Genome-wide association studies for additive and dominance effects for body composition traits in commercial crossbred Piétrain pigs

Fat depth (FD) and muscle depth (MD) are economically important traits and used to estimate carcass lean content (LMP), which is one of the main breeding objectives in pig breeding programmes. We assessed the genetic architectures of body composition traits for additive and dominance effects in commercial crossbred Piétrain pigs using both 50 K array and sequence genotypes. We first performed a genome-wide association study (GWAS) using single-marker association analysis with a false discovery rate of 0.1. Then, we estimated the additive and dominance effects of the most significant variant in the quantitative trait loci (QTL) regions. It was investigated whether the use of whole-genome sequence (WGS) will improve the QTL detection (both additive and dominance) with a higher power compared with lower density SNP arrays. Our results showed that more QTL regions were detected by WGS compared with 50 K array (n = 54 vs. n = 17). Of the novel associated regions associated with FD and LMP and detected by WGS, the most pronounced peak was on SSC13, situated at ~116-118, 121-127 and 129-134 Mbp. Additionally, we found that only additive effects contributed to the genetic architecture of the analysed traits and no significant dominance effects were found for the tested SNPs at QTL regions, regardless of panel density. The associated SNPs are located in or near several relevant candidate genes. Of these genes, GABRR2, GALR1, RNGTT, CDH20 and MC4R have been previously reported as being associated with fat deposition traits. However, the genes on SSC1 (ZNF292, ORC3, CNR1, SRSF12, MDN1, TSHZ1, RELCH and RNF152) and SSC18 (TTC26 and KIAA1549) have not been reported previously to our best knowledge. Our current findings provide insights into the genomic regions influencing composition traits in Piétrain pigs.

Plasma protein levels of young healthy pigs as indicators of disease resilience

Selection for disease resilience, which refers to the ability of an animal to maintain performance when exposed to disease, can reduce the impact of infectious diseases. However, direct selection for disease resilience is challenging because nucleus herds must maintain a high health status. A possible solution is indirect selection of indicators of disease resilience. To search for such indicators, we conducted phenotypic and genetic quantitative analyses of the abundances of 377 proteins in plasma samples from 912 young and visually healthy pigs and their relationships with performance and subsequent disease resilience after natural exposure to a polymicrobial disease challenge. Abundances of 100 proteins were significantly heritable (false discovery rate (FDR) <0.10). The abundance of some proteins was or tended to be genetically correlated (rg) with disease resilience, including complement system proteins (rg = -0.24, FDR = 0.001) and IgG heavy chain proteins (rg = -0.68, FDR = 0.22). Gene set enrichment analyses (FDR < 0.2) based on phenotypic and genetic associations of protein abundances with subsequent disease resilience revealed many pathways related to the immune system that were unfavorably associated with subsequent disease resilience, especially the innate immune system. It was not possible to determine whether the observed levels of these proteins reflected baseline levels in these young and visually healthy pigs or were the result of a response to environmental disturbances that the pigs were exposed to before sample collection. Nevertheless, results show that, under these conditions, the abundance of proteins in some immune-related pathways can be used as phenotypic and genetic predictors of disease resilience and have the potential for use in pig breeding and management.

Applying multi-omics data to study the genetic background of bovine respiratory disease infection in feedlot crossbred cattle

Bovine respiratory disease (BRD) is the most common and costly infectious disease affecting the wellbeing and productivity of beef cattle in North America. BRD is a complex disease whose development is dependent on environmental factors and host genetics. Due to the polymicrobial nature of BRD, our understanding of the genetic and molecular mechanisms underlying the disease is still limited. This knowledge would augment the development of better genetic/genomic selection strategies and more accurate diagnostic tools to reduce BRD prevalence. Therefore, this study aimed to utilize multi-omics data (genomics, transcriptomics, and metabolomics) analyses to study the genetic and molecular mechanisms of BRD infection. Blood samples of 143 cattle (80 BRD; 63 non-BRD animals) were collected for genotyping, RNA sequencing, and metabolite profiling. Firstly, a genome-wide association study (GWAS) was performed for BRD susceptibility using 207,038 SNPs. Two SNPs (Chr5:25858264 and BovineHD1800016801) were identified as associated (p-value <1 × 10^-5) with BRD susceptibility. Secondly, differential gene expression between BRD and non-BRD animals was studied. At the significance threshold used (log₂FC>2, logCPM>2, and FDR<0.01), 101 differentially expressed (DE) genes were identified. These DE genes significantly (p-value <0.05) enriched several immune responses related functions such as inflammatory response. Additionally, we performed expression quantitative trait loci (eQTL) analysis and identified 420 cis-eQTLs and 144 trans-eQTLs significantly (FDR <0.05) associated with the expression of DE genes. Interestingly, eQTL results indicated the most significant SNP (Chr5:25858264) identified via GWAS was a cis-eQTL for DE gene GPR84. This analysis also demonstrated that an important SNP (rs209419196) located in the promoter region of the DE gene BPI significantly influenced the expression of this gene. Finally, the abundance of 31 metabolites was significantly (FDR <0.05) different between BRD and non-BRD animals, and 17 of them showed correlations with multiple DE genes, which shed light on the interactions between immune response and metabolism. This study identified associations between genome, transcriptome, metabolome, and BRD phenotype of feedlot crossbred cattle. The findings may be useful for the development of genomic selection strategies for BRD susceptibility, and for the development of new diagnostic and therapeutic tools.

Imputation to whole-genome sequence and its use in genome-wide association studies for pork colour traits in crossbred and purebred pigs

Imputed whole-genome sequence (WGS) has been proposed to improve genome-wide association studies (GWAS), since all causative mutations responsible for phenotypic variation are expected to be present in the data. This approach was applied on a large number of purebred (PB) and crossbred (CB) pigs for 18 pork color traits to evaluate the impact of using imputed WGS relative to medium-density marker panels. The traits included Minolta A*, B*, and L* for fat (FCOL), quadriceps femoris muscle (QFCOL), thawed loin muscle (TMCOL), fresh ham gluteus medius (GMCOL), ham iliopsoas muscle (ICOL), and longissimus dorsi muscle on the fresh loin (FMCOL). Sequence variants were imputed from a medium-density marker panel (61K for CBs and 50K for PBs) in all genotyped pigs using BeagleV5.0. We obtained high imputation accuracy (average of 0.97 for PBs and 0.91 for CBs). GWAS were conducted for three datasets: 954 CBs and 891 PBs, and the combined CBs and PBs. For most traits, no significant associations were detected, regardless of panel density or population type. However, quantitative trait loci (QTL) regions were only found for a few traits including TMCOL Minolta A* and GMCOL Minolta B* (CBs), FMCOL Minolta B*, FMCOL Minolta L*, and ICOL Minolta B* (PBs) and FMCOL Minolta A*, FMCOL Minolta B*, GMCOL Minolta B*, and ICOL Minolta B* (Combined dataset). More QTL regions were identified with WGS (n = 58) relative to medium-density marker panels (n = 22). Most of the QTL were linked to previously reported QTLs or candidate genes that have been previously reported to be associated with meat quality, pH and pork color; e.g., VIL1, PRKAG3, TTLL4, and SLC11A1, USP37. CTDSP1 gene on SSC15 has not been previously associated with meat color traits in pigs. The findings suggest any added value of WGS was only for detecting novel QTL regions when the sample size is sufficiently large as with the Combined dataset in this study. The percentage of phenotypic variance explained by the most significant SNPs also increased with WGS compared with medium-density panels. The results provide additional insights into identification of a number of candidate regions and genes for pork color traits in different pig populations.

The influence of litter birth weight phenotype on embryonic and placental development at day 30 of gestation in multiparous purebred Large White sows

The aim of this study was to understand the intrauterine biological processes associated with the low litter birth weight phenotype in pigs. Analyses were conducted on reproductive data from a purebred Large White maternal line to identify sows (>2 parities) with repeatable high or low litter birth weight phenotype (HLBWP or LLBWP). A total of 40 sows were selected (n = 20 HLBWP and n = 20 LLBWP) and bred with semen from purebred Large White boars of proven fertility. Sows were euthanized on day 28-30 of gestation (day 29.5 ± 0.6) and samples of placenta and embryos collected. Total number of embryos (TNE), embryonic weight (EW), embryonic viability, and crown-rump (CRL) measurements were recorded, along with the ovulation rate (OR) and allantochorionic fluid volume (AFV). No significant difference was detected (P > 0.05) in OR, TNE, and number of viable embryos on day 30 of gestation between the two groups. There was no significant difference in EW (LLBWP: 0.80 ± 0.05 g; HLBWP: 0.88 ± 0.04 g, P = 0.18) or CRL (LLBWP: 21.5 ± 0.7 mm; HLBWP: 21.9 ± 0.68 mm, P = 0.46). Placental development represented by the average AFV was significantly lower in the LLBWP compared to HLBWP (LLBWP: 131 ± 9.82 mL; HLBWP: 149 ± 9.39 mL, P = 0.03). In conclusion, placental development may be the main factor causing lower BW of entire litters in LLBWP sows.

Genome-wide association study of disease resilience traits from a natural polymicrobial disease challenge model in pigs identifies the importance of the major histocompatibility complex region

Infectious diseases cause tremendous financial losses in the pork industry, emphasizing the importance of disease resilience, which is the ability of an animal to maintain performance under disease. Previously, a natural polymicrobial disease challenge model was established, in which pigs were challenged in the late nursery phase by multiple pathogens to maximize expression of genetic differences in disease resilience. Genetic analysis found that performance traits in this model, including growth rate, feed and water intake, and carcass traits, as well as clinical disease phenotypes, were heritable and could be selected for to increase disease resilience of pigs. The objectives of the current study were to identify genomic regions that are associated with disease resilience in this model, using genome-wide association studies and fine-mapping methods, and to use gene set enrichment analyses to determine whether genomic regions associated with disease resilience are enriched for previously published quantitative trait loci, functional pathways, and differentially expressed genes subject to physiological states. Multiple quantitative trait loci were detected for all recorded performance and clinical disease traits. The major histocompatibility complex region was found to explain substantial genetic variance for multiple traits, including for growth rate in the late nursery (12.8%) and finisher (2.7%), for several clinical disease traits (up to 2.7%), and for several feeding and drinking traits (up to 4%). Further fine mapping identified 4 quantitative trait loci in the major histocompatibility complex region for growth rate in the late nursery that spanned the subregions for class I, II, and III, with 1 single-nucleotide polymorphism in the major histocompatibility complex class I subregion capturing the largest effects, explaining 0.8–27.1% of genetic variance for growth rate and for multiple clinical disease traits. This single-nucleotide polymorphism was located in the enhancer of TRIM39 gene, which is involved in innate immune response. The major histocompatibility complex region was pleiotropic for growth rate in the late nursery and finisher, and for treatment and mortality rates. Growth rate in the late nursery showed strong negative genetic correlations in the major histocompatibility complex region with treatment or mortality rates (−0.62 to −0.85) and a strong positive genetic correlation with growth rate in the finisher (0.79). Gene set enrichment analyses found genomic regions associated with resilience phenotypes to be enriched for previously identified disease susceptibility and immune capacity quantitative trait loci, for genes that were differentially expressed following bacterial or virus infection and immune response, and for gene ontology terms related to immune and inflammatory response. In conclusion, the major histocompatibility complex and other quantitative trait loci that harbor immune-related genes were identified to be associated with disease resilience traits in a large-scale natural polymicrobial disease challenge. The major histocompatibility complex region was pleiotropic for growth rate under challenge and for clinical disease traits. Four quantitative trait loci were identified across the class I, II, and III subregions of the major histocompatibility complex for nursery growth rate under challenge, with 1 single-nucleotide polymorphism in the major histocompatibility complex class I subregion capturing the largest effects. The major histocompatibility complex and other quantitative trait loci identified play an important role in host response to infectious diseases and can be incorporated in selection to improve disease resilience, in particular the identified single-nucleotide polymorphism in the major histocompatibility complex class I subregion.

Integrative analyses of genomic and metabolomic data reveal genetic mechanisms associated with carcass merit traits in beef cattle

Improvement of carcass merit traits is a priority for the beef industry. Discovering DNA variants and genes associated with variation in these traits and understanding biological functions/processes underlying their associations are of paramount importance for more effective genetic improvement of carcass merit traits in beef cattle. This study integrates 10,488,742 imputed whole genome DNA variants, 31 plasma metabolites, and animal phenotypes to identify genes and biological functions/processes that are associated with carcass merit traits including hot carcass weight (HCW), rib eye area (REA), average backfat thickness (AFAT), lean meat yield (LMY), and carcass marbling score (CMAR) in a population of 493 crossbred beef cattle. Regression analyses were performed to identify plasma metabolites associated with the carcass merit traits, and the results showed that 4 (3-hydroxybutyric acid, acetic acid, citric acid, and choline), 6 (creatinine, L-glutamine, succinic acid, pyruvic acid, L-lactic acid, and 3-hydroxybutyric acid), 4 (fumaric acid, methanol, D-glucose, and glycerol), 2 (L-lactic acid and creatinine), and 5 (succinic acid, fumaric acid, lysine, glycine, and choline) plasma metabolites were significantly associated with HCW, REA, AFAT, LMY, and CMAR (P-value < 0.1), respectively. Combining the results of metabolome-genome wide association studies using the 10,488,742 imputed SNPs, 103, 160, 83, 43, and 109 candidate genes were identified as significantly associated with HCW, REA, AFAT, LMY, and CMAR (P-value < 1 × 10^-5), respectively. By applying functional enrichment analyses for candidate genes of each trait, 26, 24, 26, 24, and 28 significant cellular and molecular functions were predicted for HCW, REA, AFAT, LMY, and CMAR, respectively. Among the five topmost significantly enriched biological functions for carcass merit traits, molecular transport and small molecule biochemistry were two top biological functions associated with all carcass merit traits. Lipid metabolism was the most significant biological function for LMY and CMAR and it was also the second and fourth highest biological function for REA and HCW, respectively. Candidate genes and enriched biological functions identified by the integrative analyses of metabolites with phenotypic traits and DNA variants could help interpret the results of previous genome-wide association studies for carcass merit traits. Our integrative study also revealed additional potential novel genes associated with these economically important traits. Therefore, our study improves understanding of the molecular and biological functions/processes that influence carcass merit traits, which could help develop strategies to enhance genomic prediction of carcass merit traits with incorporation of metabolomic data. Similarly, this information could guide management practices, such as nutritional interventions, with the purpose of boosting specific carcass merit traits.

Genetic analysis of disease resilience of wean-to-finish pigs under a natural disease challenge model using reaction norms

Background

Disease resilience is the ability to maintain performance across environments with different disease challenge loads (CL). A reaction norm describes the phenotypes that a genotype can produce across a range of environments and can be implemented using random regression models. The objectives of this study were to: (1) develop measures of CL using growth rate and clinical disease data recorded under a natural polymicrobial disease challenge model; and (2) quantify genetic variation in disease resilience using reaction norm models.

Methods

Different CL were derived from contemporary group effect estimates for average daily gain (ADG) and clinical disease phenotypes, including medical treatment rate (TRT), mortality rate, and subjective health scores. Resulting CL were then used as environmental covariates in reaction norm analyses of ADG and TRT in the challenge nursery and finisher, and compared using model loglikelihoods and estimates of genetic variance associated with CL. Linear and cubic spline reaction norm models were compared based on goodness-of-fit and with multi-variate analyses, for which phenotypes were separated into three traits based on low, medium, or high CL.

Results

Based on model likelihoods and estimates of genetic variance explained by the reaction norm, the best CL for ADG in the nursery was based on early ADG in the finisher, while the CL derived from clinical disease traits across the nursery and finisher was best for ADG in the finisher and for TRT in the nursery and across the nursery and finisher. With increasing CL, estimates of heritability for nursery and finisher ADG initially decreased, then increased, while estimates for TRT generally increased with CL. Genetic correlations for ADG and TRT were low between high versus low CL, but high for close CL. Linear reaction norm models fitted the data significantly better than the standard genetic model without genetic slopes, while the cubic spline model fitted the data significantly better than the linear reaction norm model for most traits. Reaction norm models also fitted the data better than multi-variate models.

Conclusions

Reaction norm models identified genotype-by-environment interactions related to disease CL. Results can be used to select more resilient animals across different levels of CL, high-performance animals at a given CL, or a combination of these.

Breeding for disease resilience: opportunities to manage polymicrobial challenge and improve commercial performance in the pig industry

Disease resilience, defined as an animal's ability to maintain productive performance in the face of infection, provides opportunities to manage the polymicrobial challenge common in pig production. Disease resilience can deliver a number of benefits, including more sustainable production as well as improved animal health and the potential for reduced antimicrobial use. However, little progress has been made to date in the application of disease resilience in breeding programs due to a number of factors, including (1) confusion around definitions of disease resilience and its component traits disease resistance and tolerance, and (2) the difficulty in characterizing such a complex trait consisting of multiple biological functions and dynamic elements of rates of response and recovery from infection. Accordingly, this review refines the definitions of disease resistance, tolerance, and resilience based on previous studies to help improve the understanding and application of these breeding goals and traits under different scenarios. We also describe and summarize results from a "natural disease challenge model" designed to provide inputs for selection of disease resilience. The next steps for managing polymicrobial challenges faced by the pig industry will include the development of large-scale multi-omics data, new phenotyping technologies, and mathematical and statistical methods adapted to these data. Genome editing to produce pigs resistant to major diseases may complement selection for disease resilience along with continued efforts in the more traditional areas of biosecurity, vaccination and treatment. Altogether genomic approaches provide exciting opportunities for the pig industry to overcome the challenges provided by hard-to-manage diseases as well as new environmental challenges associated with climate change.

Improving Chicken Responses to Glycoconjugate Vaccination Against Campylobacter jejuni

Campylobacter jejuni is a common cause of diarrheal disease worldwide. Human infection typically occurs through the ingestion of contaminated poultry products. We previously demonstrated that an attenuated Escherichia coli live vaccine strain expressing the C. jejuni N-glycan on its surface reduced the Campylobacter load in more than 50% of vaccinated leghorn and broiler birds to undetectable levels (responder birds), whereas the remainder of the animals was still colonized (non-responders). To understand the underlying mechanism, we conducted three vaccination and challenge studies using 135 broiler birds and found a similar responder/non-responder effect. Subsequent genome-wide association studies (GWAS), analyses of bird sex and levels of vaccine-induced IgY responses did not correlate with the responder versus non-responder phenotype. In contrast, antibodies isolated from responder birds displayed a higher Campylobacter-opsonophagocytic activity when compared to antisera from non-responder birds. No differences in the N-glycome of the sera could be detected, although minor changes in IgY glycosylation warrant further investigation. As reported before, the composition of the microbiota, particularly levels of OTU classified as Clostridium spp., Ruminococcaceae and Lachnospiraceae are associated with the response. Transplantation of the cecal microbiota of responder birds into new birds in combination with vaccination resulted in further increases in vaccine-induced antigen-specific IgY responses when compared to birds that did not receive microbiota transplants. Our work suggests that the IgY effector function and microbiota contribute to the efficacy of the E. coli live vaccine, information that could form the basis for the development of improved vaccines targeted at the elimination of C. jejuni from poultry.

Relationship between indirect genetic effects for growth, environmental enrichment, coping style and sex with the serum metabolome profile of pigs

Including Indirect Genetic Effects (IGE) in breeding programs to reduce aggression in group housed animals has been proposed. However, the effect of selection for IGE for growth on animal metabolism and physiology is unknown. The purpose of this study was twofold: (1) To investigate the effects of this new breeding method along with two housing (barren and straw), coping style (high and low resisters) and sex (female and castrated males) options on the metabolome profile of pigs. (2) To identify and map biological processes associated with a regrouping test at 9 weeks of age. We used Nuclear Magnetic Resonance to quantify 49 serum metabolites at week 8, 9 and 22. Also, we quantified 3 catecholamines (tyramine, epinephrine, phenylethylamine) and serotonin and three water soluble vitamins (B2, B5 and B7). Overall, no significant differences were observed between negative and positive IGE animals. The magnitude of change (delta) of many metabolites as a response to the regrouping test was significantly affected by IGE, especially that of the amino acids (P < 0.05), being greater in positive IGE pigs. The regrouping test was associated with alteration in glycine, serine and threonine metabolism. In conclusion positive and negative IGE animals respond differently to the regrouping test.

Identification of candidate genes and enriched biological functions for feed efficiency traits by integrating plasma metabolites and imputed whole genome sequence variants in beef cattle

BACKGROUND

Feed efficiency is one of the key determinants of beef industry profitability and sustainability. However, the cellular and molecular background behind feed efficiency is largely unknown. This study combines imputed whole genome DNA variants and 31 plasma metabolites to dissect genes and biological functions/processes that are associated with residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) in beef cattle.

RESULTS

Regression analyses between feed efficiency traits and plasma metabolites in a population of 493 crossbred beef cattle identified 5 (L-valine, lysine, L-tyrosine, L-isoleucine, and L-leucine), 4 (lysine, L-lactic acid, L-tyrosine, and choline), 1 (citric acid), and 4 (L-glutamine, glycine, citric acid, and dimethyl sulfone) plasma metabolites associated with RFI, DMI, ADG, and MWT (P-value < 0.1), respectively. Combining the results of metabolome-genome wide association studies using 10,488,742 imputed SNPs, 40, 66, 15, and 40 unique candidate genes were identified as associated with RFI, DMI, ADG, and MWT (P-value < 1 × 10-5), respectively. These candidate genes were found to be involved in some key metabolic processes including metabolism of lipids, molecular transportation, cellular function and maintenance, cell morphology and biochemistry of small molecules.

CONCLUSIONS

This study identified metabolites, candidate genes and enriched biological functions/processes associated with RFI and its component traits through the integrative analyses of metabolites with phenotypic traits and DNA variants. Our findings could enhance the understanding of biochemical mechanisms of feed efficiency traits and could lead to improvement of genomic prediction accuracy via incorporating metabolite data.

Thyroid hormone suppression in feeder pigs following polymicrobial or porcine reproductive and respiratory syndrome virus-2 challenge

Thyroid hormones are powerful regulators of growth, development, and basal metabolic rate and can be dysregulated under conditions of severe stress or illness. To understand the role of these hormones in porcine disease response, serum samples were obtained from three batches of nursery-aged pigs (n = 208) exposed to a natural polymicrobial disease challenge with an array of bacterial and viral pathogens. Levels of total thyroxin (T4) and triiodothyronine (T3) assessed in sera by radioimmunoassay, decreased significantly by 14 days post-exposure (DPE). Levels of T3 partially rebounded by 48 DPE, while T4 levels remain depressed. Post-exposure T3 and T4 levels were positively correlated with acute and long-term average daily gain (ADG). Cross-sectional sampling of animals maintained at the high health source farms, showed no equivalent change in either hormone when managed under standard industrial conditions. To further elucidate the effect of porcine reproductive and respiratory syndrome virus (PRRSV)-infection on thyroid hormone levels, archived sera over 42 days post inoculation (DPI) from nursery pigs (N = 190) challenged with one of two PRRSV2 strains by the PRRS Host Genetics Consortium were similarly assessed, with animals selected in a two-by-two design, to investigate biological extremes in ADG and viral load (VL). All animals showed a similar decrease in both thyroid hormones reaching a minimum at 7 DPI and returning to near pre-challenge levels by 42 DPI. Post-challenge T3 and T4 levels were significantly greater in high ADG groups, with no significant association with VL or strain. The results of this study demonstrate porcine susceptibility to thyroid disruption in response to disease challenge and demonstrate a relationship between this response and growth performance.

Genetic parameters of drinking and feeding traits of wean-to-finish pigs under a polymicrobial natural disease challenge

Background

The pork industry faces unprecedented challenges from disease, which increases cost of production and use of antibiotics, and reduces production efficiency, carcass quality, and animal wellbeing. One solution is to improve the overall resilience of pigs to a broad array of common diseases through genetic selection. Behavioral changes in feeding and drinking are usually the very first clinical signs when animals are exposed to stressors such as disease. Changes in feeding and drinking behaviors in diseased pigs may reflect the way they cope with the challenge and, thus, could be used as indicator traits to select for disease resilience. The objectives of this study were to estimate genetic parameters of feeding and drinking traits for wean-to-finish pigs in a natural polymicrobial disease challenge model, to estimate genetic correlations of feeding and drinking traits with growth rate and clinical disease traits, and to develop indicator traits to select for disease resilience.

Results

In general, drinking traits had moderate to high estimates of heritability, especially average daily water dispensed, duration, and number of visits (0.44 to 0.58). Similar estimates were observed for corresponding feeding traits (0.35 to 0.51). Most genetic correlation estimates among drinking traits were moderate to high (0.30 to 0.92) and higher than among feeding traits (0 to 0.11). Compared to other drinking traits, water intake duration and number of visits had relatively stronger negative genetic correlation estimates with treatment rate and mortality, especially across the challenge nursery and finisher (− 0.39 and − 0.45 for treatment rate; − 0.20 and − 0.19 for mortality).

Conclusion

Most of the recorded drinking and feeding traits under a severe disease challenge had moderate to high estimates of heritability, especially for feed or water intake duration and number of visits. Phenotypic and genetic correlations among the recorded feeding traits under disease were generally low but drinking traits showed high correlations with each other. Water intake duration and number of visits are potential indicator traits to select for disease resilience because of their high heritability and had moderate genetic correlations with treatment and mortality rates under severe disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00622-x.

Proliferation of peripheral blood mononuclear cells from healthy piglets after mitogen stimulation as indicators of disease resilience

Disease resilience refers to the productivity of an animal under disease. Given the high biosecurity of pig nucleus herds, traits that can be measured on healthy pigs and that are genetically correlated with disease resilience, that is, genetic indicator traits, offer a strategy to select for disease resilience. Our objective was to evaluate mitogen stimulation assays (MSAs) on peripheral blood mononuclear cells (PBMCs) from young healthy pigs as genetic indicators for disease resilience. Data were from a natural disease challenge in which batches of 60 or 75 naïve Yorkshire × Landrace piglets were introduced every 3 wk into a continuous flow barn that was seeded with multiple diseases. In this environment, disease resilience traits, including growth, treatment, and mortality rates, were recorded on 3,136 pigs that were genotyped with a high-density marker panel. PBMCs from 882 of these pigs from 19 batches were isolated from whole blood collected prior to the disease challenge and stimulated with five mitogens: concanavalin A (ConA), phytohemagglutinin (PHA), pokeweed mitogen (PWM), lipopolysaccharide (LPS), and phorbol myristate acetate (PMA). The proliferation of cells was evaluated at 48, 72, and 96 h and compared with unstimulated samples (rest count). Heritabilities of cell proliferation were estimated using a model with batch as a fixed effect and covariates of entry age; rest count; complete blood count proportions of lymphocytes, monocytes, eosinophils, and basophils; and pen, litter, and animal genetics as random effects. Heritability estimates were highest for response to ConA (0.30 ± 0.09, 0.28 ± 0.10, 0.17 ± 0.10, and 0.25 ±0.10 at 48, 72, and 96 h after stimulation and for area under the curve across the three time points, respectively). Estimates were in a similar range for response to PHA and PMA but low for PWM and LPS. Responses to ConA, PHA, and PMA were moderately genetically correlated with several disease resilience traits and in the expected direction, but individual estimates were not significantly different from zero due to large SEs. In conclusion, although validation is needed, MSAss, in particular based on ConA, show promise as genetic indicator traits for disease resilience.

Quantitative analysis of the blood transcriptome of young healthy pigs and its relationship with subsequent disease resilience

Background

Disease resilience, which is the ability of an animal to maintain performance under disease, is important for pigs in commercial herds, where they are exposed to various pathogens. Our objective was to investigate population-level gene expression profiles in the blood of 912 healthy F1 barrows at ~ 27 days of age for associations with performance and health before and after their exposure to a natural polymicrobial disease challenge at ~ 43 days of age.

Results

Most significant (q < 0.20) associations of the level of expression of individual genes in blood of young healthy pigs were identified for concurrent growth rate and subjective health scores prior to the challenge, and for mortality, a combined mortality-treatment trait, and feed conversion rate after the challenge. Gene set enrichment analyses revealed three groups of gene ontology biological process terms that were related to disease resilience: 1) immune and stress response-related terms were enriched among genes whose increased expression was unfavorably associated with both pre- and post-challenge traits, 2) heme-related terms were enriched among genes that had favorable associations with both pre- and post-challenge traits, and 3) terms related to protein localization and viral gene expression were enriched among genes that were associated with reduced performance and health traits after but not before the challenge.

Conclusions

Gene expression profiles in blood from young healthy piglets provide insight into their performance when exposed to disease and other stressors. The expression of genes involved in stress response, heme metabolism, and baseline expression of host genes related to virus propagation were found to be associated with host response to disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07912-8.

Investigating the genetic architecture of disease resilience in pigs by genome-wide association studies of complete blood count traits collected from a natural disease challenge model

Background

Genetic improvement for disease resilience is anticipated to be a practical method to improve efficiency and profitability of the pig industry, as resilient pigs maintain a relatively undepressed level of performance in the face of infection. However, multiple biological functions are known to be involved in disease resilience and this complexity means that the genetic architecture of disease resilience remains largely unknown. Here, we conducted genome-wide association studies (GWAS) of 465,910 autosomal SNPs for complete blood count (CBC) traits that are important in an animal’s disease response. The aim was to identify the genetic control of disease resilience.

Results

Univariate and multivariate single-step GWAS were performed on 15 CBC traits measured from the blood samples of 2743 crossbred (Landrace × Yorkshire) barrows drawn at 2-weeks before, and at 2 and 6-weeks after exposure to a polymicrobial infectious challenge. Overall, at a genome-wise false discovery rate of 0.05, five genomic regions located on Sus scrofa chromosome (SSC) 2, SSC4, SSC9, SSC10, and SSC12, were significantly associated with white blood cell traits in response to the polymicrobial challenge, and nine genomic regions on multiple chromosomes (SSC1, SSC4, SSC5, SSC6, SSC8, SSC9, SSC11, SSC12, SSC17) were significantly associated with red blood cell and platelet traits collected before and after exposure to the challenge. By functional enrichment analyses using Ingenuity Pathway Analysis (IPA) and literature review of previous CBC studies, candidate genes located nearby significant single-nucleotide polymorphisms were found to be involved in immune response, hematopoiesis, red blood cell morphology, and platelet aggregation.

Conclusions

This study helps to improve our understanding of the genetic basis of CBC traits collected before and after exposure to a polymicrobial infectious challenge and provides a step forward to improve disease resilience.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07835-4.

A genome-wide case-control association study of dark cutting in beef cattle

The genetic architecture of dark cutting was investigated with a case-control genome-wide association study on two groups of beef cattle analyzed separately and together (combined group). Groups I (n = 64) and II (n = 150) were genotyped using the 70K GeneSeek Genomic Profiler for Beef Cattle-HD and the 50K Illumina BovineSNP50v2 BeadChip, respectively. Dark cutting was analyzed as a binary trait (case versus control) using logistic regression in an additive model implemented in PLINK version 1.9. Significant loci were not identified when correcting for multiple testing (false discovery rate), suggesting that the trait is not controlled by genes with big effects, or the sample size was not large enough to detect these major genes. Regions harbouring single-nucleotide polymorphisms (SNPs) with a raw p < 0.01 using 1 MB window were analyzed for gene function using the ingenuity pathway analysis. For groups I, II, and the combined group, 449, 301, and 191 SNPs were identified, respectively. Genes identified were involved in pyruvic acid modification and release, 2-deoxyglucose clearance and disposal, sucrose recognition, energy production, and metabolism of carbohydrate. Although detected SNP associations require validation in a large population, results suggested the possibility for marker-assisted or genomic selection of beef cattle to reduce dark cutting.

Genetic analysis of disease resilience in wean-to-finish pigs from a natural disease challenge model

The objective was to estimate the genetic parameters of performance and resilience of growing pigs under disease. Data were from 3,139 Yorkshire × Landrace wean-to-finish pigs that were exposed to a natural polymicrobial disease challenge that was established by entering naturally infected animals into a nursery barn, targeting various viral and bacterial diseases. The challenge was maintained by entering batches of 60 or 75 healthy nursery pigs every 3 wk in a continuous flow system. Traits analyzed included average daily gain (ADG), feed intake (ADFI) and duration (ADFD); feed conversion ratio (FCR); residual feed intake (RFI); mortality (MOR); number of health treatments (TRT); health scores (HScore); carcass weight (CWT), back fat (CBF) and loin depth (CLD); dressing percentage (DRS); lean yield (LYLD); day-to-day variation in feed intake and duration (VARFI and VARDUR); and the proportion of off-feed days (OFFFI and OFFDUR). Analyses were performed by mixed linear models with genomic relationships. The resilience traits, such as TRT, MOR, and HScore, were lowly heritable (up to 0.15) but had high genetic correlations with each other. Performance traits, such as ADG, ADFI, ADFD, FCR, RFI, and carcass traits, were moderate to highly heritable (0.17 to 0.49). Heritabilities of resilience indicator traits such as OFF and VAR had low to moderate heritabilities (0.08 to 0.23) but were higher when based on duration vs. amount. ADFI had a low genetic correlation with ADFD (0.13). ADG in the challenge nursery had stronger negative genetic correlations with both TRT and MOR than ADG in the finisher (-0.37 to -0.74 vs. -0.15 to -0.56). ADFI and FCR had moderate negative (-0.21 to -0.39) and positive (0.34 to 0.49) genetic correlations, respectively, with TRT and MOR. ADFD and RFI had very low genetic correlations with TRT and MOR. CWT and DRS were moderately negatively correlated with TRT and MOR (-0.33 to -0.59). Resilience indicator traits based on feed intake or duration had moderate to high positive genetic correlations with TRT (0.18 to 0.81) and MOR (0.33 to 0.87). In conclusion, performance and resilience traits under a polymicrobial disease challenge are heritable and can be changed by selection. Phenotypes extracted from feed intake patterns can be used as genetic indicator traits for disease resilience. Most promising is day-to-day variation in intake duration, which had a sizeable heritability (0.23) and favorable genetic correlations with MOR (0.79) and treatment rate (0.20).

Genomic Heritability and Genome-Wide Association Studies of Plasma Metabolites in Crossbred Beef Cattle

Metabolites, substrates or products of metabolic processes, are involved in many biological functions, such as energy metabolism, signaling, stimulatory and inhibitory effects on enzymes and immunological defense. Metabolomic phenotypes are influenced by combination of genetic and environmental effects allowing for metabolome-genome-wide association studies (mGWAS) as a powerful tool to investigate the relationship between these phenotypes and genetic variants. The objectives of this study were to estimate genomic heritability and perform mGWAS and in silico functional enrichment analyses for a set of plasma metabolites in Canadian crossbred beef cattle. Thirty-three plasma metabolites and 45,266 single nucleotide polymorphisms (SNPs) were available for 475 animals. Genomic heritability for all metabolites was estimated using genomic best linear unbiased prediction (GBLUP) including genomic breed composition as covariates in the model. A single-step GBLUP implemented in BLUPF90 programs was used to determine SNP P values and the proportion of genetic variance explained by SNP windows containing 10 consecutive SNPs. The top 10 SNP windows that explained the largest genetic variation for each metabolite were identified and mapped to detect corresponding candidate genes. Functional enrichment analyses were performed on metabolites and their candidate genes using the Ingenuity Pathway Analysis software. Eleven metabolites showed low to moderate heritability that ranged from 0.09 ± 0.15 to 0.36 ± 0.15, while heritability estimates for 22 metabolites were zero or negligible. This result indicates that while variations in 11 metabolites were due to genetic variants, the majority are largely influenced by environment. Three significant SNP associations were detected for betaine (rs109862186), L-alanine (rs81117935), and L-lactic acid (rs42009425) based on Bonferroni correction for multiple testing (family wise error rate <0.05). The SNP rs81117935 was found to be located within the Catenin Alpha 2 gene (CTNNA2) showing a possible association with the regulation of L-alanine concentration. Other candidate genes were identified based on additive genetic variance explained by SNP windows of 10 consecutive SNPs. The observed heritability estimates and the candidate genes and networks identified in this study will serve as baseline information for research into the utilization of plasma metabolites for genetic improvement of crossbred beef cattle.

Genomic Analysis of IgG Antibody Response to Common Pathogens in Commercial Sows in Health-Challenged Herds

Losses due to infectious diseases are one of the main factors affecting productivity in the swine industry, motivating the investigation of disease resilience-related traits for genetic selection. However, these traits are not expected to be expressed in the nucleus herds, where selection is performed. One alternative is to use information from the commercial level to identify and select nucleus animals genetically superior for coping with pathogen challenges. In this study, we analyzed the genetic basis of antibody (Ab) response to common infectious pathogens in health-challenged commercial swine herds as potential indicator traits for disease resilience, including Ab response to influenza A virus of swine (IAV), Mycoplasma hyopneumoniae (MH), porcine circovirus (PCV2), and Actinobacillus pleuropneumoniae (APP; different serotypes). Ab response was measured in blood at entry into gilt rearing, post-acclimation (∼40 days after entering the commercial herd), and parities 1 and 2. Heritability estimates for Ab response to IAV, MH, and PCV2 ranged from 0 to 0.76. Ab response to APP ranged from 0 to 0.40. The genetic correlation (r _G ) of Ab response to IAV with MH, PCV2, PRRSV, and APP_mean (average Ab responses for all serotypes of APP) were positive (>0.29) at entry. APP_mean was negatively correlated with PCV2 and MH at entry and parity 2 but positively correlated with MH at post-acclimation and parity 1. Genomic regions associated with Ab response to different APP serotypes were identified on 13 chromosomes. The region on chromosome 14 (2 Mb) was associated with several serotypes of APP, explaining up to 4.3% of the genetic variance of Ab to APP7 at entry. In general, genomic prediction accuracies for Ab response were low to moderate, except average Ab response to all infectious pathogens evaluated. These results suggest that genetic selection of Ab response in commercial sows is possible, but with variable success depending on the trait and the time-point of collection. Future work is needed to determine genetic correlations of Ab response with disease resilience, reproductive performance, and other production traits.

The genetic basis of natural antibody titers of young healthy pigs and relationships with disease resilience

Background

Disease resilience is the ability to maintain performance under pathogen exposure but is difficult to select for because breeding populations are raised under high health. Selection for resilience requires a trait that is heritable, easy to measure on healthy animals, and genetically correlated with resilience. Natural antibodies (NAb) are important parts of the innate immune system and are found to be heritable and associated with disease susceptibility in dairy cattle and poultry. Our objective was to investigate NAb and total IgG in blood of healthy, young pigs as potential indicator traits for disease resilience.

Results

Data were from Yorkshire x Landrace pigs, with IgG and IgM NAb (four antigens) and total IgG measured by ELISA in blood plasma collected ~ 1 week after weaning, prior to their exposure to a natural polymicrobial challenge. Heritability estimates were lower for IgG NAb (0.12 to 0.24, + 0.05) and for total IgG (0.19 + 0.05) than for IgM NAb (0.33 to 0.53, + 0.07) but maternal effects were larger for IgG NAb (0.41 to 0.52, + 0.03) and for total IgG (0.19 + 0.05) than for IgM NAb (0.00 to 0.10, + 0.04). Phenotypically, IgM NAb titers were moderately correlated with each other (average 0.60), as were IgG NAb titers (average 0.42), but correlations between IgM and IgG NAb titers were weak (average 0.09). Phenotypic correlations of total IgG were moderate with NAb IgG (average 0.46) but weak with NAb IgM (average 0.01). Estimates of genetic correlations among NAb showed similar patterns but with small SE, with estimates averaging 0.76 among IgG NAb, 0.63 among IgM NAb, 0.17 between IgG and IgM NAb, 0.64 between total IgG and IgG NAb, and 0.13 between total IgG and IgM NAb. Phenotypically, pigs that survived had slightly higher levels of NAb and total IgG than pigs that died. Genetically, higher levels of NAb tended to be associated with greater disease resilience based on lower mortality and fewer parenteral antibiotic treatments. Genome-wide association analyses for NAb titers identified several genomic regions, with several candidate genes for immune response.

Conclusions

Levels of NAb in blood of healthy young piglets are heritable and potential genetic indicators of resilience to polymicrobial disease.

Genetic relationships of antibody response, viremia level, and weight gain in pigs experimentally infected with porcine reproductive and respiratory syndrome virus1

Genetic and antigenic variability between Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) isolates has encumbered vaccine development. Here, the genetic basis of PRRSV antibody response was assessed using data from experimental infection trials of commercial crossbred weaner pigs across with one of two distinct PRRSV isolates, NVSL-97-7895 (~750 pigs) and KS-2006-72109 (~450 pigs). Objectives were to estimate the genetic parameters of antibody response, measured as the sample to positive ratio (S:P) of PRRSV N-protein specific IgG in serum at 42 d post infection (dpi); assess the relationship of S:P at 42 dpi with serum viremia and growth under infection; and identify genomic regions associated with S:P at 42 dpi. Estimates of heritability of S:P at 42 dpi for NVSL and KS06 were 0.31 ± 0.09 and 0.40 ± 0.10 and appeared to be under similar genetic control (genetic correlation 0.73 ± 0.39). Estimates of genetic correlations of S:P were generally weak with viral load (NVSL: -0.20 ± 0.18; KS06: -0.69 ± 0.20), measured as area under the curve of log10 serum viremia from 0 to 21 dpi, and with weight gain (WG) from 0 to 42 dpi (NVSL: -0.38 ± 0.19; KS06: -0.08 ± 0.25). However, genetic correlations of S:P at 42 dpi with daily serum viremia and with 3-d WG revealed dynamic relationships, with S:P at 42 dpi having the strongest negative genetic correlations with daily viremia when IgG production starts (10-20 dpi), and negative genetic correlations with WG early after infection but positive later on. This suggests that animals that placed more emphasis on immune response early in infection reaped benefits of that later in infection by more effectively clearing the virus. The WUR10000125 SNP on SSC4, previously associated with response to PRRSV, did not have a significant effect on S:P at 42 dpi (P > 0.05) but genotype-specific genetic correlations of S:P with daily viremia and 3-d WG suggested that the lower WG of pigs with the unfavorable AA WUR10000125 genotype may be due to their utilization of a more energetically costly host response compared to pigs with the favorable genotype. Genome-wide association studies identified three SNPs in the Major Histocompatibility Complex associated with S:P that explained ~10 (NVSL) and 45% (KS06) of the genetic variance but were not associated with viremia or WG. In conclusion, antibody response to PRRSV infection is a possible biomarker for improved host response to PRRSV infection.

Exploring Phenotypes for Disease Resilience in Pigs Using Complete Blood Count Data From a Natural Disease Challenge Model

Disease resilience is a valuable trait to help manage infectious diseases in livestock. It is anticipated that improved disease resilience will sustainably increase production efficiency, as resilient animals maintain their performance in the face of infection. The objective of this study was to identify phenotypes related to disease resilience using complete blood count (CBC) data from a wean-to-finish natural disease challenge model, established to mimic the disease pressure caused by many common pathogens at the commercial level of pig production. In total, 2433 F1 crossbred (Landrace × Yorkshire) barrows that went through the natural disease challenge model were classified into four groups (resilient, average, susceptible, and dead) based on their divergent responses in terms of growth and individual treatment. Three sets of blood samples for CBC analysis were drawn at 2-weeks before, and at 2- and 6-weeks after the challenge: Blood 1, Blood 3, and Blood 4 respectively. CBC of Blood 1 taken from healthy pigs before challenge did not show differences between groups. However, resilient animals were found to be primed to initiate a faster adaptive immune response and recover earlier following infection, with greater increases of lymphocyte concentration from Blood 1 to Blood 3 and for hemoglobin concentration and hematocrit from Blood 3 to Blood 4, but a lower neutrophil concentration from Blood 3 to Blood 4 than in susceptible and dead animals (FDR < 0.05). The CBC traits in response to the challenge were found to be heritable and genetically correlated with growth and treatment, which may indicate the potential for developing CBC under disease or commercial conditions as a phenotype in commercial systems as part of developing predictions for disease resilience.

The effects of a globin blocker on the resolution of 3'mRNA sequencing data in porcine blood

Background

Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3’mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq.

Results

In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001).

Conclusions

The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

59 The Genetic Basis of Natural Antibody Titers and Relationships with Disease Resilience in Pigs

Disease resilience is the ability of an animal to maintain performance under pathogen exposure but is difficult to select for because breeding populations are raised in biosecure, high-health facilities. Selection for resilience requires an indicator trait that is easy to measure on healthy young animals, heritable, and genetically correlated with resilience. Our objective was to investigate circulating Natural Antibody (NAb) levels as potential indicators for disease resilience in pigs. Data were from a natural polymicrobial disease challenge, in which batches of 60–75 weaned LWxLR barrows were sourced every three weeks (28 batches, 1799 pigs) from healthy multipliers. NAb and total IgG were evaluated by indirect ELISA in blood samples collected around 35 d of age. Disease resilience data were collected until pigs reached market age. All pigs were genotyped on a 650k panel. Genetic parameters were estimated by univariate and bivariate analyses in ASReml4. Single-marker and Bayesian variable selection methods were used for GWAS. Heritability estimates were lower for IgG NAb (0.03–0.22) than for IgM NAb (0.24–0.42) but maternal effects were larger for IgG (0.49–0.58) than for IgM (0.04–0.12). Phenotypically, IgM titers correlated with each other (0.26–0.71), as did IgG titers (0.40–0.81), but correlations between IgM and IgG were low (0.00–0.13). Genetic correlations showed similar patterns, ranging from 0.44–0.99, 0.45–0.84, and -0.30–0.25 for IgG, IgM, and IgG/IgM, respectively. Genetically, higher levels of NAb tended to be associated with fewer treatments, lower mortality, higher finishing ADG, and lower day-to-day fluctuations in feed intake but SE were large. Phenotypically, pigs that reached market age had significantly higher levels of IgG NAb than pigs that died. GWAS identified several genomic regions for NAb levels. In conclusion, levels of circulating NAb in healthy young piglets are potential indicators of polymicrobial disease resilience. Funded by Genome Canada and Alberta, and by USDA-NIFA.

PSIII-10 Effect of WUR genotype on resilience to a polymicrobial natural disease challenge in pigs

Porcine Reproductive and Respiratory Syndrome (PRRS) is caused by a virus that poses a threat to the global swine industry, costing the U.S. industry over 664 million dollars annually. Vaccination has limited effectiveness due to the virus’ antigenic and genetic shifts. Leveraging genetics to develop more resilient swine can, however, mitigate the effects of PRRS. Previous studies identified a Single Nucleotide Polymorphism (SNP) near the GBP5 gene (WUR) that was associated with resistance and resilience to PRRS, with the G allele being favorable over A. The objective of this study was to determine whether the WUR SNP is also associated with resilience to a polymicrobial natural disease challenge. Using a continuous flow system, a new batch of 60-75 naïve Yorkshire x Landrace nursery piglets was introduced every three weeks into a natural challenge facility that was initially seeded with multiple diseases, including PRRS. Traits recorded were growth rate, feed intake, backfat, loin depth, veterinary treatments, and mortality. Pigs were genotyped using a 600K SNP chip. Data from 2133 pigs were analyzed using a univariate linear mixed model that included, pen, litter, and animal genetics as random effects and WUR genotype as a fixed effect. Frequencies were 0.85, 0.14, and 0.01 for AA, AG, and GG. The G allele was favorable for most traits, with the contrast of AA vs AG significant for average daily gain in the nursery (0.339 vs 0.365 kg/d, p = 0.013) and number of treatments (2.48 vs 2.16 over 180 days, p = 0.072). Mortality rate was 26.0% for AA and 23.8% for AG (not significantly different). In conclusion, the G allele at the WUR SNP is potentially also associated with resilience to multi-factorial disease. Funded by Genome Canada, Genome Alberta, Genome Prairie, PigGen Canada, and USDA-NIFA.

375 Identification of QTL associated with antibody response to common infectious diseases in commercial sows

The objective of this study was to perform genome-wide association studies (GWAS) to identify Quantitative Trait Loci (QTL) associated with antibody response to infectious diseases in commercial sows. A total of 2,848 Large White x Landrace replacement gilts were sourced from 17 high-health multipliers (7 breeding companies; BC) and introduced to 23 commercial farms with a history of common pig diseases, following the standard acclimation procedures with an average of 53 animals per entry group (CG). Serum was used to quantify antibody response to swine influenza virus (SIV), Mycoplasma hyopneumoniae (MH), porcine circovirus type-2 (PCV2), and 8 serotypes of Actinobacillus pleuropneumoniae (APP1-3, 5, 7, 10, 12, and 13) at entry (S/PEntry), following acclimation (S/PAcclimation), and during parities 1 (S/PParity1) and 2 (S/PParity2). All animals were genotyped for 38,191 SNPs. GWAS was performed using BayesB (pi=0.99), with the fixed effect of CG and the random effects of SNPs in the model. For APP, QTL were only identified at S/PAcclimation; on SSC14 (2Mb) for APP3, APP7, APP10, and APP13 that explained 5.6, 4.7, 2.8, and 3.6% of the genetic variance, respectively. A gene within this QTL region is SYK, involved in the control of immune-receptors. For APP5, a QTL that explained 4.2% of the genetic variance was identified on SSC4 (105Mb), which co-localizes with two genes associated with immune-response: SIKE1and NRAS. For SIV, no QTL was identified. A QTL on SSC7 (130-131Mb) was identified for MH (S/PParity1, 5.1%) and PCV2 (S/PEntry, 34%; S/PAcclimation, 43.4%). These results provide new information on the genetic basis of response to infectious diseases in sows. The identified QTL have the potential to be used to select for improved immune response. The authors thanks PigGen Canada, Genome Canada, and the Canadian Swine Health Board for financial support, and the late Dr. Stephen Bishop for his scientific contributions.

PSIII-5 Accuracy of genomic prediction of antibody response to common infectious diseases in commercial sows

Previous results indicated that antibody response to PRRSV has moderate genomic prediction accuracy; however, little is known about this for other common infectious diseases. Therefore, the objective of this study was to estimate the accuracy of genomic prediction for antibody response to infectious diseases in commercial sows. A total of 2,848 Large White x Landrace replacement gilts were sourced from 17 high-health multipliers (7 breeding companies; BC) and introduced to 23 commercial farms with a history of common diseases, following standard acclimation procedures. Serum was used to quantify antibody response to swine influenza virus (SIV), Mycoplasma hyopneumoniae (MH), porcine circovirus type 2 (PCV2), and 8 serotypes of Actinobacilluspleuropneumoniae(APP1-3, 5, 7, 10, 12, and 13) at entry (S/PEntry), following acclimation (S/PAcclimation), and during parities 1 (S/PParity1) and 2 (S/PParity2). All animals were genotyped for 38,191 SNPs. Genomic prediction was performed using BayesB (pi=0.99), with the fixed effect of CG and random effects of SNPs included in the model. Training and validation were performed using 7-fold cross-validation, with data from each BC used as the validation dataset in one-fold. In general, prediction accuracies were low: SIV, from 0.13 (S/PAcclimation) to 0.26 (S/PParity1); MH, -0.07 (S/PAcclimation) to 0.13 (S/PParity2); PCV2, 0.04 (S/PParity1) to 0.32 (S/PAcclimation); APP, -0.08 (S/PEntry, APP10) to 0.26 (S/PAcclimation, APP7). At each point, average accuracies were 0.06 for S/PEntry, 0.09 for S/PAcclimationand S/PParity1, and 0.08 for S/PParity2, showing small increases in accuracy after the acclimation period. Among diseases, average accuracies ranged from 0.01 (APP1) to 0.22 (PCV2). Results show that, overall, the accuracy of genomic prediction of antibody response to common infectious diseases in commercial gilts is limited. The authors thank PigGen Canada, Genome Canada, and the Canadian Swine Health Board for financial support, and the late Dr. Stephen Bishop for his scientific contributions.

PSIII-13 Genetic parameters and the purebred–crossbred genetic correlation for growth, carcass, and meat quality traits in pigs

Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in commercial crossbred pigs and purebred-crossbred genetic correlations are necessary for a successful breeding program. The objectives of this study were to 1) estimate genetic parameters for growth, meat quality and carcass traits in a purebred sire line and related commercial crossbred pigs and 2) estimate the corresponding genetic correlations between purebreds and crossbreds (rpc). We analyzed 115266, 10927 and 43057 purebred records for growth, meat quality (n = 4) and carcass traits (n = 7), respectively. For crossbreds, there were 2000 pigs with growth records, with 900 of them having meat quality and carcass data. A series of univariate and bivariate analyses were used to estimate genetic parameters and rpc. Growth showed moderate heritability (0.20 ± 0.10 to 0.25 ± 0.01) in both purebreds and crossbreds. Heritability estimates for meat quality traits ranged from 0.21 ± 0.03 to 0.42 ± 0.04 in purebreds and from 0.17 ± 0.14 to 0.47 ± 0.15 in crossbreds. Carcass traits had higher heritability estimates in purebreds compared to crossbreds, except for hot carcass weight (0.10 ± 0.02 vs. 0.24 ± 0.16). Genetic correlations among meat quality traits were variable in both populations, whereas genetic correlations among carcass traits were similar in purebreds and crossbreds. Estimates of rpc were high for growth (0.99 ± 0.5) and for meat quality traits (0.94 ± 0.39 to 0.99 ± 0.2), except for Minolta color (-0.48 ± 0.56). Carcass traits had moderate to high estimates of rpc (0.64 ± 0.4 to 0.92 ± 0.3). Carcass fat had a negative estimate of rpc (-0.1 ± 0.5). However, ultrasound fat as an indicator trait for carcass fat had a high positive estimate of rpc (0.88 ± 0.14). Our results indicate that selection in purebreds can be efficient to improve these traits in both purebreds and crossbreds but for some traits, genetic gain can be improved by applying combined crossbred and purebred selection. Funding provided by Genome Canada and the National Research Council.

PSIII-8 Genomic prediction of reproductive performance of commercial sows in health challenged herds

The objective of this study was to perform genomic predictions for reproductive performance of sows under natural health challenge. Reproductive performance (1 to 4 parities) and genotype (~40K SNPs) were available for 2,604 crossbred sows, for a total of 7,635 farrowing records. Animals from 17 high-health multipliers from 7 breeding companies (PigGen Canada) were shipped to 23 commercial farms with recent history of common infectious diseases. Gilts entered farms with an average of 53 animals per contemporary group (CG). Traits included total number of piglets: born (TB), born alive (NBA), stillborn (SB), mummified (MUM), born dead (NBD), and weaned (NW). Genomic predictions were performed using Bayes-B (pi=0.995) with a seven-fold cross-validation using each company in turn for validation and the others for training. The model included the effects of CG (fixed) and SNP (random), and net number of fosters (covariate) for NW. Genomic predictions were done for animal lifetime performance (sum performance of parities) for each trait and using first parity performance as the training set to predict subsequent parity performance. Accuracy was calculated as the weighted average correlation between GEBV and adjusted phenotype across validation sets divided by the square root of heritability. Lifetime performance accuracies were low to moderate, ranging from 0.11 (TB) to 0.45 (NBD). Accuracies using parity 1 to predict subsequent performance were low, ranging from -0.07 (SB in parity 3) to 0.19 (NBD in parity 2), with average accuracies per trait ranging from 0.04 (SB) to 0.16 (NBD).Although most accuracies were low, the moderately high accuracies for some lifetime performance shows that genomic prediction can be used to improve performance under natural health challenge in sows. We appreciate the financial support of PigGen Canada, Canadian Swine Health Board, Genome Alberta and Swine Innovation Porc, and the late Dr. Stephen Bishop for his scientific contributions.

Identification of factors associated with virus level in tonsils of pigs experimentally infected with porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome (PRRS) is one of the most important global swine diseases from both an economic and animal welfare standpoint. PRRS has plagued the US swine industry for over 25 yr, and containment of PRRS virus (PRRSV) has been unsuccessful to date. The primary phase of PRRS, tracked by serum viremia, typically clears between 21 and 42 d postinfection (dpi) but tonsils are a main site of PRRSV persistence and PRRSV can be detected in tonsils in excess of 150 dpi. Measuring tonsil virus (TV) levels at late stages of infection (6 to 7 wk postinfection) can be used to assess tonsil persistence, as levels of virus in tonsil at this time likely influence how long the virus will remain in the tissue. TV levels were measured on pigs experimentally infected with either the NVSL-97-7895 (NVSL; n = 524) or KS-2006-72109 (KS06; n = 328) PRRSV type 2 isolates across five trials. The objectives of this study were to (i) estimate the heritability of TV levels at 35 or 42 dpi; (ii) identify factors the affect TV level, including serum viremia; (iii) identify genomic regions associated with TV level; and (iv) compare results for the two PRRSV isolates. TV level was lowly heritable for both isolates (NVSL: 0.05 ± 0.06; KS06: 0.11 ± 0.10). Level of TV was phenotypically associated with traits related to viral clearance from serum: pigs with low TV levels had an earlier and faster rate of maximal serum viral clearance, lower total serum viral load, and lower viremia level at 35 or 42 dpi. Although no genomic regions with major effects on TV level were identified, several showed some association (>0.1% of total genetic variance in the NVSL-infected dataset, the KS06-infected dataset, and the combined dataset). These regions contained the genes CCL1, CCL2, CCL8, HS3ST3B1, GALNT10, TCF7, C1QA/B/C, HPSE, G0S2, and CD34, which are involved in viral infiltration or replication, immune cell migration, and viral clearance from tissue. Results were similar between the two PRRSV isolates. In conclusion, selection for viral clearance traits in serum may reduce PRRSV persistence in the tonsil across PRRSV isolates. However, genetic correlations need to be estimated to determine whether this will be successful.

Novel Resilience Phenotypes Using Feed Intake Data From a Natural Disease Challenge Model in Wean-to-Finish Pigs

The objective of this study was to extract novel phenotypes related to disease resilience using daily feed intake data from growing pigs under a multifactorial natural disease challenge that was designed to mimic a commercial environment with high disease pressure to maximize expression of resilience. Data used were the first 1,341 crossbred wean-to-finish pigs from a research facility in Québec, Canada. The natural challenge was established under careful veterinary oversight by seeding the facility with diseased pigs from local health-challenged farms, targeting various viral and bacterial diseases, and maintaining disease pressure by entering batches of 60–75 pigs in a continuous flow system. Feed intake (FI) is sensitive to disease, as pigs tend to eat less when they become ill. Four phenotypes were extracted from the individual daily FI data during finishing as novel measures of resilience. The first two were daily variability in FI or FI duration, quantified by the root mean square error (RMSE) from the within individual regressions of FI or duration at the feeder (DUR) on age (RMSE_FI and RMSE_DUR). The other two were the proportion of off-feed days, classified based on negative residuals from a 5% quantile regression (QR) of daily feed intake or duration data on age across all pigs (QR_FI and QR_DUR). Mortality and treatment rate had a heritability of 0.13 (±0.05) and 0.29 (±0.07), respectively. Heritability estimates for RMSE_FI, RMSE_DUR, QR_FI, and QR_DUR were 0.21 (±0.07) 0.26 (±0.07), 0.15 (±0.06), and 0.23 (±0.07), respectively. Genetic correlations of RMSE and QR measures with mortality and treatment rate ranged from 0.37 to 0.85, with QR measures having stronger correlations with both. Estimates of genetic correlations of RMSE measures with production traits were typically low, but often favorable (e.g., −0.31 between RMSE_FI and finishing ADG). Although disease resilience was our target, fluctuations in FI and duration can be caused by many factors other than disease and should be viewed as overall indicators of general resilience to a variety of stressors. In conclusion, daily variation in FI or duration at the feeder can be used as heritable measures of resilience.

Putative Loci Causing Early Embryonic Mortality in Duroc Swine

Lethal recessive alleles that act prenatally may be detected from the absence of homozygous individuals in a population. However, these alleles may be maintained at relatively low frequencies in populations as heterozygotes. In pigs, they may reduce litter size. This study aimed to detect putative lethal variants in the Duroc breed. Phenotypes for the numbers of piglets born (TNB), born live (BA), alive at 24 h (L24), stillborn (SB), and born as mummified fetuses (MM) were available from 5340 recorded litters which resulted from mating of 192 genotyped boars with sows of unknown genotype (dataset 1). An additional 50 litters were produced from parents that were both genotyped (dataset 2). Imputed genotypes of 650K SNPs for 1359 Duroc boars were used in this study. One significant SNP (Bonferroni corrected P = 5.5E-06) was located on SSC14 with 45.3 homozygous individuals expected but none observed. This SNP was significant for mummified fetuses. One hundred fifty two haplotypes were also found to potentially harbor recessive lethal mutations. Twenty-one haplotypes had a significant harmful effect on at least one trait. Two regions, located on SSC8 (144.9–145.5 Mb) and SSC9 (19–19.4 Mb) had significant effects on fertility traits in both datasets. Additionally, regions on SSC1 (82.0–82.8 Mb), SSC3 (73.3–73.7 and 87.1–87.5 Mb) and SSC12 (35.8–36.2 and 50.0–50.5 Mb) had significant deleterious effects on TNB or BA or L24 in dataset 1. Finally, a region on SSC17 (28.7–29.3 Mb) had significant effects on TNB, BA and L24 in dataset 2. A few candidate genes identified within these regions were described as being involved in spermatogenesis and male fertility (TEX14, SEP4, and HSF5), or displayed recessive lethality (CYP26B1, SCD5, and PCF11) in other species. The putative loci detected in this study provide valuable information to potentially increase Duroc litter size by avoiding carrier-by-carrier matings in breeding programs. Further study of the identified candidate genes responsible for such lethal effects may lead to new insights into functions regulating pig fertility.

Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle

BACKGROUND

Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations.

METHODS

Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb.

RESULTS

Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals.

CONCLUSIONS

Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.

Synaptogyrin-2 influences replication of Porcine circovirus 2

Porcine circovirus 2 (PCV2) is a circular single-stranded DNA virus responsible for a group of diseases collectively known as PCV2 Associated Diseases (PCVAD). Variation in the incidence and severity of PCVAD exists between pigs suggesting a host genetic component involved in pathogenesis. A large-scale genome-wide association study of experimentally infected pigs (n = 974), provided evidence of a host genetic role in PCV2 viremia, immune response and growth during challenge. Host genotype explained 64% of the phenotypic variation for overall viral load, with two major Quantitative Trait Loci (QTL) identified on chromosome 7 (SSC7) near the swine leukocyte antigen complex class II locus and on the proximal end of chromosome 12 (SSC12). The SNP having the strongest association, ALGA0110477 (SSC12), explained 9.3% of the genetic and 6.2% of the phenotypic variance for viral load. Dissection of the SSC12 QTL based on gene annotation, genomic and RNA-sequencing, suggested that a missense mutation in the SYNGR2 (SYNGR2 p.Arg63Cys) gene is potentially responsible for the variation in viremia. This polymorphism, located within a protein domain conserved across mammals, results in an amino acid variant SYNGR2 p.63Cys only observed in swine. PCV2 titer in PK15 cells decreased when the expression of SYNGR2 was silenced by specific-siRNA, indicating a role of SYNGR2 in viral replication. Additionally, a PK15 edited clone generated by CRISPR-Cas9, carrying a partial deletion of the second exon that harbors a key domain and the SYNGR2 p.Arg63Cys, was associated with a lower viral titer compared to wildtype PK15 cells (>24 hpi) and supernatant (>48hpi)(P < 0.05). Identification of a non-conservative substitution in this key domain of SYNGR2 suggests that the SYNGR2 p.Arg63Cys variant may underlie the observed genetic effect on viral load.

Modeling heterotic effects in beef cattle using genome-wide SNP-marker genotypes

An objective of commercial beef cattle crossbreeding programs is to simultaneously optimize use of additive (breed differences) and non-additive (heterosis) effects. A total of 6,794 multibreed and crossbred beef cattle with phenotype and Illumina BovineSNP50 genotype data were used to predict genomic heterosis for growth and carcass traits by applying two methods assumed to be linearly proportional to heterosis. The methods were as follows: 1) retained heterozygosity predicted from genomic breed fractions (HET1) and 2) deviation of adjusted crossbred phenotype from midparent value (HET2). Comparison of methods was based on prediction accuracy from cross-validation. Here, a mutually exclusive random sampling of all crossbred animals (n = 5,327) was performed to form five groups replicated five times with approximately 1,065 animals per group. In each run within a replicate, one group was assigned as a validation set, while the remaining four groups were combined to form the reference set. The phenotype of the animals in the validation set was assumed to be unknown; thus, it resulted in every animal having heterosis values that were predicted without using its own phenotype, allowing their adjusted phenotype to be used for validation. The same approach was used to test the impact of predicted heterosis on accuracy of genomic breeding values (GBV). The results showed positive heterotic effects for growth traits but not for carcass traits that reflect the importance of heterosis for growth traits in beef cattle. Heterosis predicted by HET1 method resulted in less variable estimates that were mostly within the range of estimates generated by HET2. Prediction accuracy was greater for HET2 (0.37-0.98) than HET1 (0.34-0.43). Proper consideration of heterosis in genomic evaluation models has debatable effects on accuracy of EBV predictions. However, opportunity exists for predicting heterosis, improving accuracy of genomic selection, and consequently optimizing crossbreeding programs in beef cattle.

Efficacy of genetic parameter estimation of pork loin quality of crossbred commercial pigs using technological quality measurements of frozen and unfrozen product

Meat quality characteristics have been measured on fresh and previously frozen meat as part of genetic studies, but freezing of meat may alter its quality characteristics and, therefore, the relationships between genetic components and meat quality measurements. Pork color, pH, and drip loss measurements performed on longissimus dorsi from the carcasses of 2027 crossbred commercial pigs when either fresh or thawed after frozen storage were used to estimate genetic parameters using a bivariate animal model in ASReml. Meat quality traits measured before and after freezing and thawing were significantly (P < 0.0001) different from each other and intramuscular crude fat content exerted a large effect on the magnitude of change in L* (lightness) and b* (yellowness). Meat quality measurements of fresh pork were moderately to highly heritable except for b* and pH, with heritability estimates for L*, pH, and drip loss greater when measured on fresh rather than frozen-thawed samples. Considering heritability and genetic correlation results, we concluded that whilst either fresh or frozen-thawed pork samples can be used for fresh pork L*, a* (redness), and b* measurements, pH, and possibly drip loss should be measured in fresh pork samples rather than in those that have been frozen-thawed during genetic selection for fresh pork quality.

Development and validation of a small SNP panel for feed efficiency in beef cattle

The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle.

Genomic investigation of porcine periweaning failure to thrive syndrome (PFTS)

Porcine periweaning failure to thrive syndrome (PFTS) can be defined by anorexia, lethargy, progressive debilitation and compulsive behaviours that occur in seemingly healthy pigs within two to threeweeks of weaning in the absence of any known infectious, nutritional, management or environmental factors. A genetic component has been hypothesised for this syndrome. In the present study, 119 commercial pigs (80 cases and 39 controls) were genotyped with the porcine 80K single nucleotide polymorphism-chip and were analysed with logistic regression and two Fixation Index-based approaches. The analyses revealed several regions on chromosomes 1, 3, 6 and 11 with moderate divergence between cases and controls, particularly three haplotypes on SSC3 and 11. The gene-based analyses of the candidate regions revealed the presence of genes that have been reported to be associated with phenotypes like PFST including depression (PDE10A) and intestinal villous atrophy (CUL4A). It is important to increase the effort of collecting more samples to improve the power of these analyses.

Functional Annotation of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture

We describe an emerging initiative - the 'Functional Annotation of All Salmonid Genomes' (FAASG), which will leverage the extensive trait diversity that has evolved since a whole genome duplication event in the salmonid ancestor, to develop an integrative understanding of the functional genomic basis of phenotypic variation. The outcomes of FAASG will have diverse applications, ranging from improved understanding of genome evolution, to improving the efficiency and sustainability of aquaculture production, supporting the future of fundamental and applied research in an iconic fish lineage of major societal importance.

Estimation of genetic parameters for traits associated with reproduction, lactation, and efficiency in sows

Increased milk production due to high litter size, coupled with low feed intake, results in excessive mobilization of sow body reserves during lactation, which can have detrimental effects on future reproductive performance. A possibility to prevent this is to improve sow lactation performance genetically, along with other traits of interest. The aim of this study was to estimate breed-specific genetic parameters (by parity, between parities, and across parities) for traits associated with lactation and reproduction in Yorkshire and Landrace sows. Performance data were available for 2,107 sows with 1 to 3 parities (3,424 farrowings total). Sow back fat, loin depth and BW at farrowing, sow feed intake (SFI), and body weight loss (BWL) during lactation showed moderate heritabilities (0.21 to 0.37) in both breeds, whereas back fat loss (BFL), loin depth loss (LDL), and litter weight gain (LWG) showed low heritabilities (0.12 to 0.18). Among the efficiency traits, sow lactation efficiency showed extremely low heritability (near zero) in Yorkshire sows but a slightly higher (0.05) estimate in Landrace sows, whereas sow residual feed intake (SRFI) and energy balance traits showed moderate heritabilities in both breeds. Genetic correlations indicated that SFI during lactation had strong negative genetic correlations with body resource mobilization traits (BWL, BFL, and LDL; -0.35 to -0.70), and tissue mobilization traits in turn had strong positive genetic correlations with LWG (+0.24 to +0.54; < 0.05). However, SFI did not have a significant genetic correlation with LWG. These genetic correlations suggest that SFI during lactation is predominantly used for reducing sow body tissue losses, rather than for milk production. Estimates of genetic correlations for the same trait measured in parities 1 and 2 ranged from 0.64 to 0.98, which suggests that first and later parities should be treated as genetically different for some traits. Genetic correlations estimated between traits in parities 1 and 2 indicated that BWF and BWL measured in parity 1 can be used as indicator traits for SFI and SRFI measured in parities 1 and 2. In conclusion, traits associated with lactation in sows have a sizable genetic component and show potential for genetic improvement.

Genetic architecture of gene expression underlying variation in host response to porcine reproductive and respiratory syndrome virus infection

It has been shown that inter-individual variation in host response to porcine reproductive and respiratory syndrome (PRRS) has a heritable component, yet little is known about the underlying genetic architecture of gene expression in response to PRRS virus (PRRSV) infection. Here, we integrated genome-wide genotype, gene expression, viremia level, and weight gain data to identify genetic polymorphisms that are associated with variation in inter-individual gene expression and response to PRRSV infection in pigs. RNA-seq analysis of peripheral blood samples collected just prior to experimental challenge (day 0) and at 4, 7, 11 and 14 days post infection from 44 pigs revealed 6,430 differentially expressed genes at one or more time points post infection compared to the day 0 baseline. We mapped genetic polymorphisms that were associated with inter-individual differences in expression at each day and found evidence of cis-acting expression quantitative trait loci (cis-eQTL) for 869 expressed genes (qval < 0.05). Associations between cis-eQTL markers and host response phenotypes using 383 pigs suggest that host genotype-dependent differences in expression of GBP5, GBP6, CCHCR1 and CMPK2 affect viremia levels or weight gain in response to PRRSV infection.

Genomic investigation of piglet resilience following porcine epidemic diarrhea outbreaks

Porcine epidemic diarrhea virus (PEDV) belongs to the Coronaviridae family and causes malabsorptive watery diarrhea, vomiting, dehydration and imbalanced blood electrolytes in pigs. Since the 1970s, PED outbreaks have become a source of problems in pig producing countries all over the world, causing large economic losses for pig producers. Although the infection in adults is not fatal, in naïve suckling piglets mortality is close to 100%. In this study, we investigated genome-wide differences between dead and recovered suckling piglets from commercial farms after PED outbreaks. Samples from 262 animals (156 dead and 106 recovered) belonging to several commercial lines were collected from five different farms in three different countries (USA, Canada and Germany) and genotyped with the porcine 80K SNP chip. Mean F_st value was calculated in 1-Mb non-overlapping windows between dead and recovered individuals, and the results were normalized to find differences within the comparison. Seven windows with high divergence between dead and recovered were detected-five on chromosome 2, one on chromosome 4 and one on chromosome 15-in total encompassing 152 genes. Several of these genes are either under- or overexpressed in many virus infections, including Coronaviridae (such as SARS-CoV). A total of 32 genes are included in one or more Gene Ontology terms that can be related to PED development, such as Golgi apparatus, as well as mechanisms generally linked to resilience or diarrhea development (cell proliferation, ion transport, ATPase activity). Taken together this information provides a first genomic picture of PEDV resilience in suckling piglets.

GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes

The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO‐FAANG) Workshop in Washington, DC on October 7–8, 2015. This consortium is a grass‐roots organization formed to advance the annotation of newly assembled genomes of domesticated and non‐model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO‐FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta‐data analysis standards were established.

Genetic and genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) in gilts and sows

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; QTL_MHC 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 (SNP_All), SNPs in one (SNP_MHC and SNP₁₃₀) or both (SNP_SSC7) QTL, or SNPs outside the QTL (SNP_Rest).

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 (SNP_SSC7, with accuracies of 0.39 and 0.31 for outbreak and GA validation datasets, respectively. Average accuracies for SNP_ALL, SNP_MHC, SNP₁₃₀, and SNP_Rest 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0230-0) contains supplementary material, which is available to authorized users.

Comparison of host genetic factors influencing pig response to infection with two North American isolates of porcine reproductive and respiratory syndrome virus

Background

Porcine reproductive and respiratory syndrome (PRRS) is one of the most important swine diseases in the world and genetic selection of pigs for increased resistance to PRRS is an attractive method to improve the health status of the swine herd. This study compared phenotypic and genetic responses to infection with one of two genetically distinct type 2 PRRS virus (PRRSV) isolates: NVSL-97-7895 (NVSL) and KS-2006-72109 (KS06), and evaluated whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) on chromosome 4 that was associated with viral load and weight gain under infection with NVSL also has an effect on response to infection across North American PRRSV isolates. Wood’s lactation curve was fitted to repeated viremia measurements to derive five curve characteristics that were evaluated.

Results

Infection with NVSL was characterized by reaching a 14 ± 2 % higher peak viremia (PV) 2.5 ± 0.6 days earlier (time to peak; TP) than KS06, followed by 36 ± 1 % faster virus clearance, which occurred 3.9 ± 0.7 days sooner. Weight gain from 0 to 42 days post-infection (WG) tended to be higher under infection with KS06 than NVSL (3.7 ± 1.5 kg). Estimates of heritability were moderate for both PRRSV isolates for viral load from 0 to 21 days post-infection (VL) (NVSL: 0.31 ± 0.06; KS06: 0.51 ± 0.09) and WG (NVSL: 0.33 ± 0.06; KS06: 0.31 ± 0.09). Strong negative genetic correlations were observed between VL and WG for both NVSL (−0.74 ± 0.10) and KS06 (−0.52 ± 0.17) infected pigs. Pigs with genotype AB at the WUR SNP had a more desirable phenotype than AA pigs for all traits under infection with NVSL, but only for VL and PV with KS06; effects on other traits were smaller and not significantly different from zero (P > 0.05). Genetic correlations of host response between isolates were strong for VL, WG and PV. Accounting for WUR genotype had little impact on these correlations, suggesting that response to PRRSV infection has a substantial polygenic component that is common between these two isolates.

Conclusions

These results suggest that the KS06 PRRSV isolate is less virulent than NVSL but that genetic selection for increased resistance to either of these genetically distinct isolates is expected to increase resistance to the other isolate.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0222-0) contains supplementary material, which is available to authorized users.