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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.

Background Genetic selection of individuals that are less susceptible to infection, less infectious once infected, and recover faster, offers an effective and long-lasting solution to reduce the incidence and impact of infectious diseases in farmed animals. However, computational methods for simultaneously estimating genetic parameters for host susceptibility, infectivity and recoverability from real-word data have been lacking. Our previously developed methodology and software tool SIRE 1.0 (Susceptibility, Infectivity and Recoverability Estimator) allows estimation of host genetic effects of a single nucleotide polymorphism (SNP), or other fixed effects (e.g . breed, vaccination status), for these three host traits using individual disease data typically available from field studies and challenge experiments. SIRE 1.0, however, lacks the capability to estimate genetic parameters for these traits in the likely case of underlying polygenic control. Results This paper introduces novel Bayesian methodology and a new software tool SIRE 2.0 for estimating polygenic contributions (i.e. variance components and additive genetic effects) for host susceptibility, infectivity and recoverability from temporal epidemic data, assuming that pedigree or genomic relationships are known. Analytical expressions for prediction accuracies (PAs) for these traits are derived for simplified scenarios, revealing their dependence on genetic and phenotypic variances, and the distribution of related individuals within and between contact groups. PAs for infectivity are found to be critically dependent on the size of contact groups. Validation of the methodology with data from simulated epidemics demonstrates good agreement between numerically generated PAs and analytical predictions. Genetic correlations between infectivity and other traits substantially increase trait PAs. Incomplete data (e.g. time censored or infrequent sampling) generally yield only small reductions in PAs, except for when infection times are completely unknown, which results in a substantial reduction. Conclusions The method presented can estimate genetic parameters for host susceptibility, infectivity and recoverability from individual disease records. The freely available SIRE 2.0 software provides a valuable extension to SIRE 1.0 for estimating host polygenic effects underlying infectious disease transmission. This tool will open up new possibilities for analysis and quantification of genetic determinates of disease dynamics.

Background Genetic linkage maps are useful tools for mapping quantitative trait loci (QTL) influencing variation in traits of interest in a population. Genotyping-by-sequencing approaches such as Restriction-site Associated DNA sequencing (RAD-Seq) now enable the rapid discovery and genotyping of genome-wide SNP markers suitable for the development of dense SNP linkage maps, including in non-model organisms such as Atlantic salmon ( Salmo salar ). This paper describes the development and characterisation of a high density SNP linkage map based on SbfI RAD-Seq SNP markers from two Atlantic salmon reference families. Results Approximately 6,000 SNPs were assigned to 29 linkage groups, utilising markers from known genomic locations as anchors. Linkage maps were then constructed for the four mapping parents separately. Overall map lengths were comparable between male and female parents, but the distribution of the SNPs showed sex-specific patterns with a greater degree of clustering of sire-segregating SNPs to single chromosome regions. The maps were integrated with the Atlantic salmon draft reference genome contigs, allowing the unique assignment of ~4,000 contigs to a linkage group. 112 genome contigs mapped to two or more linkage groups, highlighting regions of putative homeology within the salmon genome. A comparative genomics analysis with the stickleback reference genome identified putative genes closely linked to approximately half of the ordered SNPs and demonstrated blocks of orthology between the Atlantic salmon and stickleback genomes. A subset of 47 RAD-Seq SNPs were successfully validated using a high-throughput genotyping assay, with a correspondence of 97% between the two assays. Conclusions This Atlantic salmon RAD-Seq linkage map is a resource for salmonid genomics research as genotyping-by-sequencing becomes increasingly common. This is aided by the integration of the SbfI RAD-Seq SNPs with existing reference maps and the draft reference genome, as well as the identification of putative genes proximal to the SNPs. Differences in the distribution of recombination events between the sexes is evident, and regions of homeology have been identified which are reflective of the recent salmonid whole genome duplication.

The understanding of host genetic variation in disease resistance increasingly requires the use of field data to obtain sufficient numbers of phenotypes. We introduce concepts necessary for a genetic interpretation of field disease data, for diseases caused by microparasites such as bacteria or viruses. Our focus is on variance component estimation and we introduce epidemiological concepts to quantitative genetics. We have derived simple deterministic formulae to predict the impacts of incomplete exposure to infection, or imperfect diagnostic test sensitivity and specificity on heritabilities for disease resistance. We show that these factors all reduce the estimable heritabilities. The impacts of incomplete exposure depend on disease prevalence but are relatively linear with the exposure probability. For prevalences less than 0.5, imperfect diagnostic test sensitivity results in a small underestimation of heritability, whereas imperfect specificity leads to a much greater underestimation, with the impact increasing as prevalence declines. These impacts are reversed for prevalences greater than 0.5. Incomplete data recording in which infected or diseased individuals are not observed, e.g. data recording for too short a period, has impacts analogous to imperfect sensitivity. These results help to explain the often low disease resistance heritabilities observed under field conditions. They also demonstrate that incomplete exposure to infection, or suboptimal diagnoses, are not fatal flaws for demonstrating host genetic differences in resistance, they merely reduce the power of datasets. Lastly, they provide a tool for inferring the true extent of genetic variation in disease resistance given knowledge of the disease biology.

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.

Infectious pancreatic necrosis (IPN) is a viral disease currently presenting a major problem in the production of Atlantic salmon (Salmon salar). IPN can cause significant mortality to salmon fry within freshwater hatcheries and to smolts following transfer to seawater, although challenged populations show clear genetic variation in resistance. To determine whether this genetic variation includes loci of major effect, a genomewide quantitative trait loci (QTL) scan was performed within 10 full-sib families that had received a natural seawater IPN challenge. To utilize the large difference between Atlantic salmon male and female recombination rates, a two-stage mapping strategy was employed. Initially, a sire-based QTL analysis was used to detect linkage groups with significant effects on IPN resistance, using two to three microsatellite markers per linkage group. A dam-based analysis with additional markers was then used to confirm and position any detected QTL. Two genomewide significant QTL and one suggestive QTL were detected in the genome scan. The most significant QTL was mapped to linkage group 21 and was significant at the genomewide level in both the sire and the dam-based analyses. The identified QTL can be applied in marker-assisted selection programs to improve the resistance of salmon to IPN and reduce disease-related mortality.

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 ).

Background Restriction site-associated DNA sequencing (RAD-Seq) is a genome complexity reduction technique that facilitates large-scale marker discovery and genotyping by sequencing. Recent applications of RAD-Seq have included linkage and QTL mapping with a particular focus on non-model species. In the current study, we have applied RAD-Seq to two Atlantic salmon families from a commercial breeding program. The offspring from these families were classified into resistant or susceptible based on survival/mortality in an Infectious Pancreatic Necrosis (IPN) challenge experiment, and putative homozygous resistant or susceptible genotype at a major IPN-resistance QTL. From each family, the genomic DNA of the two heterozygous parents and seven offspring of each IPN phenotype and genotype was digested with the SbfI enzyme and sequenced in multiplexed pools. Results Sequence was obtained from approximately 70,000 RAD loci in both families and a filtered set of 6,712 segregating SNPs were identified. Analyses of genome-wide RAD marker segregation patterns in the two families suggested SNP discovery on all 29 Atlantic salmon chromosome pairs, and highlighted the dearth of male recombination. The use of pedigreed samples allowed us to distinguish segregating SNPs from putative paralogous sequence variants resulting from the relatively recent genome duplication of salmonid species. Of the segregating SNPs, 50 were linked to the QTL. A subset of these QTL-linked SNPs were converted to a high-throughput assay and genotyped across large commercial populations of IPNV-challenged salmon fry. Several SNPs showed highly significant linkage and association with resistance to IPN, and population linkage-disequilibrium-based SNP tests for resistance were identified. Conclusions We used RAD-Seq to successfully identify and characterise high-density genetic markers in pedigreed aquaculture Atlantic salmon. These results underline the effectiveness of RAD-Seq as a tool for rapid and efficient generation of QTL-targeted and genome-wide marker data in a large complex genome, and its possible utility in farmed animal selection programs.

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies.

Atlantic salmon (Salmo salar L.), a member of the family Salmonidae, is a totemic species of ecological and cultural significance that is also economically important in terms of both sports fisheries and aquaculture. These factors have promoted the continuous development of genomic resources for this species, furthering both fundamental and applied research. MicroRNAs (miRNA) are small endogenous non-coding RNA molecules that control spatial and temporal expression of targeted genes through post-transcriptional regulation. While miRNA have been characterised in detail for many other species, this is not yet the case for Atlantic salmon. To identify miRNAs from Atlantic salmon, we constructed whole fish miRNA libraries for 18 individual juveniles (fry, four months post hatch) and characterised them by Illumina high-throughput sequencing (total of 354,505,167 paired-ended reads). We report an extensive and partly novel repertoire of miRNA sequences, comprising 888 miRNA genes (547 unique mature miRNA sequences), quantify their expression levels in basal conditions, examine their homology to miRNAs from other species and identify their predicted target genes. We also identify the location and putative copy number of the miRNA genes in the draft Atlantic salmon reference genome sequence. The Atlantic salmon miRNAs experimentally identified in this study provide a robust large-scale resource for functional genome research in salmonids. There is an opportunity to explore the evolution of salmonid miRNAs following the relatively recent whole genome duplication event in salmonid species and to investigate the role of miRNAs in the regulation of gene expression in particular their contribution to variation in economically and ecologically important traits.