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Background: Residual feed intake (RFI), a measure of feed efficiency, is the difference between observed feed intake and the expected feed requirement predicted from growth and maintenance. Pigs with low RFI have reduced feed costs without compromising their growth. Identification of genes or genetic markers associated with RFI will be useful for marker-assisted selection at an early age of animals with improved feed efficiency., Methodology/principal Findings: Whole genome association studies (WGAS) for RFI, average daily feed intake (ADFI), average daily gain (ADG), back fat (BF) and loin muscle area (LMA) were performed on 1,400 pigs from the divergently selected ISU-RFI lines, using the Illumina PorcineSNP60 BeadChip. Various statistical methods were applied to find SNPs and genomic regions associated with the traits, including a Bayesian approach using GenSel software, and frequentist approaches such as allele frequency differences between lines, single SNP and haplotype analyses using PLINK software. Single SNP and haplotype analyses showed no significant associations (except for LMA) after genomic control and FDR. Bayesian analyses found at least 2 associations for each trait at a false positive probability of 0.5. At generation 8, the RFI selection lines mainly differed in allele frequencies for SNPs near (<0.05 Mb) genes that regulate insulin release and leptin functions. The Bayesian approach identified associations of genomic regions containing insulin release genes (e.g., GLP1R, CDKAL, SGMS1) with RFI and ADFI, of regions with energy homeostasis (e.g., MC4R, PGM1, GPR81) and muscle growth related genes (e.g., TGFB1) with ADG, and of fat metabolism genes (e.g., ACOXL, AEBP1) with BF. Specifically, a very highly significantly associated QTL for LMA on SSC7 with skeletal myogenesis genes (e.g., KLHL31) was identified for subsequent fine mapping., Conclusions/significance: Important genomic regions associated with RFI related traits were identified for future validation studies prior to their incorporation in marker-assisted selection programs.

A genome-wide association study (GWAS) using Bayesian variable selection was performed to determine genomic regions associated with mortality due to Marek's disease virus (MDV) infection in layers. Mortality (%) under experimental disease challenge (500 plaque-forming units of a very virulent plus MDV strain) was recorded for progeny groups (average 15.5 birds; range 3 to 30) of 253 genotyped sires from four generations of a brown-egg layer line. An additional generation of 43 sires with progeny data was used to validate results. Sires were genotyped with a 42K Illumina single-nucleotide polymorphism (SNP) chip. Methods BayesB (pi = 0.995) and BayesCpi, with or without weighting residuals by the size of progeny groups were applied. The proportion of genetic variance contributed by SNPs within each 1-megabase (Mb) genomic region was quantified. Average mortality was 33% but differed significantly between generations. Genetic markers explained about 11% of phenotypic variation in mortality. Correlations between genomic estimated breeding values and percentage of progeny mortality for the validation generation (sons of individuals in training) were 0.12, 0.17, 0.02, and 0.16 for BayesB, weighted BayesB, BayesCpi, and weighted BayesCpi, respectively, when using the whole genome, and 0.03, 0.20, -0.06, and 0.14, when using only SNP from the 10, 1-Mb regions, explaining the largest proportion of genetic variance according to each method. Results suggest that regions on chromosomes 2, 3, 4, 9, 15, 18, and 21 are associated with Marek's disease resistance and can be used for selection and that accounting for the size of progeny groups has a large impact on correct localization of such genomic regions.

Random regression models allow for analysis of longitudinal data, which together with the use of genomic information are expected to increase accuracy of selection, when compared with analyzing average or total production with pedigree information. The objective of this study was to estimate variance components for egg production over time in a commercial brown egg layer population using genomic relationship information. A random regression reduced animal model with a marker-based relationship matrix was used to estimate genomic breeding values of 3,908 genotyped animals from 6 generations. The first 5 generations were used for training, and predictions were validated in generation 6. Daily egg production up to 46 wk in lay was accumulated into 85,462 biweekly (every 2 wk) records for training, of which 17,570 were recorded on genotyped hens and the remaining on their nongenotyped progeny. The effect of adding additional egg production data of 2,167 nongenotyped sibs of selection candidates [16,037 biweekly (every 2 wk) records] to the training data was also investigated. The model included a 5th order Legendre polynomial nested within hatch-week as fixed effects and random terms for coefficients of quadratic polynomials for genetic and permanent environmental components. Residual variance was assumed heterogeneous among 2-wk periods. Models using pedigree and genomic relationships were compared. Estimates of residual variance were very similar under both models, but the model with genomic relationships resulted in a larger estimate of genetic variance. Heritability estimates increased with age up to mid production and decreased afterward, resulting in an average heritability of 0.20 and 0.33 for pedigree and genomic models. Prediction of total egg number was more accurate with the genomic than with the pedigree-based random regression model (correlation in validation 0.26 vs. 0.16). The genomic model outperformed the pedigree model in most of the 2-wk periods. Thus, results of this study show that random regression reduced animal models can be used in breeding programs using genomic information and can result in substantial improvements in the accuracy of selection for trajectory traits.

Microbes and microbial components potentially impact the performance of pigs through immune stimulation and altered metabolism. These immune modulating factors can include endotoxin from gram negative bacterial outer membrane component, commonly referred to as lipopolysaccharide (LPS). In this study, our objective was to examine the relationship between intestinal barrier integrity, endotoxin and inflammation with feed efficiency (FE), using pig lines divergently selected for residual feed intake (RFI) as a model. Twelve gilts (62 ± 3 kg BW) from the low RFI (LRFI, more efficient) and 12 from the high RFI (HRFI, less efficient) were used. Individual performance data was recorded for 5 wk. At the end of the experimental period, ADFI of LRFI pigs was less (P < 0.001), ADG not different between the 2 lines (P = 0.72) but the G:F of LRFI pigs was greater than for HRFI pigs (P = 0.019). Serum endotoxin concentration (P < 0.01) and the acute phase protein haptoglobin (P < 0.05) were greater in HRFI pigs. Transepithelial resistance of the ileum, transport of fluorescein isothiocyanate labeled-Dextran and-LPS in ileum and colon, as well as tight junction protein mRNA expression in ileum, did not differ between the lines, indicating the 2 lines did not differ in transport characteristics at the intestinal level. Ileum inflammatory markers, myeloperoxidase (P < 0.05) and IL-8 (P < 0.10), were found to be greater in HRFI pigs. Alkaline phosphatase (ALP) activity was significantly increased in the LRFI pigs in ileum and liver tissues and negatively correlated with blood endotoxin (P < 0.05). Lysozyme activity in the liver was not different between the lines; however, the LRFI pigs had a twofold greater lysozyme activity in ileum (P < 0.05). Despite the difference in their activity, ALP or lysozyme mRNA expression was not different between the lines in either tissue. Decreased endotoxin and inflammatory markers and the enhanced activities of antimicrobial enzymes in the LRFI line may not fully explain the difference in the FE between the lines, but they have the potential to prevent the growth potential in HRFI pigs. Further studies are needed to identify the other mechanisms that may contribute to the greater endotoxin and acute phase proteins in the HRFI pigs and the greater FE in the LRFI pigs.

The objective of this study was to determine the extent to which genetic selection for residual feed intake (RFI) impacts electron leakage and reactive oxygen species (ROS) production in mitochondria from muscle and liver tissue. Understanding how genetic selection for RFI impacts animal physiology and growth efficiency is of the utmost importance as the world population increases. Production efficiency is tied directly to energy use. Mitochondria were used in this study because they produce 90% of the ATP in the body and use a large majority of dietary energy. Mitochondria were isolated from both muscle and liver tissue from pigs genetically selected for RFI (n = 8 per RFI line; 34 ± 4 kg). A 2,7-dichlorofluorscein diacetate assay was used to detect differences in hydrogen peroxide production between the more efficient low RFI line and the less efficient high RFI line. Our hypothesis was that greater efficiency would be linked to less ROS production from the mitochondria. There was less ROS production in mitochondria from the white portion of the semitendinosus in the low RFI line compared with the high RFI line, when both NADH and Flavin Adenine Dinucleotide (FADH2) energy substrates were used (glutamate and succinate, respectively). Additionally, mitochondria from the red portion of the semitendinosus in the low RFI line had less ROS production when succinate was used as an energy substrate (P < 0.05). A positive correlation was observed between RFI and ROS in mitochondria from the LM. These data indicate genetic selection for RFI may influence mitochondrial ROS production and efficiency of pork production.

Background: Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation., Results: When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training., Conclusion: Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection.

The objective of this study was to determine the relationship between individual sire estimated breeding values (EBV) for litters/sow/year (LSY) and sire progeny means for farrowing rate (FR), removal parity and lifetime born alive (LTBA). Genetic parameters and breeding values were estimated using ASREML. The heritability estimate for LSY was 0.11. When all sires with 10 or more daughters with records were included in the analysis, Spearman rank correlations between the sire's LSY EBV and the sires' daughter means for FR, removal parity and LTBA were 0.49, 0.23 and 0.25 (p < 0.01). The sire EBV for LSY was favourably correlated with sires' daughter means for all three traits. This provides evidence that selecting sires with high EBV for LSY could improve herd FR, removal parity and LTBA. By including LSY as part of the selection criterion, the LTBA may be indirectly improved. The positive genetic correlation between LTBA and LSY may be a result of the improved longevity of sows with greater LSY compared with sows with lower LSY. The relationships between LSY and FR, removal parity and LTBA are strongly supported by the correlations between the sire progeny means for each trait and the sire LSY EBV., (© 2012 Blackwell Verlag GmbH.)

Weaned pigs from a line bred for increased feed efficiency were enrolled in a study of the role of host genes in the response to infection with Porcine Reproductive and Respiratory Syndrome Virus (PRRSV). Four of the pigs were euthanatized early in the study due to weight loss with illness and poor body condition; 2 pigs before PRRSV infection and the other 2 pigs approximately 2 weeks after virus inoculation. The 2 inoculated pigs failed to produce PRRSV-specific antibodies. Gross findings included pneumonia, absence of a detectable thymus, and small secondary lymphoid tissues. Histologically, lymph nodes, spleen, tonsils, and Peyer's patches were sparsely cellular with decreased to absent T and B lymphocytes.

Objective: The objective of this study was to determine whether a lifestyle intervention with individual counselling was cost-effective for reducing body weight compared with usual care from a company perspective., Participants: Overweight employees were recruited and randomly assigned to the intervention groups, either phone or Internet, or the control group., Methods: The intervention was based on a cognitive behavioural approach and addressed physical activity and diet. Self-reported body weight was collected at baseline and 12 months follow-up. Intervention costs and costs of sick leave days based on gross and net lost productivity days (GLPDs/NLPDs) obtained from the participating companies were calculated. Missing data were imputed using multiple imputation techniques. Uncertainty surrounding the differences in costs and the incremental cost-effectiveness ratios (ICER) was estimated by bootstrapping techniques, and presented on cost-effectiveness planes and cost-effectiveness acceptability curves., Results: No statistically significant differences in total costs were found between the intervention groups and control group, though mean total costs in both intervention groups tended to be higher than those in the control group. The ICER of the Internet group compared with the control group was €59 per kilogram of weight loss based on GLPD costs. The probability of cost effectiveness of the Internet intervention was 45% at a willingness-to-pay of €0 per extra kilogram weight loss and 75% at a willingness-to-pay of €1500 per extra kilogram body weight loss. Comparable results were found for the phone intervention., Conclusions: The intervention was not cost effective in comparison with usual care from the company perspective. Due to the large amount of missing data, it is not possible to draw firm conclusions.

Little is known of the consequences of divergent selection for residual feed intake (RFI) on intestinal digestion capacity, particularly during immune system stimulation (ISS). Our objective was to evaluate the impact of ISS and divergent selection for RFI on apparent ileal digestibility (AID) and apparent fecal digestibility (AFD) of nutrients and intestinal nutrient active transport and barrier function. Twenty-eight gilts (63 ± 4 kg BW) from low RFI (LRFI; n = 14) and high RFI (HRFI; n = 14) Yorkshire lines were randomly selected from the Iowa State University RFI herd. Following adaptation, 8 pigs in each line were injected intramuscularly and every 48 h for 7 d with increasing amounts of Escherichia coli lipopolysaccharide (ISS+). Remaining pigs were injected with saline (ISS-). Pigs were then euthanized and ileal digesta was collected for measuring AID of nutrients. Fecal samples were collected on a daily basis and pooled for measuring AFD of nutrients. A segment of ileum was used to measure nutrient transport and transepithelial resistance (TER) and/or barrier integrity by Ussing chambers. No effects of line or its interaction with ISS on AID of CP (N × 6.25) and OM, TER, and active nutrients transport were observed. However, ISS decreased (P < 0.05) and tended to (P < 0.1) decrease AID of CP and OM, respectively. Decrease in AFD of CP as result of ISS was greater in the LRFI line compared to the HRFI line (P < 0.05). Relative to ISS-, active glucose and P transport was greater in ISS+ pigs (P < 0.05). Genetic selection for LRFI increases the AFD but has no effect on AID of nutrients. It also reduces the total tract digestive capacity of growing pigs during ISS. Immune system stimulation affects both AID and AFD of dietary CP.

Given a large number of t-statistics, we consider the problem of approximating the distribution of noncentrality parameters (NCPs) by a continuous density. This problem is closely related to the control of false discovery rates (FDR) in massive hypothesis testing applications, e.g., microarray gene expression analysis. Our methodology is similar to, but improves upon, the existing approach by Ruppert, Nettleton, and Hwang (2007, Biometrics, 63, 483-495). We provide parametric, nonparametric, and semiparametric estimators for the distribution of NCPs, as well as estimates of the FDR and local FDR. In the parametric situation, we assume that the NCPs follow a distribution that leads to an analytically available marginal distribution for the test statistics. In the nonparametric situation, we use convex combinations of basis density functions to estimate the density of the NCPs. A sequential quadratic programming procedure is developed to maximize the penalized likelihood. The smoothing parameter is selected with the approximate network information criterion. A semiparametric estimator is also developed to combine both parametric and nonparametric fits. Simulations show that, under a variety of situations, our density estimates are closer to the underlying truth and our FDR estimates are improved compared with alternative methods. Data-based simulations and the analyses of two microarray datasets are used to evaluate the performance in realistic situations., (© 2012, The International Biometric Society.)

For analysis of genomic data, e.g., microarray data from gene expression profiling experiments, the two-component mixture model has been widely used in practice to detect differentially expressed genes. However, it naïvely imposes strong exchangeability assumptions across genes and does not make active use of a priori information about intergene relationships that is currently available, e.g., gene annotations through the Gene Ontology (GO) project. We propose a general strategy that first generates a set of covariates that summarizes the intergene information and then extends the two-component mixture model into a hierarchical semiparametric model utilizing the generated covariates through latent nonparametric regression. Simulations and analysis of real microarray data show that our method can outperform the naïve two-component mixture model., (© 2012, The International Biometric Society.)

Background: Insect bite hypersensitivity is a common allergic disease in horse populations worldwide. Insect bite hypersensitivity is affected by both environmental and genetic factors. However, little is known about genes contributing to the genetic variance associated with insect bite hypersensitivity. Therefore, the aim of our study was to identify and quantify genomic associations with insect bite hypersensitivity in Shetland pony mares and Icelandic horses in the Netherlands., Methods: Data on 200 Shetland pony mares and 146 Icelandic horses were collected according to a matched case-control design. Cases and controls were matched on various factors (e.g. region, sire) to minimize effects of population stratification. Breed-specific genome-wide association studies were performed using 70 k single nucleotide polymorphisms genotypes. Bayesian variable selection method Bayes-C with a threshold model implemented in GenSel software was applied. A 1 Mb non-overlapping window approach that accumulated contributions of adjacent single nucleotide polymorphisms was used to identify associated genomic regions., Results: The percentage of variance explained by all single nucleotide polymorphisms was 13% in Shetland pony mares and 28% in Icelandic horses. The 20 non-overlapping windows explaining the largest percentages of genetic variance were found on nine chromosomes in Shetland pony mares and on 14 chromosomes in Icelandic horses. Overlap in identified associated genomic regions between breeds would suggest interesting candidate regions to follow-up on. Such regions common to both breeds (within 15 Mb) were found on chromosomes 3, 7, 11, 20 and 23. Positional candidate genes within 2 Mb from the associated windows were identified on chromosome 20 in both breeds. Candidate genes are within the equine lymphocyte antigen class II region, which evokes an immune response by recognizing many foreign molecules., Conclusions: The genome-wide association study identified several genomic regions associated with insect bite hypersensitivity in Shetland pony mares and Icelandic horses. On chromosome 20, associated genomic regions in both breeds were within 2 Mb from the equine lymphocyte antigen class II region. Increased knowledge on insect bite hypersensitivity associated genes will contribute to our understanding of its biology, enabling more efficient selection, therapy and prevention to decrease insect bite hypersensitivity prevalence.

Background: Distance lifestyle counseling for weight control is a promising public health intervention in the work setting. Information about the cost-effectiveness of such interventions is lacking, but necessary to make informed implementation decisions. The purpose of this study was to perform an economic evaluation of a six-month program with lifestyle counseling aimed at weight reduction in an overweight working population with a two-year time horizon from a societal perspective., Methods: A randomized controlled trial comparing a program with two modes of intervention delivery against self-help. 1386 Employees from seven companies participated (67% male, mean age 43 (SD 8.6) years, mean BMI 29.6 (SD 3.5) kg/m2). All groups received self-directed lifestyle brochures. The two intervention groups additionally received a workbook-based program with phone counseling (phone; n=462) or a web-based program with e-mail counseling (internet; n=464). Body weight was measured at baseline and 24 months after baseline. Quality of life (EuroQol-5D) was assessed at baseline, 6, 12, 18 and 24 months after baseline. Resource use was measured with six-monthly diaries and valued with Dutch standard costs. Missing data were multiply imputed. Uncertainty around differences in costs and incremental cost-effectiveness ratios was estimated by applying non-parametric bootstrapping techniques and graphically plotting the results in cost-effectiveness planes and cost-effectiveness acceptability curves., Results: At two years the incremental cost-effectiveness ratio was €1009/kg weight loss in the phone group and €16/kg weight loss in the internet group. The cost-utility analysis resulted in €245,243/quality adjusted life year (QALY) and €1337/QALY, respectively. The results from a complete-case analysis were slightly more favorable. However, there was considerable uncertainty around all outcomes., Conclusions: Neither intervention mode was proven to be cost-effective compared to self-help.

The pioneering work by Professor Soller et al., among others, on the use of genetic markers to analyze quantitative traits has provided opportunities to discover their genetic architecture in livestock by identifying quantitative trait loci (QTL). The recent availability of high-density single nucleotide polymorphism (SNP) panels has advanced such studies by capitalizing on population-wide linkage disequilibrium at positions across the genome. In this study, genomic prediction model Bayes-B was used to identify genomic regions associated with the mean and standard deviation of egg weight at three ages in a commercial brown egg layer line. A total of 24,425 segregating SNPs were evaluated simultaneously using over 2900 genotyped individuals or families. The corresponding phenotypic records were represented as individual measurements or family means from full-sib progeny. A novel approach using the posterior distribution of window variances from the Monte Carlo Markov Chain samples was used to describe genetic architecture and to make statistical inferences about regions with the largest effects. A QTL region on chromosome 4 was found to explain a large proportion of the genetic variance for the mean (30%) and standard deviation (up to 16%) of the weight of eggs laid at specific ages. Additional regions with smaller effects on chromosomes 2, 5, 6, 8, 20, 23, 28 and Z showed suggestive associations with mean egg weight and a region on chromosome 13 with the standard deviation of egg weight at 26-28 weeks of age. The genetic architecture of the analyzed traits was characterized by a limited number of genes or genomic regions with large effects and many regions with small polygenic effects. The region on chromosome 4 can be used to improve both the mean and standard deviation of egg weight by marker-assisted selection., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

Porcine reproductive and respiratory syndrome (PRRS) causes decreased reproductive performance in breeding animals and increased respiratory problems in growing animals, which result in significant economic losses in the swine industry. Vaccination has generally not been effective in the prevention of PRRS, partially because of the rapid mutation rate and evolution of the virus. The objective of the current study was to discover the genetic basis of host resistance or susceptibility to the PRRS virus through a genome-wide association study using data from the PRRS Host Genetics Consortium PRRS-CAP project. Three groups of approximately 190 commercial crossbred pigs from 1 breeding company were infected with PRRS virus between 18 and 28 d of age. Blood samples and BW were collected up to 42 d post infection (DPI). Pigs were genotyped with the Illumina Porcine 60k Beadchip. Whole-genome analysis focused on viremia at each day blood was collected and BW gains from 0 to 21 DPI (WG21) or 42 DPI (WG42). Viral load (VL) was quantified as area under the curve from 0 to 21 DPI. Heritabilities for WG42 and VL were moderate at 0.30 and litter accounted for an additional 14% of phenotypic variation. Genomic regions associated with VL were found on chromosomes 4 and X and on 1, 4, 7, and 17 for WG42. The 1-Mb region identified on chromosome 4 influenced both WG and VL, exhibited strong linkage disequilibrium, and explained 15.7% of the genetic variance for VL and 11.2% for WG42. Despite a genetic correlation of -0.46 between VL and WG42, genomic EBV for this region were favorably and nearly perfectly correlated. The favorable allele for the most significant SNP in this region had a frequency of 0.16 and estimated allele substitution effects were significant (P < 0.01) for each group when the SNP was fitted as a fixed covariate in a model that included random polygenic effects with overall estimates of -4.1 units for VL (phenotypic SD = 6.9) and 2.0 kg (phenotypic SD = 3 kg) for WG42. Candidate genes in this region on SSC4 include the interferon induced guanylate-binding protein gene family. In conclusion, host response to experimental PRRS virus challenge has a strong genetic component, and a QTL on chromosome 4 explains a substantial proportion of the genetic variance in the studied population. These results could have a major impact in the swine industry by enabling marker-assisted selection to reduce the impact of PRRS but need to be validated in additional populations.

Genetic parameters were estimated for egg defects, egg production, and egg quality traits. Eggs from 11,738 purebred brown-egg laying hens were classified as salable or as having one of the following defects: bloody, broken, calcium deposit, dirty, double yolk, misshapen, pee-wee, shell-less, and soft shelled. Egg quality included albumen height, egg weight, yolk weight, and puncture score. Body weight, age at sexual maturity, and egg production were also recorded. Heritability estimates of liability to defects using a threshold animal model were less than 0.1 for bloody and dirty; between 0.1 and 0.2 for pee-wee, broken, misshapen, soft shelled, and shell-less; and above 0.2 for calcium deposit and double yolk. Quality and production traits were more heritable, with estimates ranging from 0.29 (puncture score) to 0.74 (egg weight). High-producing hens had a lower frequency of egg defects. High egg weight and BW were associated with an increased frequency of double yolks, and to a lesser extent, with more shell quality defects. Estimates of genetic correlations among defect traits that were related to shell quality were positive and moderate to strong (0.24-0.73), suggesting that these could be grouped into one category or selection could be based on the trait with the highest heritability or that is easiest to measure. Selection against defective eggs would be more efficient by including egg defect traits in the selection criterion, along with egg production rate of salable eggs and egg quality traits.

Background: The goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15th QTL-MAS workshop., Methods: Three methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion π = 0.995 of SNPs assumed to have no effect, (ii) BayesCπ, where π is considered as unknown, and (iii) GBLUP, which directly fits animal genetic effects using a genomic relationship matrix., Results: BayesB, BayesCπ and GBLUP with various fitted models detected 6, 5, and 4 out of 8 simulated QTL, respectively. All five additive QTL were detected by Bayesian methods. When two QTL were in either coupling or repulsion phase, GBLUP only detected one of them and missed the other. In addition, GBLUP yielded more false positives. One imprinted QTL was detected by BayesB and GBLUP despite that only additive gene action was assumed. This QTL was missed by BayesCπ. None of the methods found two simulated additive-by-additive epistatic QTL. Variance components estimation correctly detected no evidence for dominance gene-action. Bayesian methods predicted additive genetic merit more accurately than GBLUP, and similar accuracies were observed between BayesB and BayesCπ., Conclusions: Bayesian methods and GBLUP mapped QTL to similar chromosome regions but Bayesian methods gave fewer false positives. Bayesian methods can be superior to GBLUP in GEBV prediction when genomic architecture is unknown.

The main goal in animal breeding is to select individuals that have high breeding values for traits of interest as parents to produce the next generation and to do so as quickly as possible. To date, most programs rely on statistical analysis of large data bases with phenotypes on breeding populations by linear mixed model methodology to estimate breeding values on selection candidates. However, there is a long history of research on the use of genetic markers to identify quantitative trait loci and their use in marker-assisted selection but with limited implementation in practical breeding programs. The advent of high-density SNP genotyping, combined with novel statistical methods for the use of this data to estimate breeding values, has resulted in the recent extensive application of genomic or whole-genome selection in dairy cattle and research to implement genomic selection in other livestock species is underway. The high-density SNP data also provides opportunities to detect QTL and to encover the genetic architecture of quantitative traits, in terms of the distribution of the size of genetic effects that contribute to trait differences in a population. Results show that this genetic architecture differs between traits but that for most traits, over 50% of the genetic variation resides in genomic regions with small effects that are of the order of magnitude that is expected under a highly polygenic model of inheritance.

Animal models for cancer therapy are invaluable for preclinical testing of potential cancer treatments; however, therapies tested in such models often fail to translate into clinical settings. Therefore, a better preclinical model for cancer treatment testing is needed. Here we demonstrate that an immunodeficient line of pigs can host and support the growth of xenografted human tumors and has the potential to be an effective animal model for cancer therapy. Wild-type and immunodeficient pigs were injected subcutaneously in the left ear with human melanoma cells (A375SM cells) and in the right ear with human pancreatic carcinoma cells (PANC-1). All immunodeficient pigs developed tumors that were verified by histology and immunohistochemistry. Nonaffected littermates did not develop tumors. Immunodeficient pigs, which do not reject xenografted human tumors, have the potential to become an extremely useful animal model for cancer therapy because of their similarity in size, anatomy, and physiology to humans.

The performance of linear regression models in genome-wide association studies is influenced by how marker information is parameterized in the model. Considering the impact of parameterization is especially important when using information from multiple markers to test for association. Properties of the population, such as linkage disequilibrium (LD) and allele frequencies, will also affect the ability of a model to provide statistical support for an underlying quantitative trait locus (QTL). Thus, for a given location in the genome, the relationship between population properties and model parameterization is expected to influence the performance of the model in providing evidence for the position of a QTL. As LD and allele frequencies vary throughout the genome and between populations, understanding the relationship between these properties and model parameterization is of considerable importance in order to make optimal use of available genomic data. Here, we evaluate the performance of regression-based association models using genotype and haplotype information across the full spectrum of allele frequency and LD scenarios. Genetic marker data from 200 broiler chickens were used to simulate genomic conditions by selecting individual markers to act as surrogate QTL (sQTL) and then investigating the ability of surrounding markers to estimate sQTL genotypes and provide statistical support for their location. The LD and allele frequencies of markers and sQTL are shown to have a strong effect on the performance of models relative to one another. Our results provide an indication of the best choice of model parameterization given certain scenarios of marker and QTL LD and allele frequencies. We demonstrate a clear advantage of haplotype-based models, which account for phase uncertainty over other models tested, particularly for QTL with low minor allele frequencies. We show that the greatest advantage of haplotype models over single-marker models occurs when LD between markers and the causal locus is low. Under these situations, haplotype models have a greater accuracy of predicting the location of the QTL than other models tested., (© 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.)

Gompertz growth functions were fitted to longitudinal measurements of daily feed intake (DFI) and BW of 586 boars and 495 gilts from a selection experiment in Yorkshire pigs for residual feed intake (RFI). The selection experiment consists of a line selected for low residual feed intake (LRFI) for 5 generations and a randomly selected control line (CTRL). The objectives of this study were to use Bayesian methods to estimate genetic parameters of the Gompertz curve parameters for DFI and BW, to evaluate the effect of selection for reduced RFI on the Gompertz parameters and shape of curves for DFI and BW, and to develop methodology for quantifying genetic variation at the level of the original phenotypes for DFI and BW based on the Bayesian analysis of the nonlinear model. Separate analyses were done for boars and gilts and for BW and DFI. A hierarchical model was specified in 2 levels: in the first level, the Gompertz function was modeled for each pig, and at the second level, a 3-trait linear mixed model was fitted to the 3 Gompertz parameters (asymptotic value, inflection point, and decay parameter), with fixed effects of line by generation and random effects of additive genetic and environmental effects. Bayesian methods were used to combine the 2 levels of modeling. A total of 30,000 random samples of the posterior distributions after convergence of Markov chains were used for inference. Posterior means of heritability within the first level of the model for the asymptotic value, inflection point, and decay parameter for DFI were 0.74, 0.66, and 0.82 for boars and 0.79, 0.70, and 0.57 for gilts; corresponding estimates for BW were 0.64, 0.58, and 0.60 for boars and 0.46, 0.35, and 0.33 for gilts. For DFI, LRFI boars had a reduced mature DFI (2.91 vs. 3.20 kg/d) and an earlier inflection point (85 vs. 95 d) compared with CTRL boars. For BW, LRFI boars had a lighter mature BW (279 vs. 317 kg), an earlier inflection point (184 vs. 198 d), and a decreased decay parameter (127 vs. 134 d) compared with CTRL boars. In contrast, LRFI gilts had a later inflection point (225 vs. 200 d) and a greater decay parameter (172 vs. 143 d) than CTRL gilts for BW. The other Gompertz curve parameters for DFI and BW for boars and gilts were considered not different between lines, with posterior probabilities of the line differences being greater than zero ranging from 0.1 to 0.9.

Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP) panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC) estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed "fastBayesA") without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.

Myostatin, or GDF8, is an inhibitor of skeletal muscle growth. A non-functional myostatin mutation leads to a double muscling phenotype in some species, for example, mice, cattle and humans. Previous studies have indicated that there are loci in the genome that interact with myostatin to control backfat depth and other complex traits. We now report a quantitative trait loci (QTL) mapping study designed to identify loci that interact with myostatin to impact growth traits in mice. Body weight and average daily gain traits were collected on F2 progeny derived from a myostatin-null C57BL/6 strain by M16i cross. In all, 44 main effect QTL were detected above a 5% genome-wide significance threshold when an interval mapping method was used. An additional 37 QTL were identified to significantly interact with myostatin, sex or reciprocal cross. A total of 12 of these QTL interacted with myostatin genotype. These results provide a foundation for the further fine mapping of genome regions that harbor loci that interact with myostatin.

Background: Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction., Methods: Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values., Results: Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied., Conclusions: These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Asymptomatic Salmonella-carrier pigs present a major problem in preharvest food safety, with a recent survey indicating >50% of swine herds in the United States have Salmonella-positive animals. Salmonella-carrier pigs serve as a reservoir for contamination of neighbouring pigs, abattoir pens and pork products. In addition, fresh produce as well as water can be contaminated with Salmonella from manure used as fertilizer. Control of Salmonella at the farm level could be through genetic improvement of porcine disease resistance, a potentially powerful method of addressing preharvest pork safety. In this research, we integrate gene expression profiling data and sequence alignment-based prediction of single nucleotide polymorphisms (SNPs) to successfully identify SNPs in functional candidate genes to test for the associations with swine response to Salmonella. A list of 2527 genes that were differentially regulated in porcine whole blood in response to infection with Salmonella enterica serovar Typhimurium were selected. In those genes, SNPs were predicted using ANEXdb alignments based on stringent clustering of all publically available porcine cDNA and expressed sequence tag (EST) sequences. A set of 30 mostly non-synonymous SNPs were selected for genotype analysis of four independent populations (n = 750) with Salmonella faecal shedding or tissue colonization phenotypes. Nine SNPs segregated with minor allele frequency ≥15% in at least two populations. Statistical analysis revealed SNPs associated with Salmonella shedding, such as haptoglobin (HP, p = 0.001, q = 0.01), neutrophil cytosolic factor 2 (NCF2 #2, p = 0.04, q = 0.21) and phosphogluconate dehydrogenase (p = 0.066, q = 0.21). These associations may be useful in identifying and selecting pigs with improved resistance to this bacterium., (© 2011 Blackwell Verlag GmbH.)

Salmonella in swine is a major food safety problem, as the majority of US swine herds are Salmonella-positive. Salmonella can be shed from colonized swine and contaminate (i) neighbouring pigs; (ii) slaughter plants and pork products; (iii) edible crops when swine manure is used as a fertilizer; and (iv) water supplies if manure used as crop fertilizer runs off into streams and waterways. A potentially powerful method of addressing pre-harvest food safety at the farm level is through genetic improvement of disease resistance in animals. In this research, we describe a successful strategy for discovering genetic variation at candidate genes associated with disease resistance in pigs. This involves integrating our recent global gene expression analysis of the porcine response to Salmonella with information from the literature about important candidate genes. We identified single-nucleotide polymorphisms (SNPs) in these functional candidate genes and genotyped three independent pig populations that had data on Salmonella faecal shedding or internal burden (total n = 377) at these loci. Of 31 SNPs genotyped, 21 SNPs segregated in at least two populations with a minor allele frequency of 15% or greater. Statistical analysis revealed thirteen SNPs associated with Salmonella faecal shedding or tissue colonization, with an estimated proportion of false positives (PFP) ≤0.2. The genes with associated SNPs included GNG3, NCF2, TAP1, VCL, AMT, CCR1, CD163, CCT7, EMP1 and ACP2. These associations provide new information about the mechanisms of porcine host response to Salmonella and may be useful in improving genetic resistance to this bacterium., (© 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.)

Residual feed intake (RFI), defined as the difference between observed and expected feed intake based on growth and backfat, has been used to investigate genetic variation in feed efficiency in cattle, poultry and pigs. However, little is known about the biological basis of differences in RFI in pigs. To this end, the objective of this study was to evaluate the fifth generation of a line of pigs selected for reduced RFI against a randomly selected Control line for performance, carcass and chemical carcass composition and overall efficiency. Here, emphasis was on the early grower phase. A total of 100 barrows, 50 from each line, were paired by age and weight (22.6 ± 3.9 kg) and randomly assigned to one of four feeding treatments in 11 replicates: ad libitum (Ad), 75% of Ad (Ad75), 55% of Ad (Ad55) and weight stasis (WS), which involved weekly adjustments in intake to keep body weight (BW) constant for each pig. Pigs were individually penned (group housing was used for selection) and were on treatment for 6 weeks. Initial BW did not significantly differ between the lines (P > 0.17). Under Ad feeding, the low RFI pigs consumed 8% less feed compared with Control line pigs (P < 0.06), had less carcass fat (P < 0.05), but with no significant difference in growth rate (P > 0.85). Under restricted feeding, low RFI pigs under the Ad75 treatment had a greater rate of gain while consuming the same amount of feed as Control pigs. Despite the greater gain, no significant line differences in carcass composition or carcass traits were observed. For the WS treatment, low RFI pigs had similar BW (P > 0.37) with no significant difference in feed consumption (P > 0.32). Overall, selection for reduced RFI has decreased feed intake, with limited differences in growth rate but reduced carcass fat, as seen under Ad feeding. Collectively, results indicate that the effects of selection for low RFI are evident during the early grower stage, which allows for greater savings to the producer.

Background: The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information., Methods: The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability., Results: Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.

Objectives: To determine the effectiveness of a weight-management program with personal counseling by phone or e-mail., Methods: A randomized controlled trial of a 6-month program comparing two modes of intervention delivery (phone, n = 462; Internet, n = 464) with self-directed materials (control, n = 460), among overweight employees. Change in body weight after 2 years was the main outcome., Results: Among complete cases, weight loss in the Internet group was 1.2 kg (95% confidence interval [CI], -1.9 to -0.4) and in the phone group 0.8 kg (95% CI, -1.5 to 0.03), compared with the control group. Multiple imputation of missing body weight resulted in comparative weight losses of -0.9 kg (95% CI, -2.0 to 0.3) and -0.4 kg (95% CI, -1.4 to 0.7)., Conclusions: Among complete cases, the Internet intervention showed modest long-term weight loss, but among all participants neither program version was more effective than self-help.

Background: Bayesian methods allow prediction of genomic breeding values (GEBVs) using high-density single nucleotide polymorphisms (SNPs) covering the whole genome with effective shrinkage of SNP effects using appropriate priors. In this study we applied a modification of the well-known BayesA and BayesB methods to estimate the proportion of SNPs with zero effects (π) and a common variance for non-zero effects. The method, termed BayesCπ, was used to predict the GEBVs of the last generation of the QTLMAS2010 data. The accuracy of GEBVs from various methods was estimated by the correlation with phenotypes in the last generation. The methods were BayesCPi and BayesB with different π values, both with and without polygenic effects, and best linear unbiased prediction using an animal model with a genomic or numerator relationship matrix. Positions of quantitative trait loci (QTLs) were identified based on the variances of GEBVs for windows of 10 consecutive SNPs. We also proposed a novel approach to set significance thresholds for claiming QTL in this specific case by using pedigree-based simulation of genotypes. All analyses were focused on detecting and evaluating QTL with additive effects., Results: The accuracy of GEBVs was highest for BayesCπ, but the accuracy of BayesB with π equal to 0.99 was similar to that of BayesCπ. The accuracy of BayesB dropped with a decrease in π. Including polygenic effects into the model only had marginal effects on accuracy and bias of predictions. The number of QTL identified was 15 when based on a stringent 10% chromosome-wise threshold and increased to 21 when a 20% chromosome-wise threshold was used., Conclusions: The BayesCπ method without polygenic effects was identified to be the best method for the QTLMAS2010 dataset, because it had highest accuracy and least bias. The significance criterion based on variance of 10-SNP windows allowed detection of more than half of the QTL, with few false positives.

A 5-generation selection experiment in Yorkshire pigs for feed efficiency consists of a line selected for low residual feed intake (LRFI) and a random control line (CTRL). The objectives of this study were to use random regression models to estimate genetic parameters for daily feed intake (DFI), BW, backfat (BF), and loin muscle area (LMA) along the growth trajectory and to evaluate the effect of LRFI selection on genetic curves for DFI and BW. An additional objective was to compare random regression models using polynomials (RRP) and spline functions (RRS). Data from approximately 3 to 8 mo of age on 586 boars and 495 gilts across 5 generations were used. The average number of measurements was 85, 14, 5, and 5 for DFI, BW, BF, and LMA. The RRP models for these 4 traits were fitted with pen × on-test group as a fixed effect, second-order Legendre polynomials of age as fixed curves for each generation, and random curves for additive genetic and permanent environmental effects. Different residual variances were used for the first and second halves of the test period. The RRS models were fitted with the same fixed effects and residual variance structure as the RRP models and included genetic and permanent environmental random effects for both splines and linear Legendre polynomials of age. The RRP model was used for further analysis because the RRS model had erratic estimates of phenotypic variance and heritability, despite having a smaller Bayesian information criterion than the RRP model. From 91 to 210 d of age, estimates of heritability from the RRP model ranged from 0.10 to 0.37 for boars and 0.14 to 0.26 for gilts for DFI, from 0.39 to 0.58 for boars and 0.55 to 0.61 for gilts for BW, from 0.48 to 0.61 for boars and 0.61 to 0.79 for gilts for BF, and from 0.46 to 0.55 for boars and 0.63 to 0.81 for gilts for LMA. In generation 5, LRFI pigs had lower average genetic curves than CTRL pigs for DFI and BW, especially toward the end of the test period; estimated line differences (CTRL-LRFI) for DFI were 0.04 kg/d for boars and 0.12 kg/d for gilts at 105 d and 0.20 kg/d for boars and 0.24 kg/d for gilts at 195 d. Line differences for BW were 0.17 kg for boars and 0.69 kg for gilts at 105 d and 3.49 kg for boars and 8.96 kg for gilts at 195 d. In conclusion, selection for LRFI has resulted in a lower feed intake curve and a lower BW curve toward maturity.

Residual feed intake (RFI) is a measure of feed efficiency defined as the difference between observed and predicted feed intake based on average requirements for growth and maintenance. The objective of this study was to evaluate the effect of selection for decreased RFI on feeding behavior traits and to estimate their relationships with RFI. Three data sets from the 4th and 5th generations of a selection experiment with a line selected for reduced RFI (LRFI) and a randomly selected control line (CTRL) were analyzed. Lines were mixed in pens of 16 and evaluated for feeding behavior traits obtained from a single-space electronic feeder over a growing period of ~3 mo before ~115 kg. The following traits were evaluated as averages over the entire test period and over the first and second half of the test period: number of visits per day and hour; occupation time per day, visit, and hour; feed intake (FI) per day, visit, and hour; and FI rate per visit. Models used included fixed effects of line and feeder, covariates of on-test age and FI per day, and random effects of pen, on-test group, sire, and litter. Repeated measures models were used to analyze feeding patterns during the day. The LRFI pigs had significantly less FI per day than CTRL pigs for all 3 data sets. With adjustment for FI per day, line differences of all traits were in the same direction for all 3 data sets but differed in significance and size. Feed intake per visit and hour and visits per day and hour did not differ between lines, but the trend was for LRFI pigs to have fewer visits, in particular during peak eating times. The LRFI pigs had a greater feeding rate and less occupation time per day, visit, and hour than CTRL pigs, but this was not significant for all data sets. Correlations of RFI with FI per day and visit and visits per day were positive. Average daily gain was positively correlated with FI per day and visit and occupation time per visit but negatively correlated with visits per day. Feed intake per day was positively correlated with backfat. In conclusion, feed efficiency may be affected by FI behavior because selection for decreased RFI has resulted in pigs that spend less time eating and eat faster.

To evaluate the ability to use DNA pools with the Illumina Infinium genotyping platform, two sets of gradient pools were created using two pairs of highly inbred chicken lines. Replicate pools containing 0%, 10%, 20%, 40%, 60%, 80%, 90% and 100% of DNA from line A vs. B or line C vs. D were created, for a total of 28 pools. All pools were genotyped for 12,046 SNPs. Three frequency estimation methods proposed in the literature (standard, heterozygote-corrected and normalized) were compared with three alternate methods proposed herein based on mean square error (MSE), bias and variance of estimated vs. true allele frequencies and the fit of regression of estimated on true frequencies. The three new methods had average square root MSE of 4.6%, 4.6% and 4.7% compared to 5.2%, 5.5% and 11.2% for the three literature methods. Average absolute biases of the literature methods were 2.4%, 2.7% and 8.2% compared to 2.4% for all new methods. Standard deviations of estimates were also smaller for the new methods, at 3.1%, 3.2% and 3.2% compared to 3.5%, 4.0% and 5.0% for previously reported methods. In conclusion, intensity data from the Illumina Infinium Assay can be efficiently used to estimate allele frequencies in pools, in particular using any of the new methods proposed herein., (© 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.)

Background: Overweight (Body Mass Index [BMI] ≥ 25 kg/m²) and obesity (BMI ≥ 30 kg/m²) are associated with increased cardiovascular risk, posing a considerable burden to public health. The main aim of this study was to investigate lifestyle intervention effects on cardiovascular risk factors in healthy overweight employees., Methods: Participants were 276 healthy overweight employees (69.2% male; mean age 44.0 years [SD 9.2]; mean BMI 29.7 kg/m² [SD 3.1]). They were randomized to one of two intervention groups receiving a six month lifestyle intervention with behavior counseling by phone (phone group) or e-mail (Internet group), or to a control group receiving usual care. Body weight, height, waist circumference, sum of skinfolds, blood pressure, total cholesterol level and predicted aerobic fitness were measured at baseline, at 6 and at 24 months. Regression analyses included the 141 participants with complete data., Results: At 6 months a significant favorable effect on total cholesterol level (-0.2 mmol/l, 95%CI -0.5 to -0.0) was observed in the phone group and a trend for improved aerobic fitness (1.9 ml/kg/min, 95%CI -0.2 to 3.9) in the Internet group. At two years, favorable trends for body weight (-2.1 kg, 95%CI -4.4 to 0.2) and aerobic fitness (2.3 ml/kg/min, 95%CI -0.2 to 4.8) were observed in the Internet group., Conclusions: The intervention effects were independent of the used communication mode. However short-term results were in favor of the phone group and long-term results in favor of the internet group. Thus, we found limited evidence for our lifestyle intervention to be effective in reducing cardiovascular risk in a group of apparently healthy overweight workers., Trial Registration: ISRCTN04265725.

Background: Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line., Methods: The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records).The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV., Results: Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.

The objectives of this study were to estimate genetic parameters for egg production over the age trajectory in 3 layer lines, which represent different biotypes for egg production, and to validate the use of breeding values for slope as a measure of persistency to be used in the selection program. Egg production of more than 26,000 layers per line from 6 consecutive generations were analyzed with a random regression model with a within-hatch-nested fifth-order fixed-regression polynomial and linear polynomials for random additive genetic and permanent environmental effects. Daily records were cumulated into biweekly periods. In all lines, a nonzero genetic variance for mean and slope and a positive genetic correlation between mean and slope were estimated. Genetic variance of egg production by 2-wk period was low at the beginning of lay and increased as the birds aged for all 3 lines, which resulted in heritability estimates increasing with age. Breeding values for slope reflected the shape of the egg production curve well and can be used to directly select for persistency of egg production.

The objectives of this study were to determine the effect of selection for improved residual feed intake on behavior, activity, and lesion scores in gilts in their home pen. A total of 192 gilts were used, 96 from a line that had been selected for decreased residual feed intake over 5 generations (LRFI) and 96 from a randomly bred control line. Gilts were housed in 12 pens (16 gilts/pen; 0.82 m(2)/gilt) containing 8 gilts from each line in a conventional grow-finish unit. Twelve hours of video footage were collected on the day of placement and then every 4 wk for 3 more observational periods. Video was scored using a 10-min instantaneous scan sampling technique for 4 postures (standing, lying, sitting, and locomotion) and 1 behavior (at drinker). Categories of active (standing, locomotion, and at drinker) and inactive (sitting and lying) were also created. Lesion scores were collected 24 h after behavior collection had begun. The body of a gilt was divided into 4 regions, with each region receiving a score of 0 (0 lesions) to 3 (5+ lesions). All statistical analyses used Proc Mixed of SAS. Data were analyzed separately for the day of placement and the subsequent 3 rounds. General activity was summarized on a percentage basis by each posture and behavior and subjected to an arcsine square root transformation to normalize data and stabilize variance. Analysis was performed on each behavior and posture. Lesion scores for each region of the body were analyzed as repeated measures. There were no differences (P > 0.05) between genetic lines for all postures and the behavior at drinker on the day of placement. However, over subsequent rounds it was observed that LRFI gilts spent less (P = 0.03) time standing, more time sitting (P = 0.05), and were less active (P = 0.03) overall. Gilts from the LRFI line had decreased (P < 0.045) lesion scores on the day after placement. However, over subsequent rounds there were no (P > 0.05) differences between the genetic lines. In conclusion, on the day of placement there were no postural, behavior, or general activity differences between genetic lines, but LRFI gilts had decreased lesion scores. Behavioral differences were observed between genetic lines over subsequent rounds, with LRFI gilts becoming less active, but there were no differences in lesion scores.

The objectives of this study were to determine the extent to which selection for decreased residual feed intake (RFI) affects pork composition and quality. Pigs from the fifth generation of selection for decreased RFI (select) and a randomly selected line (control) were utilized. Two experiments were conducted. In Exp. 1, barrows (22.6 ± 3.9 kg) from select and control lines were paired based on age and BW. The test was conducted in 8 replicates of pairs for the test period of 6 wk. Calpastatin activity and myosin isoforms profile were determined on samples from the LM. Control barrows were heavier (59.1 vs. 55.0 kg; P < 0.01) at the end of the test period. Calpastatin activity was greater (P < 0.01) in LM of select barrows than control barrows. In Exp. 2, composition and quality of gilts (114 kg) from control and select lines were determined. The model included fixed effects of line, slaughter date, melanocortin-4 receptor (MC4R) genotype, barn group, line × slaughter date, genotype × line interactions, a covariate of off-test BW, and sire, pen, and litter fitted as random effects. The select line (n = 80) had 0.043 kg less (P < 0.05) RFI per day than the control line (n = 89). Loin quality and composition were determined at 2 d postmortem. Desmin degradation was measured at 2 and 7 d postmortem. Purge, cook loss, sensory traits, and star probe texture were measured at 7 to 10 d postmortem on cooked chops. Residual correlations between RFI and composition and quality traits were calculated. Compared with the control line, carcasses from the select line tended to have less (P = 0.09) backfat, greater (P < 0.05) loin depth, and greater (P < 0.05) fat free lean. Loin chops from the select line had less (P < 0.01) intramuscular lipid content than loin chops from control line. Significant residual correlations between RFI and both tenderness (r = 0.24, P < 0.01) and star probe (r = -0.26, P < 0.01) were identified. Selection for decreased RFI has the potential to improve carcass composition with few effects on pH and water-holding capacity. However, decreased RFI could negatively affect tenderness and texture because of decreased lipid content and decreased postmortem protein degradation.

Residual feed intake (RFI), defined as the difference in the observed and expected feed intake while accounting for growth and backfat, has gained much attention, but little is known about why pigs selected for reduced RFI are more efficient. To this end, a line of Yorkshire pigs selected for reduced RFI was developed. The objective of this study was to evaluate the 5th generation of this select line against a randomly selected control line for performance, carcass and chemical carcass composition, and overall efficiency toward the later part of the growth phase. Eighty barrows, 40 from each line, were paired by age (~132 d, P < 0.60) and BW (74.8 ± 9.9 kg, P < 0.49) and randomly assigned to 1 of 4 feeding treatments in 10 replicates: 1) ad libitum, 2) 75% of ad libitum, 55% of ad libitum, and BW stasis, with weekly adjustments in intake to keep BW constant for each pig. Pigs were individually penned (group housing was used for selection) and on treatment for 6 wk. Initial BW did not differ between the lines (P < 0.49). The ad libitum select pigs consumed 10% less feed (P < 0.09) than the ad libitum control with no significant difference in BW (P < 0.80) and slight differences in carcass fat composition (P < 0.20) and backfat (P < 0.11), which resulted in significantly less carcass energy (P < 0.03). Under restricted feeding, the select line had an increase in BW (P = 0.10) while consuming the same ration of feed as the control line with no significant difference in chemical carcass composition and lighter visceral weights, which was significant for the 75% of ad libitum treatment (P < 0.01). Under BW stasis feeding the select line consumed 7.6% less feed overall (P = 0.21) and 18% less feed at the end of the 6 wk (P < 0.08), to maintain static BW with no significant difference in chemical carcass composition compared with the control line. Overall, the select line had lighter visceral weight (P < 0.02) and a greater dressing percentage (P < 0.03) compared with the control line. Using regression, the select line had reduced energy retention (P < 0.04) and feed energy utilization (P < 0.34); however, the select line appeared to have reduced maintenance requirements (P < 0.13). In conclusion, selection for reduced RFI decreases feed intake with no significant difference (P > 0.05) in growth performance, reduced backfat, increased dressing percentage, and reduced maintenance requirements. All of these traits are appealing to the producer and result in increased profits in the production setting.

Objectives: Fatigue is a common complaint of patients with primary Sjögren's syndrome (pSS), systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA). The aim of this study was to examine and compare in patients with these diseases the course of fatigue within the first hour after awakening and during the day, and to examine sleep disturbance as a potential determinant of fatigue., Methods: Eight repeated measurements at 5 fatigue dimensions were assessed on 2 consecutive days in the natural environment of female patients with pSS (n=29), SLE (n=23), RA (n=19), and healthy women (n=52). Sleep disturbance of the previous night was assessed. Fatigue levels and the change of fatigue after awakening and during the day were analysed with analyses of variance (adjusted for age)., Results: The patients showed significantly elevated levels at all fatigue dimensions as compared to healthy participants. Fatigue levels decreased in the first hour after awakening in patients with SLE and RA, but increased or did not change in patients with pSS. Fatigue progressively increased during the remainder of the day for all patient groups. Sleep disturbance correlated with overall fatigue levels, but hardly with the change of fatigue within the first hour after awakening., Conclusions: Our study confirms the presence of increased fatigue in patients with pSS, SLE, and RA. Patients with pSS failed to show a decrease in fatigue in the first hour after awakening. Future research should examine the causes of this difference in fatigue after awakening.

Background: Information for mapping of quantitative trait loci (QTL) comes from two sources: linkage disequilibrium (non-random association of allele states) and cosegregation (non-random association of allele origin). Information from LD can be captured by modeling conditional means and variances at the QTL given marker information. Similarly, information from cosegregation can be captured by modeling conditional covariances. Here, we consider a Bayesian model based on gene frequency (BGF) where both conditional means and variances are modeled as a function of the conditional gene frequencies at the QTL. The parameters in this model include these gene frequencies, additive effect of the QTL, its location, and the residual variance. Bayesian methodology was used to estimate these parameters. The priors used were: logit-normal for gene frequencies, normal for the additive effect, uniform for location, and inverse chi-square for the residual variance. Computer simulation was used to compare the power to detect and accuracy to map QTL by this method with those from least squares analysis using a regression model (LSR)., Results: To simplify the analysis, data from unrelated individuals in a purebred population were simulated, where only LD information contributes to map the QTL. LD was simulated in a chromosomal segment of 1 cM with one QTL by random mating in a population of size 500 for 1000 generations and in a population of size 100 for 50 generations. The comparison was studied under a range of conditions, which included SNP density of 0.1, 0.05 or 0.02 cM, sample size of 500 or 1000, and phenotypic variance explained by QTL of 2 or 5%. Both 1 and 2-SNP models were considered. Power to detect the QTL for the BGF, ranged from 0.4 to 0.99, and close or equal to the power of the regression using least squares (LSR). Precision to map QTL position of BGF, quantified by the mean absolute error, ranged from 0.11 to 0.21 cM for BGF, and was better than the precision of LSR, which ranged from 0.12 to 0.25 cM., Conclusions: In conclusion given a high SNP density, the gene frequency model can be used to map QTL with considerable accuracy even within a 1 cM region.

Data from a selection experiment for residual feed intake (RFI) were used to estimate genetic correlations between measures of efficiency and performance traits with juvenile IGF-I, and to demonstrate direct and correlated responses to selection. The heritability of IGF-I was 0.28 +/- 0.06 and genetic correlations of IGF-I with feed intake (0.26 +/- 0.17), backfat (0.52 +/- 0.11), and feed conversion ratio (0.78 +/- 0.14) were moderate to large. The estimated and realized genetic correlations between RFI and IGF-I were 0.63 +/- 0.15 and 0.84. In contrast, genetic correlations between IGF-I and lifetime or test period growth did not differ (P > 0.05) significantly from zero (0.06 +/- 0.14 and -0.19 +/- 0.14). Selection for decreased RFI produced a direct response in RFI, as expected, and was accompanied by downward correlated responses in ADFI, juvenile IGF-I, backfat, and growth traits, listed in order of decreasing relative magnitude, and an increased loin muscle area. The correlated response in IGF-I to selection on RFI demonstrates that this physiological measure is genetically associated with efficiency, and is thus useful as an early information source to estimate genetic merit for efficiency before performance testing. Decreased juvenile IGF-I is associated with leaner, more efficient animals.

Transcriptional profiling was used to identify genes and pathways that responded to intracerebroventricular injection of melanocortin-4 receptor (MC4R) agonist [Nle(4), d-Phe(7)]-α-melanocyte stimulating hormone (NDP-MSH) in pigs homozygous for the missense mutation in the MC4R, D298 allele (n = 12), N298 allele (n = 12), or heterozygous (n = 12). Food intake (FI) was measured at 12 and 24 h after treatment. All pigs were killed at 24 h after treatment, and hypothalamus, liver, and back-fat tissue was collected. NDP-MSH suppressed (P < 0.004) FI at 12 and 24 h in all animals after treatment. In response to NDP-MSH, 278 genes in hypothalamus (q ≤ 0.07, P ≤ 0.001), 249 genes in liver (q ≤ 0.07, P ≤ 0.001), and 5,066 genes in fat (q ≤ 0.07, P ≤ 0.015) were differentially expressed. Pathway analysis of NDP-MSH-induced differentially expressed genes indicated that genes involved in cell communication, nucleotide metabolism, and signal transduction were prominently downregulated in the hypothalamus. In both liver and adipose tissue, energy-intensive biosynthetic and catabolic processes were downregulated in response to NDP-MSH. This included genes encoding for biosynthetic pathways such as steroid and lipid biosynthesis, fatty acid synthesis, and amino acid synthesis. Genes involved in direct energy-generating processes, such as oxidative phosphorylation, electron transport, and ATP synthesis, were upregulated, whereas TCA-associated genes were prominently downregulated in NDP-MSH-treated pigs. Our data also indicate a metabolic switch toward energy conservation since genes involved in energy-intensive biosynthetic and catabolic processes were downregulated in NDP-MSH-treated pigs.

Residual feed intake (RFI) has become increasingly important and is being considered as a more reasonable approach to evaluate feed efficiency in livestock. However, the cost and technical difficulties in measuring this trait restrict the extensive adoption of RFI selection, and this makes marker assisted selection (MAS) a feasible tool. In addition, the effects on meat quality caused by low RFI selection have yet to be clarified. In this study, 11 SNPs from eight candidate genes were evaluated in a Yorkshire pig experimental population (n=169) consisting of a low RFI selection line and a randomly selected control line. Associations of these SNPs with RFI, growth rate, carcass composition, and meat quality measures including water holding capacity, pH at 2d postmortem, meat color and sensory traits were analyzed. The SNPs FTO p.Ala198Ala and TCF7L2 c.646+514A>G showed significant (P<0.05) and suggestively significant (P<0.1) associations with RFI, respectively. The MC4R SNP p.Asp298Asn was associated with backfat but it was not with ADG and meat quality attributes. Both SNPs within HNF1A were associated with intramuscular lipid content and sensory juiciness. The SNPs ACC1 c(*)384C>T and TCF7L2 c.646+514A>G were significantly (P<0.05) associated with ADG. The SNPs CTSZ p.Arg64Lys and TCF7L2 c.646+514A>G were associated with both visual scoring of meat color and the objective L-value measure of meat color. This study has identified potential genetic markers suitable for MAS in improving RFI, ADG, and meat color traits, but these associations need to be validated in other larger populations., (Published by Elsevier Ltd.)

Although concerns over the environmental impact of excess P in the excreta from pig production and governmental regulations have driven research toward reducing dietary supplementation of P to swine diets for over a decade, recent dramatic increases in feed costs have further motivated researchers to identify means to further reduce dietary P supplementation. We have demonstrated that genetic background impacts P utilization in young pigs and have identified genetic polymorphisms in several target genes related to mineral utilization. In this study, we examined the impact of a SNP in the calcitonin receptor gene (CALCR) on P utilization in growing pigs. In Exp. 1, 36 gilts representing the 3 genotypes identified by this CALCR SNP (11, 12, and 22) were fed a P-adequate (PA) or a marginally P-deficient (approximately 20% less available P; PD) diet for 14 wk. As expected, P deficiency reduced plasma P concentration, bone strength, and mineral content (P < 0.05). However, the dietary P deficiency was mild enough to not affect the growth performance of these pigs. A genotype x dietary P interaction (P < 0.05) was observed in measures of bone integrity and mineral content, with the greatest reduction in bone strength and mineral content due to dietary P deficiency being associated with the allele 1. In Exp. 2, 168 pigs from a control line and low residual feed intake (RFI) line were genotyped for the CALCR SNP and fed a PA diet. As expected, pigs from the low RFI line consumed less feed but also gained less BW when compared with the control line (P < 0.05). Although ADFI did not differ between genotypes, pigs having the 11 genotype gained less BW (P < 0.05) than pigs having the 12 or 22 genotypes. Pigs of the 11 and 12 genotypes had bones that tolerated greater load when compared with animals having the 22 genotype (P < 0.05). A similar trend was observed in bone modulus and ash % (P < 0.10). These data are supportive of the association of this CALCR SNP with bone integrity and its response to dietary P restriction. Although the allele 1 is associated with greater bone integrity and mineral content during adequate P nutrition, it is also associated with the greatest loss in bone integrity and mineral content in response to dietary P restriction. Understanding the underlying genetic mechanisms that regulate P utilization may lead to novel strategies to produce more environmentally friendly pigs.

Residual feed intake (RFI) is a measure of feed efficiency, in which low RFI denotes improved feed efficiency. Caloric restriction (CR) is associated with feed efficiency in livestock species and to human health benefits, such as longevity and cancer prevention. We have developed pig lines that differ in RFI, and we are interested in identifying the genes and pathways that underlie feed efficiency. Prepubertal Yorkshire gilts with low RFI (n = 10) or high RFI (n = 10) were fed ad libitum or fed at restricted intake of 80% of maintenance energy requirements for 8 days. We measured serum metabolites and hormones and generated transcriptional profiles of liver and subcutaneous adipose tissue on these animals. Overall, 6,114 genes in fat and 305 genes in liver were differentially expressed (DE) in response to CR, and 311 genes in fat and 147 genes in liver were DE due to RFI differences. Pathway analyses of CR-induced DE genes indicated a dramatic switch to a conservation mode of energy usage by down-regulating lipogenesis and steroidogenesis in both liver and fat. Interestingly, CR altered expression of genes in immune and cell cycle/apoptotic pathways in fat, which may explain part of the CR-driven lifespan enhancement. In silico analysis of transcription factors revealed ESR1 as a putative regulator of the adaptive response to CR, as several targets of ESR1 in our DE fat genes were annotated as cell cycle/apoptosis genes. The lipid metabolic pathway was overrepresented by down-regulated genes due to both CR and low RFI. We propose a common energy conservation mechanism, which may be controlled by PPARA, PPARG, and/or CREB in both CR and feed-efficient pigs.

In livestock, genomic selection (GS) has primarily been investigated by simulation of purebred populations. Traits of interest are, however, often measured in crossbred or mixed populations with uncertain breed composition. If such data are used as the training data for GS without accounting for breed composition, estimates of marker effects may be biased due to population stratification and admixture. To investigate this, a genome of 100 cM was simulated with varying marker densities (5 to 40 segregating markers per cM). After 1,000 generations of random mating in a population of effective size 500, 4 lines with effective size 100 were isolated and mated for another 50 generations to create 4 pure breeds. These breeds were used to generate combined, F(1), F(2), 3- and 4-way crosses, and admixed training data sets of 1,000 individuals with phenotypes for an additive trait controlled by 100 segregating QTL and heritability of 0.30. The validation data set was a sample of 1,000 genotyped individuals from one pure breed. Method Bayes-B was used to simultaneously estimate the effects of all markers for breeding value estimation. With 5 (40) markers per cM, the correlation of true with estimated breeding value of selection candidates (accuracy) was greatest, 0.79 (0.85), when data from the same pure breed were used for training. When the training data set consisted of crossbreds, the accuracy ranged from 0.66 (0.79) to 0.74 (0.83) for the 2 marker densities, respectively. The admixed training data set resulted in nearly the same accuracies as when training was in the breed to which selection candidates belonged. However, accuracy was greatly reduced when genes from the target pure breed were not included in the admixed or crossbred population. This implies that, with high-density markers, admixed and crossbred populations can be used to develop GS prediction equations for all pure breeds that contributed to the population, without a substantial loss of accuracy compared with training on purebred data, even if breed origin has not been explicitly taken into account. In addition, using GS based on high-density marker data, purebreds can be accurately selected for crossbred performance without the need for pedigree or breed information. Results also showed that haplotype segments with strong linkage disequilibrium are shorter in crossbred and admixed populations than in purebreds, providing opportunities for QTL fine mapping.

Background: Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals., Results: We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population., Conclusion: Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.

Background: The genome sequence and a high-density SNP map are now available for the chicken and can be used to identify genetic markers for use in marker-assisted selection (MAS). Effective MAS requires high linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), and sustained marker-QTL LD over generations. This study used data from a 3,000 SNP panel to assess the level and consistency of LD between single nucleotide polymorphisms (SNPs) over consecutive years in two egg-layer chicken lines, and analyzed one line by two methods (SNP-wise association and genome-wise Bayesian analysis) to identify markers associated with egg-quality and egg-production phenotypes., Results: The LD between markers pairs was high at short distances (r2 > 0.2 at < 2 Mb) and remained high after one generation (correlations of 0.80 to 0.92 at < 5 Mb) in both lines. Single- and 3-SNP regression analyses using a mixed model with SNP as fixed effect resulted in 159 and 76 significant tests (P < 0.01), respectively, across 12 traits. A Bayesian analysis called BayesB, that fits all SNPs simultaneously as random effects and uses model averaging procedures, identified 33 SNPs that were included in the model >20% of the time (phi > 0.2) and an additional ten 3-SNP windows that had a sum of phi greater than 0.35. Generally, SNPs included in the Bayesian model also had a small P-value in the 1-SNP analyses., Conclusion: High LD correlations between markers at short distances across two generations indicate that such markers will retain high LD with linked QTL and be effective for MAS. The different association analysis methods used provided consistent results. Multiple single SNPs and 3-SNP windows were significantly associated with egg-related traits, providing genomic positions of QTL that can be useful for both MAS and to identify causal mutations.