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.

CNV Analysis of Host Responses to Porcine Reproductive and Respiratory Syndrome Virus Infection.

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease with a significant impact on the swine industry causing major economic losses. The objective of this study is to examine copy number variations (CNVs) associated with the group-specific host responses to PRRS virus infection. We performed a genome-wide CNV analysis using 660 animals genotyped with on the porcine SNP60 BeadChip and discovered 7097 CNVs and 271 CNV regions (CNVRs). For this study, we used two established traits related to host response to the virus, i.e. viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain (WG42 from 0 to 42 days post infection). To investigate the effects of CNVs on differential host responses to PRRS, we compared groups of animals with extreme high and low estimated breeding values (EBVs) for both traits using a case-control study design. For VL, we identified 163 CNVRs (84 Mb) from the high group and 159 CNVRs (76 Mb) from the low group. For WG42, we detected 126 (68 Mb) and 156 (79 Mb) CNVRs for high and low groups, respectively. Based on gene annotation within group-specific CNVRs, we performed network analyses and observed some potential candidate genes. Our results revealed these group-specific genes are involved in regulating innate and acquired immune response pathways. Specifically, molecules like interferons and interleukins are closely related to host responses to PRRS virus infection.

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.

Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) reveals pathway differences between pigs with alternate genotypes for a major host response QTL.

BACKGROUND: A region on Sus scrofa chromosome 4 (SSC4) surrounding single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) has been reported to be strongly associated with both weight gain and serum viremia in pigs after infection with PRRS virus (PRRSV). A proposed causal mutation in the guanylate binding protein 5 gene (GBP5) is predicted to truncate the encoded protein. To investigate transcriptional differences between WUR genotypes in early host response to PRRSV infection, an RNA-seq experiment was performed on globin depleted whole blood RNA collected on 0, 4, 7, 10 and 14 days post-infection (dpi) from eight littermate pairs with one AB (favorable) and one AA (unfavorable) WUR genotype animal per litter. RESULTS: Gene Ontology (GO) enrichment analysis of transcripts that were differentially expressed (DE) between dpi across both genotypes revealed an inflammatory response for all dpi when compared to day 0. However, at the early time points of 4 and 7dpi, several GO terms had higher enrichment scores compared to later dpi, including inflammatory response (p < 10(-7)), specifically regulation of NFkappaB (p < 0.01), cytokine, and chemokine activity (p < 0.01). At 10 and 14dpi, GO term enrichment indicated a switch to DNA damage response, cell cycle checkpoints, and DNA replication. Few transcripts were DE between WUR genotypes on individual dpi or averaged over all dpi, and little enrichment of any GO term was found. However, there were differences in expression patterns over time between AA and AB animals, which was confirmed by genotype-specific expression patterns of several modules that were identified in weighted gene co-expression network analyses (WGCNA). Minor differences between AA and AB animals were observed in immune response and DNA damage response (p = 0.64 and p = 0.11, respectively), but a significant effect between genotypes pointed to a difference in ion transport/homeostasis and the participation of G-coupled protein receptors (p = 8e-4), which was reinforced by results from regulatory and phenotypic impact factor analyses between genotypes. CONCLUSION: We propose these pathway differences between WUR genotypes are the result of the inability of the truncated GBP5 of the AA genotyped pigs to inhibit viral entry and replication as quickly as the intact GBP5 protein of the AB genotyped pigs.

Association of Insulin-like growth factor binding protein 2 genotypes with growth, carcass and meat quality traits in pigs.

BACKGROUND: This study was conducted to investigate the potential association of variation in the insulin-like growth factor binding protein 2 (IGFBP2) gene with growth, carcass and meat quality traits in pigs. IGFBP2 is a member of the insulin-like growth factor binding protein family that is involved in regulating growth, and it maps to a region of pig chromosome 15 containing significant quantitative trait loci that affect economically important trait phenotypes. RESULTS: An IGFBP2 polymorphism was identified in the Michigan State University (MSU) Duroc × Pietrain F2 resource population (n = 408), and pigs were genotyped by MspI PCR-RFLP. Subsequently, a Duroc pig population from the National Swine Registry, USA, (n = 326) was genotyped using an Illumina Golden Gate assay. The IGFBP2 genotypic frequencies among the MSU resource population pigs were 3.43, 47.06 and 49.51 % for the AA, AB and BB genotypes, respectively. The genotypic frequencies for the Duroc pigs were 9.82, 47.85, and 42.33 % for the AA, AB and BB genotypes, respectively. Genotype effects (P < 0.05) were found in the MSU resource population for backfat thickness at 10(th) rib and last rib as determined by ultrasound at 10, 13, 16 and 19 weeks of age, ADG from 10 to 22 weeks of age, and age to reach 105 kg. A genotype effect (P < 0.05) was also found for off test Longissimus muscle area in the Duroc population. Significant effects of IGFBP2 genotype (P < 0.05) were found for drip loss, 24 h postmortem pH, pH decline from 45 min to 24 h postmortem, subjective color score, CIE L* and b*, Warner-Bratzler shear force, and sensory panel scores for juiciness, tenderness, connective tissue and overall tenderness in MSU resource population pigs. Genotype effects (P < 0.05) were found for 45-min pH, CIE L* and color score in the Duroc population. CONCLUSIONS: Results of this study revealed associations of the IGFBP2 genotypes with growth, carcass and meat quality traits in pigs. The results indicate IGFBP2 as a potential candidate gene for growth rate, backfat thickness, loin muscle area and some pork quality traits.

Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection.

BACKGROUND: The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60 K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so the effect of the WUR10000125 (WUR) genotype on expression in whole blood was also examined. RESULTS: Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4 dpi contrasted with 0 dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. CONCLUSION: There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups.

Identification of a putative quantitative trait nucleotide in guanylate binding protein 5 for host response to PRRS virus infection.

BACKGROUND: Previously, we identified a major quantitative trait locus (QTL) for host response to Porcine Respiratory and Reproductive Syndrome virus (PRRSV) infection in high linkage disequilibrium (LD) with SNP rs80800372 on Sus scrofa chromosome 4 (SSC4). RESULTS: Within this QTL, guanylate binding protein 5 (GBP5) was differentially expressed (DE) (p < 0.05) in blood from AA versus AB rs80800372 genotyped pigs at 7,11, and 14 days post PRRSV infection. All variants within the GBP5 transcript in LD with rs80800372 exhibited allele specific expression (ASE) in AB individuals (p < 0.0001). A transcript re-assembly revealed three alternatively spliced transcripts for GBP5. An intronic SNP in GBP5, rs340943904, introduces a splice acceptor site that inserts five nucleotides into the transcript. Individuals homozygous for the unfavorable AA genotype predominantly produced this transcript, with a shifted reading frame and early stop codon that truncates the 88 C-terminal amino acids of the protein. RNA-seq analysis confirmed this SNP was associated with differential splicing by QTL genotype (p < 0.0001) and this was validated by quantitative capillary electrophoresis (p < 0.0001). The wild-type transcript was expressed at a higher level in AB versus AA individuals, whereas the five-nucleotide insertion transcript was the dominant form in AA individuals. Splicing and ASE results are consistent with the observed dominant nature of the favorable QTL allele. The rs340943904 SNP was also 100 % concordant with rs80800372 in a validation population that possessed an alternate form of the favorable B QTL haplotype. CONCLUSIONS: GBP5 is known to play a role in inflammasome assembly during immune response. However, the role of GBP5 host genetic variation in viral immunity is novel. These findings demonstrate that rs340943904 is a strong candidate causal mutation for the SSC4 QTL that controls variation in host response to PRRSV.

Increasing gene discovery and coverage using RNA-seq of globin RNA reduced porcine blood samples.

BACKGROUND: Transcriptome analysis of porcine whole blood has several applications, which include deciphering genetic mechanisms for host responses to viral infection and vaccination. The abundance of alpha- and beta-globin transcripts in blood, however, impedes the ability to cost-effectively detect transcripts of low abundance. Although protocols exist for reduction of globin transcripts from human and mouse/rat blood, preliminary work demonstrated these are not useful for porcine blood Globin Reduction (GR). Our objectives were to develop a porcine specific GR protocol and to evaluate the GR effects on gene discovery and sequence read coverage in RNA-sequencing (RNA-seq) experiments. RESULTS: A GR protocol for porcine blood samples was developed using RNase H with antisense oligonucleotides specifically targeting porcine hemoglobin alpha (HBA) and beta (HBB) mRNAs. Whole blood samples (n = 12) collected in Tempus tubes were used for evaluating the efficacy and effects of GR on RNA-seq. The HBA and HBB mRNA transcripts comprised an average of 46.1% of the mapped reads in pre-GR samples, but those reads reduced to an average of 8.9% in post-GR samples. Differential gene expression analysis showed that the expression level of 11,046 genes were increased, whereas 34 genes, excluding HBA and HBB, showed decreased expression after GR (FDR <0.05). An additional 815 genes were detected only in post-GR samples. CONCLUSIONS: Our porcine specific GR primers and protocol minimize the number of reads of globin transcripts in whole blood samples and provides increased coverage as well as accuracy and reproducibility of transcriptome analysis. Increased detection of low abundance mRNAs will ensure that studies relying on transcriptome analyses do not miss information that may be vital to the success of the study.

Evaluation of QTL for carcass merit and meat quality traits in a US commercial Duroc population.

Putative quantitative trait loci (QTL) regions on 5 chromosomes (SSC3, 6, 12, 15, and 18) were selected from our previous genome scans of a Duroc×Pietrain F(2) resource population for further evaluation in a US commercial Duroc population (n=331). A total of 81 gene-specific single nucleotide polymorphism (SNP) markers were genotyped and 33 markers were segregating. The MDH1 SNP on SSC3 was associated with 45-min and ultimate pH (pHu), and pH decline. PRKAG3 on SSC15 was associated with pHu. The HSPG2 SNP on SSC6 was associated with marbling score and days to 113kg. Markers for NUP88 and FKBP10 on SSC12 were associated with 45-min pH and L*, respectively. The SSC15 marker SF3B1 was associated with L* and LMA, and the SSC18 marker ARF5 was associated with pHu and color score. These results in a commercial Duroc population showed a general consistency with our previous genome scan.

Characterizing differential individual response to porcine reproductive and respiratory syndrome virus infection through statistical and functional analysis of gene expression.

We evaluated differences in gene expression in pigs from the Porcine Reproductive and Respiratory Syndrome (PRRS) Host Genetics Consortium initiative showing a range of responses to PRRS virus infection. Pigs were allocated into four phenotypic groups according to their serum viral level and weight gain. RNA obtained from blood at 0, 4, 7, 11, 14, 28, and 42 days post-infection (DPI) was hybridized to the 70-mer 20K Pigoligoarray. We used a blocked reference design for the microarray experiment. This allowed us to account for individual biological variation in gene expression, and to assess baseline effects before infection (0 DPI). Additionally, this design has the flexibility of incorporating future data for differential expression analysis. We focused on evaluating transcripts showing significant interaction of weight gain and serum viral level. We identified 491 significant comparisons [false discovery rate (FDR) = 10%] across all DPI and phenotypic groups. We corroborated the overall trend in direction and level of expression (measured as fold change) at 4 DPI using qPCR (r = 0.91, p ≤ 0.0007). At 4 and 7 DPI, network and functional analyses were performed to assess if immune related gene sets were enriched for genes differentially expressed (DE) across four phenotypic groups. We identified cell death function as being significantly associated (FDR ≤ 5%) with several networks enriched for DE transcripts. We found the genes interferon-alpha 1(IFNA1), major histocompatibility complex, class II, DQ alpha 1 (SLA-DQA1), and major histocompatibility complex, class II, DR alpha (SLA-DRA) to be DE (p ≤ 0.05) between phenotypic groups. Finally, we performed a power analysis to estimate sample size and sampling time-points for future experiments. We concluded the best scenario for investigation of early response to PRRSV infection consists of sampling at 0, 4, and 7 DPI using about 30 pigs per phenotypic group.

Identification of Carcass and Meat Quality QTL in an F(2) Duroc × Pietrain Pig Resource Population Using Different Least-Squares Analysis Models.

A three-generation resource population was constructed by crossing pigs from the Duroc and Pietrain breeds. In this study, 954 F(2) animals were used to identify quantitative trait loci (QTL) affecting carcass and meat quality traits. Based on results of the first scan analyzed with a line-cross (LC) model using 124 microsatellite markers and 510 F(2) animals, 9 chromosomes were selected for genotyping of additional markers. Twenty additional markers were genotyped for 954 F(2) animals and 20 markers used in the first scan were genotyped for 444 additional F(2) animals. Three different Mendelian models using least-squares for QTL analysis were applied for the second scan: a LC model, a half-sib (HS) model, and a combined LC and HS model. Significance thresholds were determined by false discovery rate (FDR). In total, 50 QTL using the LC model, 38 QTL using the HS model, and 3 additional QTL using the combined LC and HS model were identified (q < 0.05). The LC and HS models revealed strong evidence for QTL regions on SSC6 for carcass traits (e.g., 10th-rib backfat; q < 0.0001) and on SSC15 for meat quality traits (e.g., tenderness, color, pH; q < 0.01), respectively. QTL for pH (SSC3), dressing percent (SSC7), marbling score and moisture percent (SSC12), CIE a* (SSC16), and carcass length and spareribs weight (SSC18) were also significant (q < 0.01). Additional marker and animal genotypes increased the statistical power for QTL detection, and applying different analysis models allowed confirmation of QTL and detection of new QTL.

Application of alternative models to identify QTL for growth traits in an F2 Duroc x Pietrain pig resource population.

BACKGROUND: A variety of analysis approaches have been applied to detect quantitative trait loci (QTL) in experimental populations. The initial genome scan of our Duroc x Pietrain F2 resource population included 510 F2 animals genotyped with 124 microsatellite markers and analyzed using a line-cross model. For the second scan, 20 additional markers on 9 chromosomes were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 animals. Three least-squares Mendelian models for QTL analysis were applied for the second scan: a line-cross model, a half-sib model, and a combined line-cross and half-sib model. RESULTS: In total, 26 QTL using the line-cross model, 12 QTL using the half-sib model and 3 additional QTL using the combined line-cross and half-sib model were detected for growth traits with a 5% false discovery rate (FDR) significance level. In the line-cross analysis, highly significant QTL for fat deposition at 10-, 13-, 16-, 19-, and 22-wk of age were detected on SSC6. In the half-sib analysis, a QTL for loin muscle area at 19-wk of age was detected on SSC7 and QTL for 10th-rib backfat at 19- and 22-wk of age were detected on SSC15. CONCLUSIONS: Additional markers and animals contributed to reduce the confidence intervals and increase the test statistics for QTL detection. Different models allowed detection of new QTL which indicated differing frequencies for alternative alleles in parental breeds.