Nancy E. Raney

Genotype imputation accuracy in a F2 pig population using high density and low density SNP panels

BackgroundF2 resource populations have been used extensively to map QTL segregating between pig breeds. A limitation associated with the use of these resource populations for fine mapping of QTL is the reduced number of founding individuals and recombinations of founding haplotypes occurring in the population. These limitations, however, become advantageous when attempting to impute unobserved genotypes using within family segregation information. A trade-off would be to re-type F2 populations using high density SNP panels for founding individuals and low density panels (tagSNP) in F2 individuals followed by imputation. Subsequently a combined meta-analysis of several populations would provide adequate power and resolution for QTL mapping, and could be achieved at relatively low cost. Such a strategy allows the wealth of phenotypic information that has previously been obtained on experimental resource populations to be further mined for QTL identification. In this study we used experimental and simulated high density genotypes (HD-60K) from an F2 cross to estimate imputation accuracy under several genotyping scenarios.ResultsSelection of tagSNP using physical distance or linkage disequilibrium information produced similar imputation accuracies. In particular, tagSNP sets averaging 1 SNP every 2.1 Mb (1,200 SNP genome-wide) yielded imputation accuracies (IA) close to 0.97. If instead of using custom panels, the commercially available 9K chip is used in the F2, IA reaches 0.99. In order to attain such high imputation accuracy the F0 and F1 generations should be genotyped at high density. Alternatively, when only the F0 is genotyped at HD, while F1 and F2 are genotyped with a 9K panel, IA drops to 0.90.ConclusionsCombining 60K and 9K panels with imputation in F2 populations is an appealing strategy to re-genotype existing populations at a fraction of the cost.

Genome-wide linkage analysis of global gene expression in loin muscle tissue identifies candidate genes in pigs.

Background Nearly 6,000 QTL have been reported for 588 different traits in pigs, more than in any other livestock species. However, this effort has translated into only a few confirmed causative variants. A powerful strategy for revealing candidate genes involves expression QTL (eQTL) mapping, where the mRNA abundance of a set of transcripts is used as the response variable for a QTL scan. Methodology/Principal Findings We utilized a whole genome expression microarray and an F2 pig resource population to conduct a global eQTL analysis in loin muscle tissue, and compared results to previously inferred phenotypic QTL (pQTL) from the same experimental cross. We found 62 unique eQTL (FDR <10%) and identified 3 gene networks enriched with genes subject to genetic control involved in lipid metabolism, DNA replication, and cell cycle regulation. We observed strong evidence of local regulation (40 out of 59 eQTL with known genomic position) and compared these eQTL to pQTL to help identify potential candidate genes. Among the interesting associations, we found aldo-keto reductase 7A2 (AKR7A2) and thioredoxin domain containing 12 (TXNDC12) eQTL that are part of a network associated with lipid metabolism and in turn overlap with pQTL regions for marbling, % intramuscular fat (% fat) and loin muscle area on Sus scrofa (SSC) chromosome 6. Additionally, we report 13 genomic regions with overlapping eQTL and pQTL involving 14 local eQTL. Conclusions/Significance Results of this analysis provide novel candidate genes for important complex pig phenotypes.

Identification of Carcass and Meat Quality QTL in an F2 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 F2 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 F2 animals, 9 chromosomes were selected for genotyping of additional markers. Twenty additional markers were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 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.

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.

Transcriptional profiling during foetal skeletal muscle development of Piau and Yorkshire-Landrace cross-bred pigs.

Skeletal muscle development is a complex process involving the coordinated expression of thousands of genes. The aim of this study was to identify differentially expressed genes in longissimus dorsi (LD) muscle of pigs at 40 and 70 days (d) of gestation (developmental stages encompassing primary and secondary fibre formation) in Yorkshire-Landrace (YL) cross-bred pigs and Piau pigs (a naturalized Brazilian breed), which are two breed types that differ in muscularity. Foetuses were obtained from gilts at each gestational age (n = 3 YL; n = 4 Piau), and transcriptional profiling was performed using the Pigoligoarray microarray containing 20 400 oligonucleotides. A total of 486 oligonucleotides were differentially expressed (fold change (FC) ≥ 1.5; false discovery rate (FDR) ≤ 0.05) between 40 and 70 d gestation in either YL or Piau pigs, and a total of 1300 oligonucleotides were differentially expressed (FC ≥ 1.5; FDR ≤ 0.05) between YL and Piau pigs at either age. Gene ontology annotation and pathway analyses determined functional classifications for differentially expressed genes and revealed breed type-specific developmental expression patterns. Thirteen genes were selected for confirmation by qRT-PCR analyses, and expression patterns for most of these genes were confirmed, providing further insight into the roles of these genes in pig muscle development. This study revealed both developmental and breed type-specific patterns of gene expression in foetal pig skeletal muscle, including genes not previously associated with myogenesis. This information will contribute to future pig genetic improvement efforts.

Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations

BackgroundCurrently, association studies are analysed using statistical mixed models, with marker effects estimated by a linear transformation of genomic breeding values. The variances of marker effects are needed when performing the tests of association. However, approaches used to estimate the parameters rely on a prior variance or on a constant estimate of the additive variance. Alternatively, we propose a standardized test of association using the variance of each marker effect, which generally differ among each other. Random breeding values from a mixed model including fixed effects and a genomic covariance matrix are linearly transformed to estimate the marker effects.ResultsThe standardized test was neither conservative nor liberal with respect to type I error rate (false-positives), compared to a similar test using Predictor Error Variance, a method that was too conservative. Furthermore, genomic predictions are solved efficiently by the procedure, and the p-values are virtually identical to those calculated from tests for one marker effect at a time. Moreover, the standardized test reduces computing time and memory requirements.The following steps are used to locate genome segments displaying strong association. The marker with the highest − log(p-value) in each chromosome is selected, and the segment is expanded one Mb upstream and one Mb downstream of the marker. A genomic matrix is calculated using the information from those markers only, which is used as the variance-covariance of the segment effects in a model that also includes fixed effects and random genomic breeding values. The likelihood ratio is then calculated to test for the effect in every chromosome against a reduced model with fixed effects and genomic breeding values. In a case study with pigs, a significant segment from chromosome 6 explained 11% of total genetic variance.ConclusionsThe standardized test of marker effects using their own variance helps in detecting specific genomic regions involved in the additive variance, and in reducing false positives. Moreover, genome scanning of candidate segments can be used in meta-analyses of genome-wide association studies, as it enables the detection of specific genome regions that affect an economically relevant trait when using multiple populations.

Gene expression profiling in hepatic tissue of newly weaned pigs fed pharmacological zinc and phytase supplemented diets

BackgroundZinc (Zn) is an essential trace element. However, Zn bioavailability from commonly consumed plants may be reduced due to phytic acid. Zn supplementation has been used to treat diarrheal disease in children, and in the U.S. swine industry at pharmacological levels to promote growth and fecal consistency, but underlying mechanisms explaining these beneficial effects remain unknown. Moreover, adding supplemental phytase improves Zn bioavailability. Thus, we hypothesized that benefits of pharmacological Zn supplementation result from changes in gene expression that could be further affected by supplemental phytase. The goal of this study was to investigate the effects of feeding newly weaned pigs dietary Zn (150, 1,000, or 2,000 mg Zn/kg) as Zn oxide with or without phytase [500 phytase units (FTU)/kg] for 14 d on hepatic gene expression. Liver RNA from pigs fed 150, 1,000, or 2,000 mg Zn/kg, or 1,000 mg Zn/kg with phytase (n = 4 per treatment) was reverse transcribed and examined using the differential display reverse transcription polymerase chain reaction technique. Liver RNA from pigs fed 150 or 2,000 mg Zn/kg (n = 4 per treatment) was also evaluated using a 70-mer oligonucleotide microarray.ResultsExpressed sequence tags for 61 putatively differentially expressed transcripts were cloned and sequenced. In addition, interrogation of a 13,297 element oligonucleotide microarray revealed 650 annotated transcripts (FDR ≤ 0.05) affected by pharmacological Zn supplementation. Seven transcripts exhibiting differential expression in pigs fed pharmacological Zn with sequence similarities to genes encoding GLO1, PRDX4, ACY1, ORM1, CPB2, GSTM4, and HSP70.2 were selected for confirmation. Relative hepatic GLO1 (P < 0.0007), PRDX4 (P < 0.009) and ACY1 (P < 0.01) mRNA abundances were confirmed to be greater in pigs fed 1,000 (n = 8) and 2,000 (n = 8) mg Zn/kg than in pigs fed 150 (n = 7) mg Zn/kg. Relative hepatic HSP70.2 (P < 0.002) mRNA abundance was confirmed to be lower in pigs fed 2,000 mg Zn/kg than in pigs fed 150 or 1,000 mg Zn/kg.ConclusionResults suggest that feeding pharmacological Zn (1,000 or 2,000 mg Zn/kg) affects genes involved in reducing oxidative stress and in amino acid metabolism, which are essential for cell detoxification and proper cell function.

Comparative mapping of genes flanking the human chromosome 12 evolutionary breakpoint in the pig.

Genes located on human chromosome 12 (HSA12) are conserved on pig chromosomes 5 and 14 (SSC5 and SSC14), with HSA12q23.3→q24.11 harboring the evolutionary breakpoint between these chromosomes. For this study, pig sequence-tagged sites (STS) were developed for nine HSA12 genes flanking this breakpoint. Radiation hybrid (RH) mapping using the IMpRH panel revealed that COL2A1, DUSP6, KITLG, PAH and STAB2 map to SSC5, while PXN, PLA2G1B, SART3 and TCF1 map to SSC14. Polymorphisms identified in COL2A1, DUSP6, PAH, PLA2G1B and TCF1 were used for genetic linkage mapping and confirmed the map locations for these genes. Our results indicate that the HSA12 evolutionary breakpoint occurs between STAB2 and SART3 in a region spanning less than five million basepairs. These results refine the comparative map of the HSA12 evolutionary breakpoint region and help to further elucidate the extensive gene order rearrangements between HSA12 and SSC5 and 14.

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

BackgroundA 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.ResultsIn 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.ConclusionsAdditional 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.

Association of halothane sensitivity with growth and meat quality in pigs.

Previous reports have indicated that a proportion of pigs, homozygous normal for the skeletal muscle ryanodine receptor gene (RYR1), was halothane sensitive, and this was associated with poor meat quality when pigs were handled aggressively. This study was conducted to evaluate halothane sensitivity in RYR1-normal pigs, managed under simulated commercial conditions, to ascertain the association of halothane sensitivity with growth rate and meat quality. A total of 363 pigs across four farrowing groups, from seven Landrace sires and 38 Yorkshire-Landrace F1 dams, were tested at 8 weeks of age for halothane sensitivity using a closed system that delivered 5% halothane at 2 l/min for 3 (group 1) or 2 (groups 2 to 4) min. After 1 min, limb rigidity, limb tremors and abdominal discoloration were evaluated on a binomial scale with 0 indicating no reaction and 1 indicating reaction. Testing was repeated 2 days later. At 10 weeks of age, pigs were moved to finishing pens and not moved again until marketing. Within farrowing group, pigs were harvested in one of two groups, and at marketing were moved a distance of 91 m, weighed, tattooed, loaded and transported a distance of 550 km to a commercial harvest plant. After overnight rest, pigs were harvested and the pH of the loin muscle was measured at 45 min (pH45) after stunning. After an 18-h chill, loin muscle pH (pHu), International Commission on Illumination (CIE) L*, a*, b*, color (1 to 6) and marbling (1 to 10) scores and fluid loss percent were collected. Generalized linear mixed models were used to estimate repeatabilities for response to halothane challenge. Repeatabilities for limb rigidity for the front right and left legs were 0.24 and 0.31, respectively, whereas rear right and left leg repeatabilities were 0.19 and 0.17, respectively. Repeatabilities for front right and left leg tremors were 0.16 and 0.20, respectively. Growth rate was not influenced by any measure of halothane sensitivity. Carcasses from pigs exhibiting limb rigidity tended to have lower pH45 (5.88 v. 5.97; P = 0.06), similar pHu (5.47 v. 5.49; P = 0.32), less pH decline from 45 min to 18 h (-0.40 v. -0.50; P = 0.04) and a tendency for greater fluid loss percent (5.01 v. 4.55; P = 0.08) than carcasses from pigs that did not exhibit limb rigidity during halothane challenge. A proportion of pigs normal for RYR1 did exhibit limb rigidity during halothane gas challenge, and subsequently tended to have lower 45 min pH and greater longissimus muscle fluid loss post harvest.