic traits have previously been suggested as determinant criteria for TST; however, the weight gain benefit and impact on anthelmintic efficacy for each determinant criterion is expected to be dependent upon the level of nematode challenge and the timing of anthelmintic treatment. A mathematical model was used to simulate a population of 10,000 parasitologically naïve Scottish Blackface lambs (with heritable variation in host-parasite interactions) grazing on medium-quality pasture (grazing density=30 lambs/ha, crude protein=140g/kg DM, metabolisable energy=10MJ/kg DM) with an initial larval contamination of 1000, 3000 or 5000 Teladorsagia circumcincta L3/kg DM. Anthelmintic drenches were administered to 0, 50 or 100% of the population on a single occasion. The day of anthelmintic treatment was independently modelled for every day within the 121day simulation. Where TST scenarios were simulated (50% treated), lambs were either chosen by random selection or according to highest faecal egg count (FEC, eggs/g DM faeces), lowest live weight (LW, kg) or lowest growth rate (kg/day). Average lamb empty body weight (kg) and the resistance (R) allele frequency amongst the parasite population on pasture were recorded at slaughter (day 121) for each scenario. Average weight gain benefit and increase in R allele frequency for each determinant criterion, level of initial larval contamination and day of anthelmintic treatment were calculated by comparison to a non-treated population. Determinant criteria were evaluated according to average weight gain benefit divided by increase in R allele frequency to determine the benefit per R. Whilst positive phenotypic correlations were predicted between worm burden and FEC; using LW as the determinant criterion provided the greatest benefit per R for all levels of initial larval contamination and day of anthelmintic treatment. Hence, LW was identified as the best determinant criterion for use in a TST regime. This study supports the use of TST strategies as benefit per R predictions for all determinant criteria were greater than those predicted for the 100% treatment group, representing an increased long-term productive benefit resulting from the maintenance of anthelmintic efficacy. Whilst not included in this study, the model could be extended to consider other parasite species and host breed parameters, variation in climatic influences on larval availability and grass growth, repeated anthelmintic treatments and variable proportional flock treatments., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background: Our recent research showed that antibody response to porcine reproductive and respiratory syndrome (PRRS), measured as sample-to-positive (S/P) ratio, is highly heritable and has a high genetic correlation with reproductive performance during a PRRS outbreak. Two major quantitative trait loci (QTL) on Sus scrofa chromosome 7 (SSC7; QTLMHC and QTL130) accounted for ~40 % of the genetic variance for S/P. Objectives of this study were to estimate genetic parameters for PRRS S/P in gilts during acclimation, identify regions associated with S/P, and evaluate the accuracy of genomic prediction of S/P across populations with different prevalences of PRRS and using different single nucleotide polymorphism (SNP) sets., Methods: Phenotypes and high-density SNP genotypes of female pigs from two datasets were used. The outbreak dataset included 607 animals from one multiplier herd, whereas the gilt acclimation (GA) dataset included data on 2364 replacement gilts from seven breeding companies placed on health-challenged farms. Genomic prediction was evaluated using GA for training and validation, and using GA for training and outbreak for validation. Predictions were based on SNPs across the genome (SNPAll), SNPs in one (SNPMHC and SNP130) or both (SNPSSC7) QTL, or SNPs outside the QTL (SNPRest)., Results: Heritability of S/P in the GA dataset increased with the proportion of PRRS-positive animals in the herd (from 0.28 to 0.47). Genomic prediction accuracies ranged from low to moderate. Average accuracies were highest when using only the 269 SNPs in both QTL regions (SNPSSC7, with accuracies of 0.39 and 0.31 for outbreak and GA validation datasets, respectively. Average accuracies for SNPALL, SNPMHC, SNP130, and SNPRest were, respectively, 0.26, 0.39, 0.21, and 0.05 for the outbreak, and 0.28, 0.25, 0.22, and 0.12, for the GA validation datasets., Conclusions: Moderate genomic prediction accuracies can be obtained for PRRS antibody response using SNPs located within two major QTL on SSC7, while the rest of the genome showed limited predictive ability. Results were obtained using data from multiple genetic sources and farms, which further strengthens these findings. Further research is needed to validate the use of S/P ratio as an indicator trait for reproductive performance during PRRS outbreaks.

Background: Sea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals., Results: Heritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction., Conclusions: Host resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.

Background: Infectious Pancreatic Necrosis (IPN) is a highly contagious birnavirus disease of farmed salmonid fish, which often causes high levels of morbidity and mortality. A large host genetic component to resistance has been previously described for Atlantic salmon (Salmo salar L.), which mediates high mortality rates in some families and zero mortality in others. However, the molecular and immunological basis for this resistance is not yet fully known. This manuscript describes a global comparison of the gene expression profiles of resistant and susceptible Atlantic salmon fry following challenge with the IPN virus., Results: Salmon fry from two IPNV-resistant and two IPNV-susceptible full sibling families were challenged with the virus and sampled at 1 day, 7 days and 20 days post-challenge. Significant viral titre was observed in both resistant and susceptible fish at all timepoints, although generally at higher levels in susceptible fish. Gene expression profiles combined with gene ontology and pathway analyses demonstrated that while a clear immune response was observed in both resistant and susceptible fish, there were striking differences between the two phenotypes. The susceptible fish showed marked up-regulation of genes related to cytokine activity and inflammatory response that evidently failed to protect against the virus. In contrast, the resistant fish demonstrated a less pronounced immune response including up-regulation of genes relating to the M2 macrophage system., Conclusions: While only the susceptible phenotype shows appreciable mortality levels, both resistant and susceptible fish can become infected with IPNV. Susceptible fish are characterized by a much larger, yet ineffective, immune response, largely related to cytokine and inflammatory systems. Resistant fish demonstrate a more moderate, putative macrophage-mediated inflammatory response, which may contribute to their survival.

Ticks and tick-borne diseases are among the main causes of economic loss in the South African cattle industry through high morbidity and mortality rates. Concerns of the general public regarding chemical residues may tarnish their perceptions of food safety and environmental health when the husbandry of cattle includes frequent use of acaricides to manage ticks. The primary objective of this study was to identify single nucleotide polymorphism (SNP) markers associated with host resistance to ticks in South African Nguni cattle. Tick count data were collected monthly from 586 Nguni cattle reared in four herds under natural grazing conditions over a period of two years. The counts were recorded for six species of ticks attached in eight anatomical locations on the animals and were summed by species and anatomical location. This gave rise to 63 measured phenotypes or traits, with results for 12 of these traits being reported here. Tick count (x) data were transformed using log10(x+1) and the resulting values were examined for normality. DNA was extracted from hair and blood samples and was genotyped using the Illumina BovineSNP50 assay. After quality control (call rate >90%, minor allele frequency >0.02), 40,436 SNPs were retained for analysis. Genetic parameters were estimated and association analysis for tick resistance was carried out using two approaches: a genome-wide association (GWA) analysis using the GenABEL package and a regional heritability mapping (RHM) analysis. The Bonferroni genome-wide (P<0.05) corrected significance threshold was 1.24×10(-6), with 2.47×10(-5) as the suggestive significance threshold (P<0.10) (i.e., one false positive per genome scan) in the GWA analysis. Likelihood ratio test (LRT) thresholds for genome-wide and suggestive significance were 13.5 and 9.15 for the RHM analysis. Six ixodid tick species were identified, with Amblyomma hebraeum (the vector for Heartwater disease) being the dominant species. Heritability estimates (h(2)) from the fitted animal and sire models ranged from 0.02±0.00 to 0.17±0.04 for the transformed tick count data. Several genomic regions harbouring quantitative trait loci (QTL) were identified for different tick count traits by both the GWA and RHM approaches. Three genome-wide significant regions on chromosomes 7, 10 and 19 were identified for total tick count on the head, total body A. hebraeum tick count and total A. hebraeum on the perineum region, respectively. Additional regions significant at the suggestive level were identified on chromosomes 1, 3, 6, 7, 8, 10, 11, 12, 14, 15, 17, 19 and 26 for several of the traits. The GWA approach identified more genomic regions than did the RHM approach. The chromosomal regions identified here as harbouring QTL underlying variation in tick burden form the basis for further analyses to identify specific candidate genes and polymorphisms related to cattle tick resistance and provide the potential for marker-assisted selection in Nguni cattle., (Copyright © 2016 Elsevier GmbH. All rights reserved.)

Background: Improving meat quality including taste and tenderness is critical to the protection and development of markets for sheep meat. Phenotypic selection for such measures of meat quality is constrained by the fact that these parameters can only be measured post-slaughter. Carcass composition has an impact on meat quality and can be measured on live animals using advanced imaging technologies such as X-ray computed tomography (CT). Since carcass composition traits are heritable, they are potentially amenable to improvement through marker-assisted and genomic selection. We conducted a genome-wide association study (GWAS) on about 600 Scottish Blackface lambs for which detailed carcass composition phenotypes, including bone, fat and muscle components, had been captured using CT and which were genotyped for ~40,000 single nucleotide polymorphisms (SNPs) using the Illumina OvineSNP50 chip., Results: We confirmed that the carcass composition traits were heritable with moderate to high (0.19-0.78) heritabilities. The GWAS analyses revealed multiple SNPs and quantitative trait loci (QTL) that were associated with effects on carcass composition traits and were significant at the genome-wide level. In particular, we identified a region on ovine chromosome 6 (OAR6) associated with bone weight and bone area that harboured SNPs with p values of 5.55 × 10(-8) and 2.63 × 10(-9), respectively. The same region had effects on fat area, fat density, fat weight and muscle density. We identified plausible positional candidate genes for these OAR6 QTL. We also detected a SNP that reached the genome-wide significance threshold with a p value of 7.28 × 10(-7) and was associated with muscle density on OAR1. Using a regional heritability mapping approach, we also detected regions on OAR3 and 24 that reached genome-wide significance for bone density., Conclusions: We identified QTL on OAR1, 3, 24 and particularly on OAR6 that are associated with effects on muscle, fat and bone traits. Based on available evidence that indicates that these traits are genetically correlated with meat quality traits, these associated SNPs have potential applications in selective breeding for improved meat quality. Further research is required to determine whether the effects associated with the OAR6 QTL are caused by a single gene or several closely-linked genes.

Understanding the relationship between genetic variants and traits of economic importance in aquaculture species is pertinent to selective breeding programmes. High-throughput sequencing technologies have enabled the discovery of large numbers of SNPs in Atlantic salmon, and high density SNP arrays now exist. A previous genome-wide association study (GWAS) using a high density SNP array (132K SNPs) has revealed the polygenic nature of early growth traits in salmon, but has also identified candidate SNPs showing suggestive associations with these traits. The aim of this study was to test the association of the candidate growth-associated SNPs in a separate population of farmed Atlantic salmon to verify their effects. Identifying SNP-trait associations in two populations provides evidence that the associations are true and robust. Using a large cohort (N = 1152), we successfully genotyped eight candidate SNPs from the previous GWAS, two of which were significantly associated with several growth and fillet traits measured at harvest. The genes proximal to these SNPs were identified by alignment to the salmon reference genome and are discussed in the context of their potential role in underpinning genetic variation in salmon growth.

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., (Copyright © 2015. Published by Elsevier B.V.)

Background: The genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. The use of genetic markers to predict the genetic merit (breeding values) of individuals is commonplace in modern farm animal breeding schemes. Recently, high density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth., Results: A pedigreed population of farmed Atlantic salmon (n = 622) were measured for weight and length traits at one year of age, and genotyped for 111,908 segregating SNP markers using a high density SNP array. The heritability of both traits was estimated using pedigree and genomic relationship matrices, and was comparable at around 0.5 and 0.6 respectively. The results of the GWA analysis pointed to a polygenic genetic architecture, with no SNPs surpassing the genome-wide significance threshold, and one SNP associated with length at the chromosome-wide level. SNPs surpassing an arbitrary threshold of significance (P < 0.005, ~ top 0.5 % of markers) were aligned to an Atlantic salmon reference transcriptome, identifying 109 SNPs in transcribed regions that were annotated by alignment to human, mouse and zebrafish protein databases. Prediction of breeding values was more accurate when applying genomic (GBLUP) than pedigree (PBLUP) relationship matrices (accuracy ~ 0.7 and 0.58 respectively) and 5,000 SNPs were sufficient for obtaining this accuracy increase over PBLUP in this specific population., Conclusions: The high density SNP array can effectively capture the additive genetic variation in complex traits. However, the traits of weight and length both appear to be very polygenic with only one SNP surpassing the chromosome-wide threshold. Genomic prediction using the array is effective, leading to an improvement in accuracy compared to pedigree methods, and this improvement can be achieved with only a small subset of the markers in this population. The results have practical relevance for genomic selection in salmon and may also provide insight into variation in the identified genes underpinning body growth and development in salmonid species.

Pancreas disease (PD), caused by a salmonid alphavirus (SAV), has a large negative economic and animal welfare impact on Atlantic salmon aquaculture. Evidence for genetic variation in host resistance to this disease has been reported, suggesting that selective breeding may potentially form an important component of disease control. The aim of this study was to explore the genetic architecture of resistance to PD, using survival data collected from two unrelated populations of Atlantic salmon; one challenged with SAV as fry in freshwater (POP 1) and one challenged with SAV as post-smolts in sea water (POP 2). Analyses of the binary survival data revealed a moderate-to-high heritability for host resistance to PD in both populations (fry POP 1 h(2)~0.5; post-smolt POP 2 h(2)~0.4). Subsets of both populations were genotyped for single nucleotide polymorphism markers, and six putative resistance quantitative trait loci (QTL) were identified. One of these QTL was mapped to the same location on chromosome 3 in both populations, reaching chromosome-wide significance in both the sire- and dam-based analyses in POP 1, and genome-wide significance in a combined analysis in POP 2. This independently verified QTL explains a significant proportion of host genetic variation in resistance to PD in both populations, suggesting a common underlying mechanism for genetic resistance across lifecycle stages. Markers associated with this QTL are being incorporated into selective breeding programs to improve PD resistance.

Background: Restriction site-Associated DNA sequencing (RAD-Seq) is widely applied to generate genome-wide sequence and genetic marker datasets. RAD-Seq has been extensively utilised, both at the population level and across species, for example in the construction of phylogenetic trees. However, the consistency of RAD-Seq data generated in different laboratories, and the potential use of cross-species orthologous RAD loci in the estimation of genetic relationships, have not been widely investigated. This study describes the use of SbfI RAD-Seq data for the estimation of evolutionary relationships amongst ten teleost fish species, using previously established phylogeny as a benchmark., Results: The number of orthologous SbfI RAD loci identified decreased with increasing evolutionary distance between the species, with several thousand loci conserved across five salmonid species (divergence ~50 MY), and several hundred conserved across the more distantly related teleost species (divergence ~100-360 MY). The majority (>70%) of loci identified between the more distantly related species were genic in origin, suggesting that the bias of SbfI towards genic regions is useful for identifying distant orthologs. Interspecific single nucleotide variants at each orthologous RAD locus were identified. Evolutionary relationships estimated using concatenated sequences of interspecific variants were congruent with previously published phylogenies, even for distantly (divergence up to ~360 MY) related species., Conclusion: Overall, this study has demonstrated that orthologous SbfI RAD loci can be identified across closely and distantly related species. This has positive implications for the repeatability of SbfI RAD-Seq and its potential to address research questions beyond the scope of the original studies. Furthermore, the concordance in tree topologies and relationships estimated in this study with published teleost phylogenies suggests that similar meta-datasets could be utilised in the prediction of evolutionary relationships across populations and species with readily available RAD-Seq datasets, but for which relationships remain uncharacterised.

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

Bayesian statistics provides a framework for the integration of dynamic models with incomplete data to enable inference of model parameters and unobserved aspects of the system under study. An important class of dynamic models is discrete state space, continuous-time Markov processes (DCTMPs). Simulated via the Doob-Gillespie algorithm, these have been used to model systems ranging from chemistry to ecology to epidemiology. A new type of proposal, termed 'model-based proposal' (MBP), is developed for the efficient implementation of Bayesian inference in DCTMPs using Markov chain Monte Carlo (MCMC). This new method, which in principle can be applied to any DCTMP, is compared (using simple epidemiological SIS and SIR models as easy to follow exemplars) to a standard MCMC approach and a recently proposed particle MCMC (PMCMC) technique. When measurements are made on a single-state variable (e.g. the number of infected individuals in a population during an epidemic), model-based proposal MCMC (MBP-MCMC) is marginally faster than PMCMC (by a factor of 2-8 for the tests performed), and significantly faster than the standard MCMC scheme (by a factor of 400 at least). However, when model complexity increases and measurements are made on more than one state variable (e.g. simultaneously on the number of infected individuals in spatially separated subpopulations), MBP-MCMC is significantly faster than PMCMC (more than 100-fold for just four subpopulations) and this difference becomes increasingly large., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

Background: Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position., Results: The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits., Conclusions: We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

Gastrointestinal nematode infections are one of the main health/economic issues in sheep industries, worldwide. Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; however, published results are inconsistent among breeds. Meta (or joint)-analysis is a tool for aggregating information from multiple independent studies. The aim of this study was to identify loci underlying variation in FEC, as an indicator of nematode resistance, in a joint analysis using data from three populations (Scottish Blackface, Sarda × Lacaune and Martinik Black-Belly × Romane), genotyped with the ovine 50k SNP chip. The trait analysed was the average animal effect for Strongyles and Nematodirus FEC data. Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated. Across-population genomic covariances were set to zero. After quality control, 4123 animals and 38 991 SNPs were available for the analysis. RHM identified genome-wide significant regions on OAR4, 12, 14, 19 and 20, with the latter being the most significant. The OAR20 region is close to the major histocompatibility complex, which has often been proposed as a functional candidate for nematode resistance. This region was significant only in the Sarda × Lacaune population. Several other regions, on OAR1, 3, 4, 5, 7, 12, 19, 20 and 24, were significant at the suggestive level., (© 2014 The Authors. Journal of Animal Breeding and Genetics Published by Blackwell Verlag GmbH.)

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.

Porcine reproductive and respiratory syndrome (PRRS) is the most economically significant disease impacting pig production in North America, Europe, and Asia, causing reproductive losses such as increased rates of stillbirth and mummified piglets. The objective of this study was to explore the genetic basis of host response to the PRRS virus (PRRSV) in a commercial multiplier sow herd before and after a PRRS outbreak, using antibody response and reproductive traits. Reproductive data comprising number born alive (NBA), number alive at 24 h (NA24), number stillborn (NSB), number born mummified (NBM), proportion born dead (PBD), number born dead (NBD), number weaned (NW), and number of mortalities through weaning (MW) of 5,227 litters from 1,967 purebred Landrace sows were used along with a pedigree comprising 2,995 pigs. The PRRS outbreak date was estimated from rolling averages of farrowing traits and was used to split the data into a pre-PRRS phase and a PRRS phase. All 641 sows in the herd during the outbreak were blood sampled 46 d after the estimated outbreak date and were tested for anti-PRRSV IgG using ELISA (sample-to-positive [S/P] ratio). Genetic parameters of traits were estimated separately for the pre-PRRS and PRRS phase data sets. Sows were genotyped using the PorcineSNP60 BeadChip, and genome-wide association studies (GWAS) were performed using method Bayes B. Heritability estimates for reproductive traits ranged from 0.01 (NBM) to 0.12 (NSB) and from 0.01 (MW) to 0.12 (NBD) for the pre-PRRS and PRRS phases, respectively. S/P ratio had heritability (0.45) and strong genetic correlations with most traits, ranging from -0.72 (NBM) to 0.73 (NBA). In the pre-PRRS phase, regions associated with NSB and PBD explained 1.6% and 3% of the genetic variance, respectively. In the PRRS phase, regions associated with NBD, NSB, and S/P ratio explained 0.8%, 11%, and 50.6% of the genetic variance, respectively. For S/P ratio, 2 regions on SSC 7 (SSC7) separated by 100 Mb explained 40% of the genetic variation, including a region encompassing the major histocompatibility complex, which explained 25% of the genetic variance. These results indicate a significant genomic component associated with PRRSV antibody response and NSB in this data set. Also, the high heritability and genetic correlation estimates for S/P ratio during the PRRS phase suggest that S/P ratio could be used as an indicator of the impact of PRRS on reproductive traits.

TM-QTL is a quantitative trait locus (QTL) on ovine chromosome 18 (OAR18) known to affect loin muscling in Texel sheep. Previous work suggested that its mode of inheritance is consistent with paternal polar overdominance, but this has yet to be formally demonstrated. This study used purebred Texel sheep segregating for TM-QTL to confirm its presence in the chromosomal region in which it was first reported and to determine its pattern of inheritance. To do so, this study used the first available data from a Texel flock, which included homozygote TM-QTL carriers (TM/TM; n=34) in addition to homozygote non-carriers (+/+; n=40 and, heterozygote TM-QTL-carriers inheriting TM-QTL from their sire (TM/+; n=53) or their dam (+/TM; n=17). Phenotypes included a wide range of loin muscling, carcass composition and tissue distribution traits. The presence of a QTL affecting ultrasound muscle depth on OAR18 was confirmed with a paternal QTL effect ranging from +0.54 to +2.82 mm UMD (s.e. 0.37 to 0.57 mm) across the sires segregating for TM-QTL. Loin muscle width, depth and area, loin muscle volume and dissected M. longissimus lumborum weight were significantly greater for TM/+ than +/+ lambs (+2.9% to +7.9%; P<0.05). There was significant evidence that the effect of TM-QTL on the various loin muscling traits measured was paternally polar overdominant (P<0.05). In contrast, there was an additive effect of TM-QTL on both live weight at 20 weeks and carcass weight; TM/TM animals were significantly (P<0.05) heavier than +/+ (+11.1% and +7.3%, respectively) and +/TM animals (+11.9% and +11.7%, respectively), with TM/+ intermediate. Weights of the leg, saddle and shoulder region (corrected for carcass weight) were similar in the genotypic groups. There was a tendency for lambs inheriting TM-QTL from their sire to be less fat with slightly more muscle than non-carriers. For example, carcass muscle weight measured by live animal CT-scanning was 2.8% higher in TM/TM than +/+ lambs (P<0.05), carcass muscle weight measured by carcass CT-scanning was 1.36% higher in TM/+ than +/+ lambs (P<0.05), and weight of fat trimmed from the carcass cuts was significantly lower for TM/+ than +/+ lambs (-11.2%; P<0.05). No negative effects of TM-QTL on carcass traits were found. Optimal commercial use of TM-QTL within the sheep industry would require some consideration, due to the apparently different mode of action of the two main effects of TM-QTL (on growth and muscling).

Background: The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates., Methodology/principal Findings: We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data., Conclusions/significance: These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies.