Genome-wide association analyses of lesion counts in group-housed pigs

Aggression in group-housed pigs is a welfare concern and can negatively affect production. Skin lesions are reliable indicators of aggression and are moderately heritable, suggesting that selective breeding may reduce aggression. To further understand the genetic control of behavioral traits, such as the aggressive response to regrouping, associated single nucleotide polymorphisms (SNPs) can be identified within the genome, and the region in which these SNPs are located can be related to known genes. To investigate SNPs associated with aggression, 1093 purebred Yorkshire pigs were strategically remixed into new groups of familiar and unfamiliar animals at three life stages and lesion counts were recorded. Genomic best linear unbiased prediction (GBLUP) models were fitted for each trait. The genetic additive effect was obtained from a genetic relationship matrix constructed from the 50 924 SNPs. SNP effects and their variances were estimated from the GBLUP objects. SNPs that were associated with a significant portion of the trait variance were identified for lesions to the anterior (three SNPs, FDR <5%) and central (one SNP, FDR <5%) portions of the body in grow-finish pigs. These SNPs were located on chromosome 11, suggesting that chromosome 11 contains a region explaining variation in lesion counts that should be further explored to identify genes underlying biological control of aggression.

Genomic heritability and genome-wide association analysis of anti-Müllerian hormone in Holstein dairy heifers

Anti-Müllerian hormone (AMH) is an ovarian growth factor that plays an important role in regulation of ovarian follicle growth. The objectives of this study were to estimate the genomic heritability of AMH and identify genomic regions associated with AMH production in a genome-wide association (GWA) analysis. Concentrations of AMH were determined in 2,905 dairy Holstein heifers genotyped using the Zoetis medium density panel (Zoetis Inclusions, Kalamazoo, MI) with 54,519 single nucleotide polymorphism (SNP) markers remaining after standard genotype quality control edits. A linear mixed model was used to model the random effects of sampling day and genomics on the logarithm of AMH. The genomic heritability (± standard error of the mean) of AMH was estimated to be 0.36 ± 0.03. Our GWA analysis inferred significant associations between AMH and 11 SNP markers on chromosome 11 and 1 SNP marker on chromosome 20. Annotated genes with significant associations were identified using the Ensembl genome database (version 88) of the cow genome (version UMD 3.1; https://www.ensembl.org/biomart). Gene set enrichment analysis revealed that 2 gene ontology (GO) terms were significantly enriched in the list of candidate genes: G-protein coupled receptor signaling pathway (GO:0007186) and the detection of chemical stimulus involved in sensory perception (GO:0050907). The estimated high heritability and previously established associations between AMH and ovarian follicular reserve, fertility, longevity, and superovulatory response in cattle implies that AMH could be used as a biomarker for genetic improvement of reproductive potential.

Interference of age and supplementation of direct-fed microbial and essential oil in the activity of digestive enzymes and expression of genes related to transport and digestion of carbohydrates and proteins in the small intestine of broilers

The objectives of this study were to describe alterations that age and dietary inclusion of direct-fed microbial (DFM) Bacillus subtilis (BS) and a specific essential oil (EO) blend (carvacrol, cinnamaldehyde, cineol, and pepper extract) causes in the activity of digestive enzymes (maltase: MALT; aminopeptidase-N: APN; intestinal alkaline phosphate: IAP) and expression patterns of genes related to transport (oligopeptide transporter gene: SLC15A1; Na+-dependent glucose and galactose transporter gene: SLC5A1; Na+-independent glucose, galactose, and fructose transporter gene: SLC2A2; ATPase, Na+/K+ transporting gene: ATP1A1) and digestion (aminopeptidase-N gene: ANPEP; maltase-glucoamylase gene: MGAM; Sucrase-isomaltase gene: SI) of carbohydrates and proteins in the small intestine of broilers. Also, the objective was to analyze if growth performance of broilers is affected by supplementation (BS and EO blend). Day-old male broiler chicks (n = 1,320) were assigned to 5 treatments. Diets included a basal diet (BD) as a negative control (CON); experimental diets were BD + BS; BD + BS + EO; BD + EO; BD + antibiotic growth promoter (AGP) avilamycin was the positive control. Performance was evaluated between 1 to 42 d. Transcript abundance of transport-related genes and digestion-related genes were assayed by RT-qPCR and determined at d 7, 21, and 42. MALT-, APN-, and IAP-specific activities were determined at d 7, 21, and 42. Broilers fed BS had greater SLC15A1 mRNA abundance compared to CON, while EO and AGP were related to higher activities of IAP and APN. Analysis over time revealed higher abundance of MGAM, SLC2A2, SLC15A1, SLC5A1 and SI mRNA at d 42 when compared to d 7. Activity of IAP decreased after d 7 and activity of MALT increased with age. The current study suggests that age had effect over carbohydrate and protein transport and carbohydrate digestion. The supplementation of BS DFM hade evident effect over protein transport and that the use of EO in the diet enhanced the activities of carbohydrate and protein digestion, reflecting improvement in digestive and transport physiology of birds. Changes performed by BS DFM and EO did not favor performance.

Estimation of genetic parameters for lesion scores and growth traits in group-housed pigs

Pigs housed in groups are remixed with unfamiliar individuals, which can trigger aggressive interactions, potentially compromising animal welfare. Skin lesions are a reliable indicator trait of aggression and are moderately heritable, suggesting that aggression may be reduced through selection. This study estimated genetic parameters of skin lesions of pigs at multiple life stages, explored genetic correlations of skin lesions between age groups and body location, and studied the relationship between skin lesions and production traits of commercial importance. A population of 1,079 Yorkshire pigs was strategically remixed into new groups of familiar and unfamiliar animals at 3 life stages (weaning, grow-finish, and mature gilts). Skin lesions (fresh, bright red cuts) were counted immediately prior to mixing and 24 h and 3 wk after mixing across 3 body regions: anterior, central, and caudal. Weights were recorded prior to each mixing event. Prior to slaughter, backfat thickness and loin muscle area were determined using ultrasound. Univariate analyses were performed to obtain heritability estimates of lesion scores. Bivariate analyses were performed with response variables being skin lesions, weight gain per life stage, backfat thickness, or loin muscle area, depending on the relationship of interest, to obtain correlations. Lesion score heritabilities ranged from 0.10 to 0.40 and were significant ( < 0.05). Heritability was highest for lesions on the anterior region of the body for 24 h and 3 wk after mixing. Lesions to the central and caudal areas showed the highest genetic correlation at each stage of production, whereas those to the anterior and caudal regions had the lowest correlation. The highest genetic correlation was found between the mature gilt and grow-finish stages, whereas the weaning and mature gilt stages had the lowest correlations. Genetic correlations between lesions and production traits were not significantly different from 0 for weight gain and backfat thickness, but loin muscle area was negatively correlated with lesions ( = 1.17 × 10, = 2.30 × 10, and = 6.08 × 10 for anterior, central, and caudal lesions, respectively). These results are promising for the industry because they suggest that pigs selected for reduced lesions will show increased loin muscle area without negative effects on growth. Alternatively, selection for these production traits would not increase lesions.

Genome-wide association study in an F2 Duroc x Pietrain resource population for economically important meat quality and carcass traits

Meat quality is essential for consumer acceptance, it ultimately impacts pork production profitability and it is subject to genetic control. The objective of this study was to map genomic regions associated with economically important meat quality and carcass traits. We performed a genome-wide association (GWA) analysis to map regions associated with 38 meat quality and carcass traits recorded for 948 F2 pigs from the Michigan State University Duroc × Pietrain resource population. The F0, F1, and 336 F2 pigs were genotyped with the Illumina Porcine SNP60 BeadChip, while the remaining F2 pigs were genotyped with the GeneSeek Genomic Profiler for Porcine Low Desnisty (LD) chip, and imputed with high accuracy ( = 0.97). Altogether the genomic dataset comprised 1,019 animals and 44,911 SNP. A Gaussian linear mixed model was fitted to estimate the breeding values and the variance components. A linear transformation was performed to estimate the marker effects and variances. Type I error rate was controlled at a False Discovery Rate of 5%. Seven putative QTL found in this study were previously reported in other studies. Two novel QTL associated with tenderness (TEN) were located on SSC3 [135.6:137.5Mb; False Discovery rate (FDR) < 0.03] and SSC5 (67.3:69.1Mb; FDR < 0.02). The QTL region identified on SSC15 includes Protein Kinase AMP-activated ɣ 3-subunit gene (), which has been associated with 24-h pH (pH24), drip loss (DL) and cook yield (CY). Also, novel candidate genes were identified for TEN in the region on SSC5 [A Kinase (PRKA) Anchor Protein 3 (], and for tenth rib backfat thickness (BF10) [Carnitine O-Acetyltransferase ()] on SSC1. The association of gene polymorphisms with pork quality traits has been reported for several pig populations. However, there are no SNP for this gene on the chip used, thus we genotyped the animals for 2 non-synonymous variants ( and ). We then performed a GWA conditioning on the genotype of both SNP and was associated with pH24, DL, protein content (PRO) and CY ( < 0.004) and T30N with Juiciness, TEN, shear force, pH24, PRO, and CY < 0.04). Finally, we performed a GWA conditioning on the genotype of the SNP peak detected in this study, and T30N remained associated only with PRO ( < 0.02). Therefore, in this study we identified 2 novel QTL regions, suggest 2 novel candidate genes, and conclude that other SNP in PRKAG3 or nearby gene(s) explain the observed associations on SSC15 in this population.

Refining genomewide association for growth and fat deposition traits in an F pig population

The identification of genomic regions that affect additive genetic variation and contain genes involved in controlling growth and fat deposition has enormous impact in the farm animal industry (e.g., carcass merit and meat quality). Therefore, a genomewide association study was implemented in an F pig population using a 60,000 SNP marker panel for traits related to growth and fat deposition. Estimated genomic EBV were linearly transformed to calculate SNP effects and to identify genomic positions possibly associated with the genetic variability of each trait. Genomic segments were then defined considering the markers included in a region 1 Mb up- and downstream from the SNP with the smallest -value and a false discovery rate < 0.05 for each trait. The significance for each 2-Mb segment was tested using the Bonferroni correction. Significant SNP were detected on SSC2, SSC3, SSC5, and SSC6, but 2-Mb segment significant effects were observed on SSC3 for weight at birth (wt_birth) and on SSC6 for 10th-rib backfat and last-rib backfat measured by ultrasound at different ages. Furthermore, a 6-Mb segment on SSC6 was also considered because the 2-Mb segments for 10 different fat deposition traits were overlapped. Although the segment effects for each trait remain significant, the proportion of additive variance explained by this larger segment was slightly smaller in some traits. In general, the results confirm the presence of genetic variability for wt_birth on SSC3 (18.0-20.2 Mb) and for fat deposition traits on SSC6 (133.8-136.0 Mb). Within these regions, fibrosin () and myosin light chain, phosphorylatable, fast skeletal muscle () genes could be considered as candidates for the wt_birth signal on SSC3, and the SERPINE1 mRNAbinding protein 1 gene () may be a candidate for the fat deposition trait signals on SSC6.

Estimates of the actual relationship between half-sibs in a pig population

Genomic relationships based on markers capture the actual instead of the expected (based on pedigree) proportion of genome shared identical by descent (IBD). Several methods exist to estimate genomic relationships. In this research, we compare four such methods that were tested looking at the empirical distribution of the estimated relationships across 6704 pairs of half-sibs from a cross-bred pig population. The first method based on multiple marker linkage analysis displayed a mean and standard deviation (SD) in close agreement with the expected ones and was robust to changes in the minor allele frequencies (MAF). A single marker method that accounts for linkage disequilibrium (LD) and inbreeding came second, showing more sensitivity to changes in the MAF. Another single marker method that considers neither inbreeding nor LD showed the smallest empirical SD and was the most sensible to changes in MAF. A higher mean and SD were displayed by VanRaden's method, which was not sensitive to changes in MAF. Therefore, the method based on multiple marker linkage analysis and the single marker method that considers LD and inbreeding performed closer to theoretical values and were consistent with the estimates reported in literature for human half-sibs.

Implementing meta-analysis from genome-wide association studies for pork quality traits

Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a meta-analysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining -scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [] and calpastatin []), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit []). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial []) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [] and ferritin, light polypeptide []). Thus, implementation of MA-GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.

Searching for causal networks involving latent variables in complex traits: Application to growth, carcass, and meat quality traits in pigs

Structural equation models (SEQM) can be used to model causal relationships between multiple variables in multivariate systems. Among the strengths of SEQM is its ability to consider causal links between latent variables. The use of latent variables allows modeling complex phenomena while reducing at the same time the dimensionality of the data. One relevant aspect in the quantitative genetics context is the possibility of correlated genetic effects influencing sets of variables under study. Under this scenario, if one aims at inferring causality among latent variables, genetic covariances act as confounders if ignored. Here we describe a methodology for assessing causal networks involving latent variables underlying complex phenotypic traits. The first step of the method consists of the construction of latent variables defined on the basis of prior knowledge and biological interest. These latent variables are jointly evaluated using confirmatory factor analysis. The estimated factor scores are then used as phenotypes for fitting a multivariate mixed model to obtain the covariance matrix of latent variables conditional on the genetic effects. Finally, causal relationships between the adjusted latent variables are evaluated using different SEQM with alternative causal specifications. We have applied this method to a data set with pigs for which several phenotypes were recorded over time. Five different latent variables were evaluated to explore causal links between growth, carcass, and meat quality traits. The measurement model, which included 5 latent variables capturing the information conveyed by 19 different phenotypic traits, showed an acceptable fit to data (e.g., χ/df = 1.3, root-mean-square error of approximation = 0.028, standardized root-mean-square residual = 0.041). Causal links between latent variables were explored after removing genetic confounders. Interestingly, we found that both growth (-0.160) and carcass traits (-0.500) have a significant negative causal effect on quality traits (-value ≤ 0.001). This result may have important implications for strategies for pig production improvement. More generally, the proposed method allows further learning regarding phenotypic causal structures underlying complex traits in farm species.

Comparisons of bone properties and keel deformities between strains and housing systems in end-of-lay hens

Susceptibility of caged layers to osteoporosis and cage layer fatigue has generated interest in newer housing systems that favor increased load-bearing activities. However, high incidences of fractures incurred during lay period have been reported in these newer systems. This study is aimed at determining the housing and strain effects on bone properties: dry weight, percentage ash content, cortical density (CBD), cortical thickness (CBT), and keel bone deformities. Tibia, femur, and keel from Hy-Line Brown (HB), Hy-Line Silver Brown (SB), and Barred Plymouth Rock (BR) hens housed in conventional cages (CC), cage-free (CF), and cage-free with range (outdoor access; R) were studied. At 78 wk, 60 hens from each strain and housing system combination were euthanized and bones were excised for analysis. Quantitative computed tomography (QCT) was used to measure CBD and CBT in each bone. Three-dimensional images of keels were generated from software using QCT scans to analyze the deformities. Tibiae CBT was greater (P < 0.01) in BR compared to other two strains. Between housing systems, CBT was greater (P < 0.05) for mid and distal tibia of R and CF compared to CC. Tibiae and femoral cortex were denser (P < 0.05) in BR compared to HB and SB. There was no effect of housing system for femur CBD, but CBD was greater (P < 0.05) for middle and distal tibia of birds housed in R compared to CC. CBD for keel bone was greater (P < 0.05) in CF and R birds compared to CC birds. The housing system did not influence the dry bone weight and ash percentage of tibiae and femur. Each housing system was associated with high prevalence (>90%) of keel deformities and the housing and genotype influenced the type of deformity. These findings indicate that range and cage-free housing may have beneficial impact on tibia and keel bone integrity compared to conventional cages but the improvement may not be sufficient to prevent fractures or deformities of keel.

A comparison of methods to estimate genomic relationships using pedigree and markers in livestock populations

Accurate prediction of breeding values depends on capturing the variability in genome sharing of relatives with the same pedigree relationship. Here, we compare two approaches to set up genomic relationship matrices for precision of genomic relationships (GR) and accuracy of estimated breeding values (GEBV). Real and simulated data (pigs, 60k SNP) were analysed, and GR were estimated using two approaches: (i) identity by state, corrected with either the observed (G_VR-O ) or the base population (G_VR-B ) allele frequencies and (ii) identity by descent using linkage analysis (G_IBD-L ). Estimators were evaluated for precision and empirical bias with respect to true pedigree IBD GR. All three estimators had very low bias. G_IBD-L displayed the lowest sampling error and the highest correlation with true genome-shared values. G_VR-B approximated G_IBD-L 's correlation and had lower error than G_VR-O . Accuracy of GEBV for selection candidates was significantly higher when G_IBD-L was used and identical between G_VR-O and G_VR-B . In real data, G_IBD-L 's sampling standard deviation was the closest to the theoretical value for each pedigree relationship. Use of pedigree to calculate GR improved the precision of estimates and the accuracy of GEBV.

Meta-analysis of genome-wide association from genomic prediction models

Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.

A comparison of alternative random regression and reaction norm models for whole genome predictions

Whole genome prediction (WGP) based on high density SNP marker panels is known to improve the accuracy of breeding value (BV) prediction in livestock. However, these accuracies can be compromised when genotype by environment interaction (G×E) exists but is not accounted for. Reaction norm (RN) and random regression (RR) models have proven to be useful in accounting for G×E in pre-WGP evaluations by modeling BV as linear or higher order functions of environmental or temporal covariates. We extend these RR/RN models based on several alternative specifications for SNP-specific intercepts and linear slopes on environmental covariates. One specification is based on bivariate normality (BVN) of SNP-specific intercepts and slopes, whereas 2 others, IW-BayesA and based on inverted Wishart (IW) extensions IW-BayesB, are, respectively, bivariate Student t extensions of currently popular models without (BayesA) or with (BayesB) variable selection. We highlight alternative specifications based on the square root free Cholesky decomposition (CD) of SNP-specific variance-covariance (VCV) matrices in an attempt to better differentially model environmentally sensitive from environmentally robust QTL. Two CD specifications were considered with (CD-BayesB) or without (CD-BayesA) any variable selection on intercept and slope effects. We compared each of the 5 models based on an RN simulation study. Six scenarios were considered based on differences in overall genetic correlations between SNP-specific intercept and slope effects as well as on heritabilities and numbers of environmentally robust versus sensitive QTL. In most scenarios, IW-BayesA had the greatest accuracy, whereas CD-BayesB exhibited the greatest accuracy in low complexity architectures (i.e., low number of QTL). In an RR application of a Duroc × Pietrain resource population at Michigan State University, 5,271 SNP markers and 928 F2 animals with known pedigree were analyzed for backfat thickness at wk 10, 13, 16, 19, and 22. SNP-based RR methods had a 2.5% greater (P < 0.0001) cross-validation accuracy for predicting phenotypes than the SNP-based conventional BayesA/BayesB and/or pedigree based RR BLUP; however, none of the proposed RR models had performances that were different from each other.

A comparison of alternative random regression and reaction norm models for whole genome predictions

Whole genome prediction (WGP) based on high density SNP marker panels is known to improve the accuracy of breeding value (BV) prediction in livestock. However, these accuracies can be compromised when genotype by environment interaction (G×E) exists but is not accounted for. Reaction norm (RN) and random regression (RR) models have proven to be useful in accounting for G×E in pre-WGP evaluations by modeling BV as linear or higher order functions of environmental or temporal covariates. We extend these RR/RN models based on several alternative specifications for SNP-specific intercepts and linear slopes on environmental covariates. One specification is based on bivariate normality (BVN) of SNP-specific intercepts and slopes, whereas 2 others, IW-BayesA and based on inverted Wishart (IW) extensions IW-BayesB, are, respectively, bivariate Student t extensions of currently popular models without (BayesA) or with (BayesB) variable selection. We highlight alternative specifications based on the square root free Cholesky decomposition (CD) of SNP-specific variance-covariance (VCV) matrices in an attempt to better differentially model environmentally sensitive from environmentally robust QTL. Two CD specifications were considered with (CD-BayesB) or without (CD-BayesA) any variable selection on intercept and slope effects. We compared each of the 5 models based on an RN simulation study. Six scenarios were considered based on differences in overall genetic correlations between SNP-specific intercept and slope effects as well as on heritabilities and numbers of environmentally robust versus sensitive QTL. In most scenarios, IW-BayesA had the greatest accuracy, whereas CD-BayesB exhibited the greatest accuracy in low complexity architectures (i.e., low number of QTL). In an RR application of a Duroc × Pietrain resource population at Michigan State University, 5,271 SNP markers and 928 F2 animals with known pedigree were analyzed for backfat thickness at wk 10, 13, 16, 19, and 22. SNP-based RR methods had a 2.5% greater (P < 0.0001) cross-validation accuracy for predicting phenotypes than the SNP-based conventional BayesA/BayesB and/or pedigree based RR BLUP; however, none of the proposed RR models had performances that were different from each other.

Effect of rearing environment on bone growth of pullets

Alternative housing systems for laying hens provide mechanical loading and help reduce bone loss. Moreover, achieving greater peak bone mass during pullet phase can be crucial to prevent fractures in the production period. The aim of this study was to determine the housing system effects on bone quality of pullets. Tibiae and humeri of White Leghorn pullets reared in conventional cages (CCs) and a cage-free aviary (AV) system were studied. At 16 wk, 120 birds at random from each housing system were euthanized. Right and left tibiae and humeri were collected and further analyzed. Cortical bone density and thickness were measured using computed tomography. Periosteal and endosteal dimensions were measured at the fracture site during mechanical testing. At 4, 8, 12, and 16 wk, serum concentrations of osteocalcin and hydroxylysyl pyridinoline were analyzed as markers of bone formation and resorption. Cortical bone density was higher (P<0.05) in humeri of AV pullets, and tibiae were denser (P<0.05) for AV pullets in the distal section of the bone compared to CC pullets. Ash content was higher (P<0.05) in AV humeri with no difference in tibiae ash content. Tibiae and humeri of AV pullets had a thicker cortex than the CC pullets (P<0.05). Additionally, the tibiae and humeri of AV pullets had greater (P<0.05) second moment of areas than the CC pullets. While some bone material properties between groups were different (P<0.05), the differences were so small (<7%) that they likely have no clinical significance. Serum osteocalcin concentrations were not different between the treatments, but hydroxylsyl pyridinoline concentrations were higher in CC pullets at 12 wk compared to the AV pullets and the effect reversed at 16 wk (P<0.05). These findings indicate that tibiae and humeri respond differently to load bearing activities during growth. The improved load bearing capability and stiffness in bones of AV pullets were related to increased cross-sectional geometry.

Effect of amino acids supply in reduced crude protein diets on performance, efficiency of mammary uptake, and transporter gene expression in lactating sows

To test the hypothesis that reduction in dietary CP concentration coupled with crystalline AA inclusion increases the efficiency of AA use for milk production, mammary AA arteriovenous concentration differences (A-V), AA transport efficiency (A-V/A × 100), and transcript abundance of AA transporters and milk protein genes were determined in lactating sows fed 1 of 3 diets containing 9.5% (Deficient), 13.5% (Ideal), or 17.5% (Standard) CP, with a similar profile of indispensable and dispensable AA. On d 7 and 18, arterial and mammary venous blood and mammary tissue were sampled postfeeding. Transcript abundance of AA transporters b(0,+)AT (SLC7A9), y(+)LAT2 (SLC7A6), ATB(0,+) (SLC6A14), CAT-1 (SLC7A1), and CAT-2b (SLC7A2) and milk protein β-casein (CSN2) and LALBA (α-lactalbumin) were determined using reverse transcription quantitative PCR. Piglet ADG increased curvilinearly (linear and quadratic, P < 0.03) with increasing percent CP from Deficient to Standard. On d 7, Lys and Arg A-V and transport efficiency increased quadratically (P < 0.05) with increasing percent CP. On d 18, Lys A-V tended to increase (linear, P = 0.08) with increasing percent CP. Increasing CP increased Ile and Val A-V on d 7 (linear, P = 0.05 and P = 0.08, respectively) and Leu and Val on d 18 (linear, P = 0.07 and P = 0.04, respectively). On d 7, plasma concentrations of branched chain AA (BCAA):Lys decreased quadratically (P < 0.05). Expression of genes SLC7A9, SLC7A6, SLC6A14, SLC7A1, SLC7A2, CSN2, and LALBA was unaffected by diet. In conclusion, decreasing the dietary CP from 17.5% to 13.5% with inclusion of crystalline AA did not affect piglet ADG, AA transporter, or milk protein gene expression but increased mammary transport efficiency and A-V of Lys and Arg on d 7 of lactation. This increase was associated with a decrease in plasma concentration of BCAA:Lys, suggesting a competitive mechanism between cationic and BCAA for transport of AA across mammary cells.

A simple analytical and experimental procedure for selection of reference genes for reverse-transcription quantitative PCR normalization data

Variation in cellular activity in a tissue induces changes in RNA concentration, which affects the validity of gene mRNA abundance analyzed by reverse transcription quantitative PCR (RT-qPCR). A common way of accounting for such variation consists of the use of reference genes for normalization. Programs such as geNorm may be used to select suitable reference genes, although a large set of genes that are not co-regulated must be analyzed to obtain accurate results. The objective of this study was to propose an alternative experimental and analytical protocol to assess the invariance of reference genes in porcine mammary tissue using mammary RNA and DNA concentrations as correction factors. Mammary glands were biopsied from 4 sows on d 110 of gestation (prepartum), on d 5 (early) and 17 (peak) of lactation, and on d 5 after weaning (postweaning). Relative expression of 7 potential reference genes, API5, MRPL39, VAPB, ACTB, GAPDH, RPS23, and MTG1, and one candidate gene, SLC7A1, was quantified by RT-qPCR using a relative standard curve approach. Variation in gene expression levels, measured as cycles to threshold at each stage of mammary physiological activity, was tested using a linear mixed model fitting RNA and DNA concentrations as covariates. Results were compared with those obtained with geNorm analysis, and genes selected by each method were used to normalize SLC7A1. Quantified relative mRNA abundance of GAPDH and MRPL39 remained unchanged across stages of mammary physiological activity after accounting for changes in tissue RNA and DNA concentration. In contrast, geNorm analysis selected MTG1, MRPL39, and VAPB as the best reference genes. However, when target gene SLC7A1 was normalized with genes selected either based on our proposed protocol or by geNorm, fold changes in mRNA abundance did not differ. In conclusion, the proposed analytical protocol assesses expression invariance of potential reference genes by accounting for variation in tissue RNA and DNA concentrations and thus represents an alternative method to select suitable reference genes for RT-qPCR analysis.

Identifying putative candidate genes and pathways involved in immune responses to porcine reproductive and respiratory syndrome virus (PRRSV) infection

Differences in gene expression were compared between RNAs from lungs of high (HR) and low (LR) porcine reproductive and respiratory syndrome virus (PRRSV) burden pigs using the swine protein-annotated long oligonucleotide microarray, the Pigoligoarray. Pathway analyses were carried out to determine biological processes, pathways and networks that differ between the LR and HR responses. Differences existed between HR and LR pigs for 16 signalling pathways [P < 0.01/-log (P-value) >1.96]. Top canonical pathways included acute phase response signalling, crosstalk between dendritic cells and natural killer cells and tight junction signalling, with numerous immune response genes that were upregulated (SOCS1, SOD2, RBP4, HLA-B, HLA-G, PPP2R1A and TAP1) or downregulated (IL18, TF, C4BPA, C1QA, C1QB and TYROBP). One mechanism, regulation of complement activation, may have been blocked in HR (PRRSV-susceptible) pigs and could account for the poor clearance of PRRSV by infected macrophages. Multiple inhibiting signals may have prevented effective immune responses in susceptible HR pigs, although some protective genes were upregulated in these pigs. It is likely that in HR pigs, expression of genes associated with protection was delayed, so that the immune response was not stimulated early; thus, PRRSV infection prevented protective immune responses.

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.

Assessment of the swine protein-annotated oligonucleotide microarray

The specificity and utility of the swine protein-annotated oligonucleotide microarray, or Pigoligoarray (http://www.pigoligoarray.org), has been evaluated by profiling the expression of transcripts from four porcine tissues. Tools for comparative analyses of expression on the Pigoligoarray were developed including HGNC identities and comparative mapping alignments with human orthologs. Hybridization results based on the Pigoligoarray's sets of control, perfect match (PM) and deliberate mismatch (MM) probes provide an important means of assessing non-specific hybridization. Simple descriptive diagnostic analyses of PM/MM probe sets are introduced in this paper as useful tools for detecting non-specific hybridization. Samples of RNA from liver, brain stem, longissimus dorsi muscle and uterine endothelium from four pigs were prepared and hybridized to the arrays. Of the total 20,400 oligonucleotides on the Pigoligoarray, 12,429 transcripts were putatively differentially expressed (DE). Analyses for tissue-specific expression [over-expressed in one tissue with respect to all the remaining three tissues (q < 0.01)] identified 958 DE transcripts in liver, 726 in muscle, 286 in uterine endothelium and 1027 in brain stem. These hybridization results were confirmed by quantitative PCR (QPCR) expression patterns for a subset of genes after affirming that cDNA and amplified antisense RNA (aRNA) exhibited similar QPCR results. Comparison to human ortholog expression confirmed the value of this array for experiments of both agricultural importance and for tests using pigs as a biomedical model for human disease.

Optimizing Ovulation to First GnRH Improved Outcomes to Each Hormonal Injection of Ovsynch in Lactating Dairy Cows

Ovulatory response to the first GnRH of Ovsynch is the critical determinant for successful synchronization of ovulation in dairy cows. Our objective in this study was to develop a pre-Ovsynch treatment that increased the percentage of cows that ovulated in response to the first GnRH injection of Ovsynch. To accomplish our goal, we evaluated a hormonal strategy that consisted of PGF2alpha and GnRH before the first GnRH of Ovsynch. Lactating dairy cows (n = 137) were assigned to receive either no treatment before Ovsynch (control) or 25 mg of PGF2alpha (PreP) followed 2 d later by 100 microg of GnRH (PreG), administered 4 (G4G), 5 (G5G), or 6 (G6G) d before initiating the Ovsynch protocol. Transrectal ultrasonography was performed to assess follicular size and resulting ovulation, and blood samples were collected to measure circulating concentrations of progesterone and estradiol immediately before each hormonal injection. Cows were inseminated at a fixed time 16 h after final GnRH of Ovsynch. Pregnancy diagnosis was performed 35 d later by palpation per rectum of uterine contents. Proportion of cows that ovulated to first GnRH of Ovsynch was 56.0, 66.7, 84.6, and 53.8% for G4G, G5G, G6G, and controls, respectively, and was greater for G6G than for control cows. Luteolytic response to PGF2alpha of Ovsynch was greater in all treated than control cows (92.0, 91.7, 96.2, and 69.2% for G4G, G5G, G6G, and control, respectively). Synchronization rate to Ovsynch was greater (92 vs. 69%, respectively) in G6G than in control cows. In addition, cows that ovulated in response to first GnRH of Ovsynch had greater response to PGF2alpha of Ovsynch (92.7 vs. 77.1%, respectively) and greater synchronization rate to the overall protocol (87.9 vs. 62.9%, respectively) than those that did not ovulate. Concentrations of progesterone at PGF2alpha of Ovsynch, and estradiol and follicle size at final GnRH of Ovsynch, were identified as significant predictors of probability of pregnancy 35 d after artificial insemination. In summary, a PGF2alpha-and-GnRH based pre-Ovsynch strategy consisting of a 6-d interval between PreG and first GnRH of Ovsynch resulted in a greater ovulatory and luteolytic response to first GnRH and PGF2alpha of Ovsynch, respectively, compared with control cows. This, in turn, optimized synchronization rate to Ovsynch.

Investigation of changes in global gene expression in the frontal cortex of early-weaned and socially isolated piglets using microarray and quantitative real-time RT-PCR

We hypothesize that early-weaned piglets experience aberrant expression of stress-responsive genes in the frontal cortex, a key brain area involved in cognitive function and behavior organization. To test this hypothesis, female early-weaned piglets (EW; n = 6) were weaned 10 days after birth, while non-weaned piglets (NW; n = 6) were left with their dams. Half of EW (n = 3) and NW (n = 3) animals were socially isolated (SI) for 15 min at 12 days of age, when all animals (n = 12) were euthanized and tissue collected. The effects of EW and SI were examined by gene expression profiling using cDNA microarray hybridizations, generated from a porcine brain cDNA library. A total of 103 genes were differentially expressed (P < 0.05, fold change >1.25) among four direct comparisons. Forty-two genes had known functions, from which 24 showed relevant brain-related functions. Quantitative real-time polymerase chain reaction (Q-RT-PCR) was used to confirm regulation of expression of a subset of 6 genes with important brain functions, selected from the microarray outcomes. In non-weaned animals, a significant suppression of mRNA abundance for carboxypeptidase E, 14-3-3 protein and phosphoprotein enriched in astrocytes 15 kDa was observed in response to SI. Also, in early-weaned animals, diazepam binding inhibitor and actin-related protein 2/3 complex mRNA levels were suppressed in response to SI. Results suggest that social isolation of non- and early-weaned piglets may impact expression of genes involved in regulation of neuronal function, development, and protection in the frontal cortex of young pigs.

Effects of early weaning and social isolation on the expression of glucocorticoid and mineralocorticoid receptor and 11beta-hydroxysteroid dehydrogenase 1 and 2 mRNAs in the frontal cortex and hippocampus of piglets

Pigs weaned at young ages show more abnormal and aggressive behaviors and cognitive deficits compared to later weaned pigs. We investigated the effects of age, weaning and/or social isolation on the expression of genes regulating glucocorticoid response [glucocorticoid receptor (GR), mineralocorticoid receptor (MR), 11beta-hydroxysteroid dehydrogenases 1 and 2 (11beta-HSD1 and 11beta-HSD2)] in the frontal cortex and hippocampus. Early- (EW; n = 6) and conventionally-weaned (CW; n = 6) piglets were weaned at 10 and 21 days after birth, respectively. Non-weaned (NW) piglets of both ages (NW; n = 6/group) remained with their dams. Immediately before euthanasia, half of CW, EW and NW animals were socially isolated for 15 min at 12 (EW, NW) and 23 (CW, NW) days of age. Differences in amounts of 11beta-HSD1, 11beta-HSD2, GR and MR mRNA were determined by quantitative real-time RT-PCR and data subjected to multivariate linear mixed model analysis. When compared with NW piglets at 12 days of age, the hippocampi of EW piglets showed decreased gene expression (P < 0.01). Social isolation decreased gene expression (P < 0.05) in the frontal cortex of all piglets. Twelve-day-old piglets showed higher MR mRNA in the frontal cortex (P < 0.01) and lower 11beta-HSD2 and GR mRNA (P < 0.05) in the hippocampus compared to 23-day-old animals. Results indicate that EW affected the hippocampus of piglets at 12 days of age, while social isolation affected frontal cortex regardless of age. These results may be correlated with behavioral and cognitive changes reported in EW piglets.

Bayesian estimation of genetic parameters for growth and carcass traits of grass-fed beef cattle by Full Conjugate Gibbs

Abstract. Growth and carcass data of Angus cattle were used to estimate heritabilities and genetic and environmental correlations between growth and carcass traits by means of a Bayesian data augmentation (DA) algorithm. Records were taken on 739 Angus steers from 31 sires, during 10 years of a designed progeny test. The cattle were entirely fed on grass during their lifelong. Growth traits evaluated were birth (BW), weaning (WW) and 18-month (W18) weights; and carcass traits were the weights of half the carcass (HCW), of hind "pistola" cut (HPW) and of three retail cuts (ECW). The model used for estimation was a multiple trait additive animal model. The prior densities used in the analyses were the multivariate normal for the fixed effects (with very large variances) and for the breeding values, and the inverted Wishart for the additive and environmental covariance matrices. The observed residual vector was augmented with sampled residuals for missing traits. The total number of samples drawn was 200,000. The heritabilities of growth traits increased with age at measure, and those of carcass traits were of sizeable magnitude. Whereas estimates of the genetic correlations were similar to those found in the literature for cattle fed on concentrates, environmental correlations were lower. Additive correlations between growth traits with either the HPW or ECW, were smaller than the correlations between growth characters and HCW.