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BACKGROUND: Obesity is associated with multiple health problems, often originating in childhood. OBJECTIVE: The objective was to investigate differences in the development of adiposity from childhood to adulthood as related to race, sex, and socioeconomic status (SES). DESIGN: Individual growth curve modeling for waist circumference, body mass index, and sum of skinfold thicknesses (triceps, subscapular, and suprailiac) was performed in an 11-y cohort study of 622 African Americans and European Americans aged 4.2-27.5 y. We examined the development of adiposity in 2 ways: 1) differences related to race, sex, and parents' education (SES), and 2) differences between obese, overweight, and normal-weight persons at the end of their childhood (> 17 y of age). RESULTS: The sum of skinfold thicknesses was greater in females than in males, with a larger increase with age. Race, sex, and SES showed a complex relation with body mass index and the sum of skinfold thicknesses. The low-SES group showed the fastest increase in waist circumference with age. The obese group showed the most rapid increase in the 3 measures of adiposity. Growth curves for the obese group were distinguishable from those for the normal-weight persons at an earlier age for African Americans than for European Americans. CONCLUSIONS: The development rate of adiposity from childhood into early adulthood is influenced by sex and SES but not by race. However, race, sex, and SES had joint effects on adiposity levels. The development of obesity can begin to be distinguished in midchildhood, but the age at which this distinction becomes apparent depends on race. Copyright © 2004 American Society for Clinical Nutrition [ABSTRACT FROM AUTHOR]

To investigate the diurnal courses of cortisol and the daytime states: pain, fatigue, negative mood, and stiffness of patients with rheumatoid arthritis, as well as the association between the cortisol and state courses, 9 repeated measurements on 2 consecutive days were taken in the real-life environment of 25 recently diagnosed patients (19 women, 6 men; mean age 55.2 years) and 28 healthy controls (20 women, 8 men; mean age 55.8 years). Patients showed a highly characteristic diurnal course of cortisol (F8, 15 = 7.4, p < .001) and a significant diurnal fatigue (F7, 18 = 2.6, p < .05) and early morning stiffness course (F3, 22 = 6.2, p < .01), but the temporal association between these courses was low. Daytime states, notably fatigue (r = 0.40, p < .05), were positively correlated with the early morning rise of cortisol and nighttime pain (r ? 0.53, p < .01) but not with cortisol level or inflammatory activity. Cortisol level and inflammatory activity were positively correlated (r = 0.47, p < .05). These results suggest that in patients with rheumatoid arthritis, cortisol has a strong endogenous rhythm that is not disturbed by inflammatory activity. It appears that diurnal fluctuations in fatigue and stiffness are independent of the circadian rhythm of cortisol or inflammatory activity, but rather reflect temporal changes as a consequence of sleep, rest, and physical activity throughout the day. [ABSTRACT FROM AUTHOR]

In population studies, body mass index (BMI) is generally calculated from self-reported body weight and height. The self-report of these anthropometrics is known to be biased, resulting in a misclassification of BMI status. The aim of our study is to evaluate the accuracy of self-reported weight, height and waist circumference among a Dutch overweight (Body Mass Index [BMI] > or = 25 kg/m2) working population, and to determine to what extent the accuracy was moderated by sex, age, BMI, socio-economic status (SES) and health-related factors.~Background~Background~Both measured and self-reported body weight and body height were collected in 1298 healthy overweight employees (66.6% male; mean age 43.9 +/- 8.6 years; mean BMI 29.5 +/- 3.4 kg/m2), taking part in the ALIFE@Work project. Measured and self-reported waist circumferences (WC) were available for a sub-group of 250 overweight subjects (70.4% male; mean age 44.1 +/- 9.2 years; mean BMI 29.6 +/- 3.0 kg/m2). Intra Class Correlation (ICC), Cohen's kappa and Bland Altman plots were used for reliability analyses, while linear regression analyses were performed to assess the factors that were (independently) associated with the reliability.~Methods~Methods~Body weight was significantly (p < 0.001) under-reported on average by 1.4 kg and height significantly (p < 0.001) over-reported by 0.7 cm. Consequently, BMI was significantly (p < 0.001) under-reported by 0.7 kg/m2. WC was significantly (p < 0.001) over-reported by 1.1 cm. Although the self-reporting of anthropometrics was biased, ICC's showed high concordance between measured and self-reported values. Also, substantial agreement existed between the prevalences of BMI status and increased WC based on measured and self-reported data. The under-reporting of BMI and body weight was significantly (p < 0.05) affected by measured weight, height, SES and smoking status, and the over-reporting of WC by age, sex and measured WC.~Results~Results~Results suggest that self-reported BMI and WC are satisfactorily accurate for the assessment of the prevalence of overweight/obesity and increased WC in a middle-aged overweight working population. As the accuracy of self-reported anthropometrics is affected by measured weight, height, WC, smoking status and/or SES, results for these subgroups should be interpreted with caution. Due to the large power of our study, the clinical significance of our statistical significant findings may be limited.~Conclusion~Conclusions~ISRCTN04265725.~Trial Registration~Background [ABSTRACT FROM AUTHOR]

Pig production systems provide multiple benefits to humans. However, the global increase in meat consumption has profound consequences for our earth. This perspective describes two alternative scenarios for improving the sustainability of future pig production systems. The first scenario is a high input-high output system based on sustainable intensification, maximizing animal protein production efficiency on a limited land surface at the same time as minimizing environmental impacts. The second scenario is a reduced input-reduced output system based on selecting animals that are more robust to climate change and are better adapted to transform low quality feed (local feeds, feedstuff co-products, food waste) into meat. However, in contrast to the first scenario, the latter scenario results in reduced predicted yields, reduced production efficiency and possibly increased costs to the consumer. National evaluation of the availability of local feed and feedstuff co-product alternatives, determination of limits to feed sourced from international markets, available land for crop and livestock production, desired production levels, and a willingness to politically enforce policies through subsidies and/or penalties are some of the considerations to combine these two scenarios. Given future novel sustainable alternatives to livestock animal protein, it may become reasonable to move towards an added general premium price on 'protein from livestock animals' to the benefit of promoting higher incomes to farmers at the same time as covering the extra costs of, politically enforced, welfare of livestock animals in sustainable production systems. © 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

Severe combined immunodeficiency (SCID) is defined by the lack of an adaptive immune system. Mutations causing SCID are found naturally in humans, mice, horses, dogs, and recently in pigs, with the serendipitous discovery of the Iowa State University SCID pigs. As research models, SCID animals are naturally tolerant of xenotransplantation and offer valuable insight into research areas such as regenerative medicine, cancer therapy, as well as immune cell signaling mechanisms. Large-animal biomedical models, particularly pigs, are increasingly essential to advance the efficacy and safety of novel regenerative therapies on human disease. Thus, there is a need to create practical approaches to maintain hygienic severe immunocompromised porcine models for exploratory medical research. Such research often requires stable genetic lines for replication and survival of healthy SCID animals for months post-treatment. A further hurdle in the development of the ISU SCID pig as a biomedical model involved the establishment of facilities and protocols necessary to obtain clean SPF piglets from the conventional pig farm on which they were discovered. A colony of homozygous SCID boars and SPF carrier sows has been created and maintained through selective breeding, bone marrow transplants, innovative husbandry techniques, and the development of biocontainment facilities.

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

A major QTL for host response to porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) infection was identified in a previous study. Single nucleotide polymorphism WUR10000125 (WUR), which is in complete linkage disequilibrium with the putative causative mutation, can be used as a tag SNP for the QTL. However, the effect of WUR following PRRS vaccination and/or coinfection with other pathogens is not known. Therefore, objectives of this study were to estimate the effect of WUR on host response following PRRS vaccination and coinfection of PRRSV with porcine circovirus type 2b (PCV2b), to estimate genetic parameters for host response to vaccination and coinfection, and to estimate the effect of previously identified candidate SNP under PRRSV-only or PCV2b-only infection on host response to coinfection. Data from 2 trials, comprising a total of 396 commercial crossbred nursery pigs from a single genetic source, were used for all analyses. Pigs were preselected based on WUR genotype: approximately half AA and half AB, where B is the favorable and dominant allele. At weaning, pigs were shipped to Kansas State University, where half of the pigs were vaccinated with a PRRS modified live virus vaccine. Four weeks later, all pigs were coinfected with field strains of PRRSV and PCV2b and followed for 42 d. Body weight and serum viremia measurements were collected following vaccination and coinfection to calculate ADG and viral load (VL), respectively. Average heritability estimates for PRRS VL, PCV2b VL, and ADG were 0.29, 0.09, and 0.40, respectively. After vaccination, AB pigs had lower vaccination VL ( = 0.03) and faster gain ( = 0.004) than AA pigs, as expected. After coinfection, AB pigs had lower PRRSV VL ( < 0.001) but did not significantly differ from AA pigs in growth rate ( = 0.86). For PCV2b VL, suggestive evidence of an interaction between vaccination and WUR genotype ( = 0.11) was detected, where AB pigs had significantly lower PCV2b VL when vaccinated ( = 0.007) but not when they were not vaccinated ( = 0.87). In addition to WUR, several PRRS-associated SNP and a PCV2b-associated SNP had significant effects on host response to coinfection. In conclusion, marker-assisted selection based on WUR genotype alone, or along with other candidate SNP for PRRSV and PCV2b infection, is a promising strategy to select for improved host response to not just PRRS but also coinfection of PRRSV with PCV2b and perhaps other pathogens.

Influenza A viruses (IAV) infect many host species, including humans and pigs. Severe combined immunodeficiency (SCID) is a condition characterized by a deficiency of T, B, and/or natural killer (NK) cells. Animal models of SCID have great value for biomedical research. Here, we evaluated the pathogenesis and the innate immune response to the 2009 H1N1 pandemic IAV (H1N1pdm09) using a recently identified line of naturally occurring SCID pigs deficient in T and B lymphocytes that still have functional NK cells. SCID pigs challenged with H1N1pdm09 showed milder lung pathology compared to the non-SCID heterozygous carrier pigs. Viral titers in the lungs and nasal swabs of challenged SCID pigs were significantly higher than in carrier pigs 7 days postinfection, despite higher levels of IL-1β and IFN-α in the lungs of SCID pigs. The lower levels of pulmonary pathology were associated with the T and B cell absence in response to infection. The higher viral titers, prolonged shedding, and delayed viral clearance indicated that innate immunity was insufficient for controlling IAV in pigs. This recently identified line of SCID pigs provides a valuable model to understand the immune mechanisms associated with influenza protection and recovery in a natural host., (© 2016 S. Karger AG, Basel.)

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease in the swine industry. Identification of host genetic factors that enable selection for improved performance during PRRS virus (PRRSV) infection would reduce the impact of this disease on animal welfare and production efficiency. We conducted genomewide association study (GWAS) analyses of data from 13 trials of approximately 200 commercial crossbred nursery-age piglets that were experimentally infected with 1 of 2 type 2 isolates of PRRSV (NVSL 97-7985 [NVSL] and KS2006-72109 [KS06]). Phenotypes analyzed were viral load (VL) in blood during the first 21 d after infection (dpi) and weight gain (WG) from 0 to 42 dpi. We accounted for the previously identified QTL in the region on SSC4 in our models to increase power to identify additional regions. Many regions identified by single-SNP analyses were not identified using Bayes-B, but both analyses identified the same regions on SSC3 and SSC5 to be associated with VL in the KS06 trials and on SSC6 in the NVSL trials ( < 5 × 10); for WG, regions on SSC5 and SSC17 were associated in the NVSL trials ( < 3 × 10). No regions were identified with either method for WG in the KS06 trials. Except for the region on SSC4, which was associated with VL for both isolates (but only with WG for NVSL), identified regions did not overlap between the 2 PRRSV isolate data sets, despite high estimates of the genetic correlation between isolates for traits based on these data. We also identified genomic regions whose associations with VL or WG interacted with either PRRSV isolate or with genotype at the SSC4 QTL. Gene ontology (GO) annotation terms for genes located near moderately associated SNP ( < 0.003) were enriched for multiple immunologically (VL) and metabolism- (WG) related GO terms. The biological relevance of these regions suggests that, although it may increase the number of false positives, the use of single-SNP analyses and a relaxed threshold also increased the identification of true positives. In conclusion, although only the SSC4 QTL was associated with response to both PRRSV isolates, genes near associated SNP were enriched for the same GO terms across PRRSV isolates, suggesting that host responses to these 2 isolates are affected by the actions of many genes that function together in similar biological processes.

Shell quality is one of the most important traits for improvement in layer chickens. Proper consideration of repeated records can increase the accuracy of estimated breeding values and thus genetic improvement of shell quality. The objective of this study was to compare different models for genetic evaluation of the collected data. For this study, 81,646 dynamic stiffness records on 21,321 brown egg layers and 93,748 records on 24,678 white egg layers from 4 generations were analyzed. Across generations, data were collected at 2 to 4 ages (at approximately 26, 42, 65, and 86 wk), with repeated records at each age. Seven models were compared, including 5 repeatability models with increasing complexity, a random regression model, and a multitrait model. The models were compared using Akaike Information Criteria with significance testing of nested models with a Log Likelihood Ratio test. Estimates of heritability were 0.31-0.36 for the brown line and 0.23-0.26 for the white line, but repeatability was higher for the model with age-specific permanent environment effects (0.59 for both lines) than for the model with an overall permanent environmental effects (0.47 for the brown and 0.41 for the white line). The model that allowed for permanent environmental effect within age and heterogeneous residual variance between ages resulted in improved fit compared to the traditional model that fits single permanent environment and residual effects, but was inferior in fit and predictive ability to the full multiple-trait model. The random regression model had better fit to the data than repeatability models but slightly worse than the multiple-trait model. For traits with repeated records at different ages, repeatability within and across ages as well as genetic correlations should be considered while choosing the number of records collected per individual as well as the model for genetic evaluation.

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

As feed costs continue to rise and efficiency during finishing is emphasized, the impact of selecting for more efficient grow/finish pigs on reproductive performance and feed efficiency of sows must be evaluated. Therefore, the objectives of this study were to evaluate correlated responses for sow reproductive performance and lactation feed efficiency to selection for residual feed intake (RFI) during the grow/finish phase of production (RFI) in 2 selection lines of pigs developed at Iowa State University (Ames, IA) and to estimate heritabilities of these traits. One line was selected over 7 generations for decreased RFIG/F (low RFI [LRFI] line) and the other line was randomly selected for 5 generations and then selected for increased RFIG/F (high RFI [HRFI] line). After 7 generations of selection, LRFI sows had 1.0 more piglets farrowed ( = 0.11) compared with HRFI sows, 1.3 more pigs born alive ( < 0.05), similar farrowing survival, 0.4 fewer mummies ( < 0.01), and more piglets weaned, both by litter (1.6 more; < 0.01) and by sow (1.1 more; < 0.01). Low RFI sows consumed 25 kg less feed and lost 9.8 kg more BW, 7.0 kg more fat mass, and 3.1 mm more backfat than HRFI sows ( < 0.001) during lactation. Although LRFI sows had a greater negative energy balance (-19.8 vs. -8.0 MJ ME/d; < 0.001), they had better RFI during lactation (-28.6 vs. 8.2 kg; < 0.0001), and the trend was for LRFI sows to have better lactation efficiency (61.3 vs. 57.8%; = 0.47) than HRFI sows. Heritabilities for sow weights, sow body composition, sow maintenance requirements (estimated from BW), and piglet birth weight were high ( > 0.4, SE < 0.07). Traits pertaining to piglet growth during lactation and mobilization of body tissue of the sow were moderately heritable (0.2 < < 0.4, SE < 0.07). In conclusion, selection for decreased RFI has favorably affected piglet performance and lactation efficiency but has unfavorably affected sow body condition loss and energy balance during lactation. These results indicate that pigs selected for increased efficiency during grow-finish are better able to direct resources where needed during other life history phases, that is, reproduction and lactation.

Most genomic prediction studies fit only additive effects in models to estimate genomic breeding values (GEBV). However, if dominance genetic effects are an important source of variation for complex traits, accounting for them may improve the accuracy of GEBV. We investigated the effect of fitting dominance and additive effects on the accuracy of GEBV for eight egg production and quality traits in a purebred line of brown layers using pedigree or genomic information (42K single-nucleotide polymorphism (SNP) panel). Phenotypes were corrected for the effect of hatch date. Additive and dominance genetic variances were estimated using genomic-based [genomic best linear unbiased prediction (GBLUP)-REML and BayesC] and pedigree-based (PBLUP-REML) methods. Breeding values were predicted using a model that included both additive and dominance effects and a model that included only additive effects. The reference population consisted of approximately 1800 animals hatched between 2004 and 2009, while approximately 300 young animals hatched in 2010 were used for validation. Accuracy of prediction was computed as the correlation between phenotypes and estimated breeding values of the validation animals divided by the square root of the estimate of heritability in the whole population. The proportion of dominance variance to total phenotypic variance ranged from 0.03 to 0.22 with PBLUP-REML across traits, from 0 to 0.03 with GBLUP-REML and from 0.01 to 0.05 with BayesC. Accuracies of GEBV ranged from 0.28 to 0.60 across traits. Inclusion of dominance effects did not improve the accuracy of GEBV, and differences in their accuracies between genomic-based methods were small (0.01-0.05), with GBLUP-REML yielding higher prediction accuracies than BayesC for egg production, egg colour and yolk weight, while BayesC yielded higher accuracies than GBLUP-REML for the other traits. In conclusion, fitting dominance effects did not impact accuracy of genomic prediction of breeding values in this population., (© 2016 Blackwell Verlag GmbH.)

Background: Our recent research showed that antibody response to porcine reproductive and respiratory syndrome (PRRS), measured as sample-to-positive (S/P) ratio, is highly heritable and has a high genetic correlation with reproductive performance during a PRRS outbreak. Two major quantitative trait loci (QTL) on Sus scrofa chromosome 7 (SSC7; QTLMHC and QTL130) accounted for ~40 % of the genetic variance for S/P. Objectives of this study were to estimate genetic parameters for PRRS S/P in gilts during acclimation, identify regions associated with S/P, and evaluate the accuracy of genomic prediction of S/P across populations with different prevalences of PRRS and using different single nucleotide polymorphism (SNP) sets., Methods: Phenotypes and high-density SNP genotypes of female pigs from two datasets were used. The outbreak dataset included 607 animals from one multiplier herd, whereas the gilt acclimation (GA) dataset included data on 2364 replacement gilts from seven breeding companies placed on health-challenged farms. Genomic prediction was evaluated using GA for training and validation, and using GA for training and outbreak for validation. Predictions were based on SNPs across the genome (SNPAll), SNPs in one (SNPMHC and SNP130) or both (SNPSSC7) QTL, or SNPs outside the QTL (SNPRest)., Results: Heritability of S/P in the GA dataset increased with the proportion of PRRS-positive animals in the herd (from 0.28 to 0.47). Genomic prediction accuracies ranged from low to moderate. Average accuracies were highest when using only the 269 SNPs in both QTL regions (SNPSSC7, with accuracies of 0.39 and 0.31 for outbreak and GA validation datasets, respectively. Average accuracies for SNPALL, SNPMHC, SNP130, and SNPRest were, respectively, 0.26, 0.39, 0.21, and 0.05 for the outbreak, and 0.28, 0.25, 0.22, and 0.12, for the GA validation datasets., Conclusions: Moderate genomic prediction accuracies can be obtained for PRRS antibody response using SNPs located within two major QTL on SSC7, while the rest of the genome showed limited predictive ability. Results were obtained using data from multiple genetic sources and farms, which further strengthens these findings. Further research is needed to validate the use of S/P ratio as an indicator trait for reproductive performance during PRRS outbreaks.

We have identified Severe Combined Immunodeficiency (SCID) in a line of Yorkshire pigs at Iowa State University. These SCID pigs lack B-cells and T-cells, but possess Natural Killer (NK) cells. This SCID phenotype is caused by recessive mutations in the Artemis gene. Interestingly, two human tumor cell lines, PANC-1 and A375-SM, survived after injection into these SCID pigs, but, as we demonstrate here, these cells, as well as K562 tumor cells, can be lysed in vitro by NK cells from SCID and non-SCID pigs. NK cells from both SCID and non-SCID pigs required activation in vitro with either recombinant human IL-2 or the combination of recombinant porcine IL-12 and IL-18 to kill tumor targets. We also showed that SCID NK cells could be activated to produce perforin, and perforin production was greatly enhanced in NK cells from both SCID and non-SCID pigs after IL-2 cytokine treatment. While CD16+, CD172- NK cells constituted an average of only 4% in non-SCID pigs, NK cells averaged 27% of the peripheral blood mononuclear cell population in SCID pigs. We found no significant differences in killing activity per NK cell between SCID and non-SCID pigs. We conclude that survival of human cancer cells in these SCID pigs is not due to an intrinsic defect in NK cell killing ability., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background: Porcine reproductive and respiratory syndrome (PRRS) is one of the most important swine diseases in the world and genetic selection of pigs for increased resistance to PRRS is an attractive method to improve the health status of the swine herd. This study compared phenotypic and genetic responses to infection with one of two genetically distinct type 2 PRRS virus (PRRSV) isolates: NVSL-97-7895 (NVSL) and KS-2006-72109 (KS06), and evaluated whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) on chromosome 4 that was associated with viral load and weight gain under infection with NVSL also has an effect on response to infection across North American PRRSV isolates. Wood's lactation curve was fitted to repeated viremia measurements to derive five curve characteristics that were evaluated., Results: Infection with NVSL was characterized by reaching a 14 ± 2 % higher peak viremia (PV) 2.5 ± 0.6 days earlier (time to peak; TP) than KS06, followed by 36 ± 1 % faster virus clearance, which occurred 3.9 ± 0.7 days sooner. Weight gain from 0 to 42 days post-infection (WG) tended to be higher under infection with KS06 than NVSL (3.7 ± 1.5 kg). Estimates of heritability were moderate for both PRRSV isolates for viral load from 0 to 21 days post-infection (VL) (NVSL: 0.31 ± 0.06; KS06: 0.51 ± 0.09) and WG (NVSL: 0.33 ± 0.06; KS06: 0.31 ± 0.09). Strong negative genetic correlations were observed between VL and WG for both NVSL (-0.74 ± 0.10) and KS06 (-0.52 ± 0.17) infected pigs. Pigs with genotype AB at the WUR SNP had a more desirable phenotype than AA pigs for all traits under infection with NVSL, but only for VL and PV with KS06; effects on other traits were smaller and not significantly different from zero (P > 0.05). Genetic correlations of host response between isolates were strong for VL, WG and PV. Accounting for WUR genotype had little impact on these correlations, suggesting that response to PRRSV infection has a substantial polygenic component that is common between these two isolates., Conclusions: These results suggest that the KS06 PRRSV isolate is less virulent than NVSL but that genetic selection for increased resistance to either of these genetically distinct isolates is expected to increase resistance to the other isolate.

Lactation is an economically and biologically important phase in the life cycle of sows. Short generation intervals in nucleus herds and low heritability of traits associated with lactation along with challenges associated with collecting accurate lactation performance phenotypes emphasize the importance of using genomic tools to examine the underlying genetics of these traits. We report the first genomewide association study (GWAS) on traits associated with lactation and efficiency in 2 lines of Yorkshire pigs that were divergently selected for residual feed intake during grow-finish phase. A total of 862 farrowing records from 2 parities were analyzed using a Bayesian whole genome variable selection model (Bayes B) to locate 1-Mb regions that were most strongly associated with each trait. The GWAS was conducted separately for parity 1 and 2 records. Marker-based heritabilities ranged from 0.03 to 0.39 for parity 1 traits and from 0.06 to 0.40 for parity 2 traits. For all traits studied, around 90% of genetic variance came from a large number of genomic regions with small effects, whereas genomic regions with large effects were found to be different for the same trait measured in parity 1 and 2. The highest percentage of genetic variance explained by a 1-Mb window for each trait ranged from 0.4% for feed intake during lactation to 4.2% for back fat measured at farrowing in parity 1 sows and from 0.2% for lactation feed intake to 5.4% for protein mass loss during lactation in parity 2 sows. A total of thirteen 1-Mb nonoverlapping windows were found to explain more than 1.5% of genetic variance for either a single trait or across multiple traits. These 1-Mb windows were on chromosomes 2, 3, 6, 7, 8, 11, 14, 15, 17, and 18. The major positional candidate genes within 1 Mb upstream and downstream of these windows were , (SSC2), (SSC6) (SSC7), (SSC8), (SSC11), (SSC14), (SSC17). Further validation studies on larger populations are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with sow lactation performance.

Identification of biomarkers for feed efficiency in livestock will aid in the efficient production of high-quality protein to meet the demands of a growing population. The overall objective of this research was to identify biomarkers in serum for swine feed efficiency and to discover pathways affected by divergent selection for residual feed intake (RFI). Serum was collected from young pigs (between 35 and 42 d of age) from 2 lines of pigs that have been genetically selected to be either more efficient (low-RFI) or less efficient (high-RFI). After blood collection, during finishing, pigs from each line were placed on either a low-energy/high-fiber diet or a traditional high-energy/low-fiber diet to test for any diet effects on RFI. Subsets of 6 pigs per line within each diet were used in 3 independent experiments. Pigs with extreme RFI phenotypes from the low-energy/high-fiber diet were used to confirm the results from the first 2 comparisons. Two-dimensional difference in gel electrophoresis and mass spectrometry were used to identify proteins with different abundances between RFI line or finishing diet. Three proteins had consistent and significant ( < 0.05) RFI line differences for both diets: gelsolin, vitronectin, and serine protease inhibitor A3 (serpinA3). Abundance of gelsolin, a protein with roles in actin filament assembly and immune response, was greater in the more efficient low-RFI pigs (9 to 39%). Vitronectin was also more abundant in the low-RFI pigs (39 to 56%) and has known roles in blood homeostasis and may regulate adiposity. SerpinA3 is a member of a very large family of proteins referred to as serine protease inhibitors. A total of 14 spots that were more abundant in the low-RFI line, some at least twice as abundant, were identified as serpinA3. Multiple isoforms of serpinA3 have been reported (serpinA3-1 to serpinA3-4 in pigs and serpinA3-1 to serpinA3-8 in cattle) with serpinA3 having many different functions dependent on isoform. Gelsolin, vitronectin, and serpinA3 are 3 proteins that may play direct and important biological roles in the pathways that control RFI and, ultimately, feed efficiency through energy utilization and homeostasis. These data demonstrate that serum proteins can be a useful source of potential biomarkers for feed efficiency and provide information on pathways with distinct expression patterns between animals that differ in feed efficiency.

Intramuscular fat (IMF) content and fatty acid composition affect the organoleptic quality and nutritional value of pork. A genome-wide association study was performed on 138 Duroc pigs genotyped with a 60k SNP chip to detect biologically relevant genomic variants influencing fat content and composition. Despite the limited sample size, the genome-wide association study was powerful enough to detect the association between fatty acid composition and a known haplotypic variant in SCD (SSC14) and to reveal an association of IMF and fatty acid composition in the LEPR region (SSC6). The association of LEPR was later validated with an independent set of 853 pigs using a candidate quantitative trait nucleotide. The SCD gene is responsible for the biosynthesis of oleic acid (C18:1) from stearic acid. This locus affected the stearic to oleic desaturation index (C18:1/C18:0), C18:1, and saturated (SFA) and monounsaturated (MUFA) fatty acids content. These effects were consistently detected in gluteus medius, longissimus dorsi, and subcutaneous fat. The association of LEPR with fatty acid composition was detected only in muscle and was, at least in part, a consequence of its effect on IMF content, with increased IMF resulting in more SFA, less polyunsaturated fatty acids (PUFA), and greater SFA/PUFA ratio. Marker substitution effects estimated with a subset of 65 animals were used to predict the genomic estimated breeding values of 70 animals born 7 years later. Although predictions with the whole SNP chip information were in relatively high correlation with observed SFA, MUFA, and C18:1/C18:0 (0.48-0.60), IMF content and composition were in general better predicted by using only SNPs at the SCD and LEPR loci, in which case the correlation between predicted and observed values was in the range of 0.36 to 0.54 for all traits. Results indicate that markers in the SCD and LEPR genes can be useful to select for optimum fatty acid profiles of pork.

Background: Genomic estimated breeding values (GEBV) based on single nucleotide polymorphism (SNP) genotypes are widely used in animal improvement programs. It is typically assumed that the larger the number of animals is in the training set, the higher is the prediction accuracy of GEBV. The aim of this study was to quantify genomic prediction accuracy depending on the number of ancestral generations included in the training set, and to determine the optimal number of training generations for different traits in an elite layer breeding line., Methods: Phenotypic records for 16 traits on 17,793 birds were used. All parents and some selection candidates from nine non-overlapping generations were genotyped for 23,098 segregating SNPs. An animal model with pedigree relationships (PBLUP) and the BayesB genomic prediction model were applied to predict EBV or GEBV at each validation generation (progeny of the most recent training generation) based on varying numbers of immediately preceding ancestral generations. Prediction accuracy of EBV or GEBV was assessed as the correlation between EBV and phenotypes adjusted for fixed effects, divided by the square root of trait heritability. The optimal number of training generations that resulted in the greatest prediction accuracy of GEBV was determined for each trait. The relationship between optimal number of training generations and heritability was investigated., Results: On average, accuracies were higher with the BayesB model than with PBLUP. Prediction accuracies of GEBV increased as the number of closely-related ancestral generations included in the training set increased, but reached an asymptote or slightly decreased when distant ancestral generations were used in the training set. The optimal number of training generations was 4 or more for high heritability traits but less than that for low heritability traits. For less heritable traits, limiting the training datasets to individuals closely related to the validation population resulted in the best predictions., Conclusions: The effect of adding distant ancestral generations in the training set on prediction accuracy differed between traits and the optimal number of necessary training generations is associated with the heritability of traits.

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

Background: Accurate evaluation of SNP effects is important for genome wide association studies and for genomic prediction. The genetic architecture of quantitative traits differs widely, with some traits exhibiting few if any quantitative trait loci (QTL) with large effects, while other traits have one or several easily detectable QTL with large effects., Methods: Body weight in broilers and egg weight in layers are two examples of traits that have QTL of large effect. A commonly used method for genome wide association studies is to fit a mixture model such as BayesB that assumes some known proportion of SNP effects are zero. In contrast, the most commonly used method for genomic prediction is known as GBLUP, which involves fitting an animal model to phenotypic data with the variance-covariance or genomic relationship matrix among the animals being determined by genome wide SNP genotypes. Genotypes at each SNP are typically weighted equally in determining the genomic relationship matrix for GBLUP. We used the equivalent marker effects model formulation of GBLUP for this study. We compare these two classes of models using egg weight data collected over 8 generations from 2,324 animals genotyped with a 42 K SNP panel., Results: Using data from the first 7 generations, both BayesB and GBLUP found the largest QTL in a similar well-recognized QTL region, but this QTL was estimated to account for 24 % of genetic variation with BayesB and less than 1 % with GBLUP. When predicting phenotypes in generation 8 BayesB accounted for 36 % of the phenotypic variation and GBLUP for 25 %. When using only data from any one generation, the same QTL was identified with BayesB in all but one generation but never with GBLUP. Predictions of phenotypes in generations 2 to 7 based on only 295 animals from generation 1 accounted for 10 % phenotypic variation with BayesB but only 6 % with GBLUP. Predicting phenotype using only the marker effects in the 1 Mb region that accounted for the largest effect on egg weight from generation 1 data alone accounted for almost 8 % variation using BayesB but had no predictive power with GBLUP., Conclusions: In conclusion, In the presence of large effect QTL, BayesB did a better job of QTL detection and its genomic predictions were more accurate and persistent than those from GBLUP.

Background: Improving feed efficiency (FE) of pigs by genetic selection is of economic and environmental significance. An increasingly accepted measure of feed efficiency is residual feed intake (RFI). Currently, the molecular mechanisms underlying RFI are largely unknown. Additionally, to incorporate RFI into animal breeding programs, feed intake must be recorded on individual pigs, which is costly and time-consuming. Thus, convenient and predictive biomarkers for RFI that can be measured at an early age are greatly desired. In this study, we aimed to explore whether differences exist in the global gene expression profiles of peripheral blood of 35 to 42 day-old pigs with extremely low (more efficient) and high RFI (less efficient) values from two lines that were divergently selected for RFI during the grow-finish phase, to use such information to explore the potential molecular basis of RFI differences, and to initiate development of predictive biomarkers for RFI., Results: We identified 1972 differentially expressed genes (DEGs) (q ≤ 0.15) between the low (n = 15) and high (n = 16) RFI groups of animals by using RNA sequencing technology. We validated 24 of 37 selected DEGs by reverse transcription-quantitative PCR (RT-qPCR) in a joint analysis of 24 (12 per line) of the 31 samples already used for RNA-seq plus 24 (12 per line) novel samples from the same contemporary group of pigs. Using an analysis of the 24 novel samples alone, only nine of the 37 selected DEGs were validated. Genes involved in small molecule biosynthetic process, antigen processing and presentation of peptide antigen via major histocompatibility complex (MHC) class I, and steroid biosynthetic process were overrepresented among DEGs that had higher expression in the low versus high RFI animals. Genes known to function in the proteasome complex or mitochondrion were also significantly enriched among genes with higher expression in the low versus high RFI animals. Alternatively, genes involved in signal transduction, bone mineralization and regulation of phosphorylation were overrepresented among DEGs with lower expression in the low versus high RFI animals. The DEGs significantly overlapped with genes associated with disease, including hyperphagia, eating disorders and mitochondrial diseases (q < 1E-05). A weighted gene co-expression network analysis (WGCNA) identified four co-expression modules that were differentially expressed between the low and high RFI groups. Genes involved in lipid metabolism, regulation of bone mineralization, cellular immunity and response to stimulus were overrepresented within the two modules that were most significantly differentially expressed between the low and high RFI groups. We also found five of the DEGs and one of the co-expression modules were significantly associated with the RFI phenotype of individual animals (q < 0.05)., Conclusions: The post-weaning blood transcriptome was clearly different between the low and high RFI groups. The identified DEGs suggested potential differences in mitochondrial and proteasomal activities, small molecule biosynthetic process, and signal transduction between the two RFI groups and provided potential new insights into the molecular basis of RFI in pigs, although the observed relationship between the post-weaning blood gene expression and RFI phenotype measured during the grow-finish phase was not strong. DEGs and representative genes in co-expression modules that were associated with RFI phenotype provide a preliminary list for developing predictive biomarkers for RFI in pigs.

Coinfections involving porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) contribute to a group of disease syndromes known as porcine circovirus-associated disease (PCVAD). Presumably, PRRSV infection enhances PCV2 replication as a result of modulation of host immunity. The purpose of this study was to evaluate PCV2 replication and pathogenesis in pigs vaccinated with a PRRS modified live virus (MLV) vaccine and subsequently challenged with a combination of PRRSV and PCV2. During the early postchallenge period, the number of pigs with PRRSV-associated clinical signs was decreased, and average daily gain (ADG) was increased, in the vaccinated group, demonstrating the protective effect of PRRS vaccination. However, during the later postchallenge period, more pigs in the vaccinated group showed increased PCV2 viremia, decreased ADG, increased PCVAD clinical signs, and increased mortality. In this disease model, the early benefits of PRRSV vaccination were outweighed by the later amplification of PCVAD., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Mutations in >30 genes are known to result in impairment of the adaptive immune system, causing a group of disorders collectively known as SCID. SCID disorders are split into groups based on their presence and/or functionality of B, T, and NK cells. Piglets from a line of Yorkshire pigs at Iowa State University were shown to be affected by T(-)B(-)NK(+) SCID, representing, to our knowledge, the first example of naturally occurring SCID in pigs. In this study, we present evidence for two spontaneous mutations as the molecular basis for this SCID phenotype. Flow cytometry analysis of thymocytes showed an increased frequency of immature T cells in SCID pigs. Fibroblasts from these pigs were more sensitive to ionizing radiation than non-SCID piglets, eliminating the RAG1 and RAG2 genes. Genetic and molecular analyses showed that two mutations were present in the Artemis gene, which in the homozygous or compound heterozygous state cause the immunodeficient phenotype. Rescue of SCID fibroblast radiosensitivity by human Artemis protein demonstrated that the identified Artemis mutations are the direct cause of this cellular phenotype. The work presented in the present study reveals two mutations in the Artemis gene that cause T(-)B(-)NK(+) SCID in pigs. The SCID pig can be an important biomedical model, but these mutations would be undesirable in commercial pig populations. The identified mutations and associated genetic tests can be used to address both of these issues., (Copyright © 2015 by The American Association of Immunologists, Inc.)

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

Background: Genomic selection (GS) using estimated breeding values (GS-EBV) based on dense marker data is a promising approach for genetic improvement. A simulation study was undertaken to illustrate the opportunities offered by GS for designing breeding programs. It consisted of a selection program for a sex-limited trait in layer chickens, which was developed by deterministic predictions under different scenarios. Later, one of the possible schemes was implemented in a real population of layer chicken., Methods: In the simulation, the aim was to double the response to selection per year by reducing the generation interval by 50 %, while maintaining the same rate of inbreeding per year. We found that GS with retraining could achieve the set objectives while requiring 75 % fewer reared birds and 82 % fewer phenotyped birds per year. A multi-trait GS scenario was subsequently implemented in a real population of brown egg laying hens. The population was split into two sub-lines, one was submitted to conventional phenotypic selection, and one was selected based on genomic prediction. At the end of the 3-year experiment, the two sub-lines were compared for multiple performance traits that are relevant for commercial egg production., Results: Birds that were selected based on genomic prediction outperformed those that were submitted to conventional selection for most of the 16 traits that were included in the index used for selection. However, although the two programs were designed to achieve the same rate of inbreeding per year, the realized inbreeding per year assessed from pedigree was higher in the genomic selected line than in the conventionally selected line., Conclusions: The results demonstrate that GS is a promising alternative to conventional breeding for genetic improvement of layer chickens.

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

The objective was to determine the extent to which feeding low-energy, high-fiber (LEHF) and high-energy, low-fiber (HELF) diets impacts meat quality and carcass composition of pigs divergently selected for residual feed intake (RFI). Two experiments were conducted in the divergently selected Iowa State University RFI lines: Exp. 1 evaluated carcasses of generation (G) 8 pigs fed on commercial feeders; Exp. 2 evaluated composition, pork quality, sensory, and postmortem proteolysis of pigs fed on electronic single-space feeders in G 8 and 9. Pigs (N = 177) in Exp. 1 were randomly assigned a pen (mixed sex and line; N = 8). Groups (n = 3) of pigs were slaughtered at a mean BW of 121.5 kg. Pigs in Exp. 2 (G8: n = 158; G9: n = 157) were randomly assigned to 1 of 6 pens of each diet per G. Pigs from G8 were slaughtered at a mean BW of 122.5 kg and G9 at a mean of 128.4 kg. Data were analyzed using the mixed procedure of SAS. Fixed effects were line, diet, sex, and all appropriate interactions. Random effects were group, pen, litter, and sire and covariate of off-test BW. For Exp. 2, G was added as a fixed effect and sensory day was added as a random effect when applicable. In Exp. 1, carcasses from low RFI (LRFI) pigs were leaner and had less fat depth (P < 0.01). Carcasses from pigs fed the LEHF diet had a lighter HCW and greater estimated percent lean than pigs fed HELF diet (P < 0.01). In Exp. 2, LRFI pigs on the HELF diet had the greatest loin depth (P < 0.01). Chops from HRFI pigs had greater drip loss, color scores, lean tissue a*, and percent lipid and lesser percent moisture than LRFI ( P< 0.05). Chops from pigs on the LEHF diet had lesser muscle L* values and greater percent moisture than chops from pigs fed the HELF diet (P < 0.05). Chops from LRFI pigs were juicer than those from HRFI pigs (P < 0.05). Protein extracted at d 2 postmortem from LRFI pigs on the LEHF diet had a greater 38 kDa desmin degradation product than protein from LRFI pigs fed the HELF diet (P < 0.05). Day 5 postmortem extracted protein from HRFI pigs had greater 38 kDa desmin degradation product than LRFI (P = 0.05). Pigs fed LEHF (P < 0.01) had adipose with a greater iodine value than adipose from HELF fed pigs. Pork sensory quality from pigs differentially selected for residual feed intake was not influenced by energy content of the diet the pigs were fed.

Improving the ability to predict livestock performance using biomarkers will provide a benefit for livestock genetic evaluation and improvement. The most practical biological sample to screen for development of biomarkers is serum due to the ease of collection. However, protein profiles in serum are complex and dynamic. Strategies are needed to manage variation in serum proteins used for biomarker identification. Albumin is the most abundant protein in serum, comprising over 50% of the overall protein content, and has historically been depleted from serum before biomarker identification. The objective of this study was to investigate the use of gel-based proteomic techniques to evaluate the need for porcine albumin depletion in biomarker identification. Albumin is known to bind many proteins in the blood, thus potential biomarkers could be removed during albumin depletion. Using two-dimensional difference in gel electrophoresis (2D-DIGE), we show whole serum can be used for biomarker discovery. The data obtained show that albumin removal methods are effective for porcine sera. Over 85% of the protein spots resolved on at least half of the gels were changed in abundance between whole and albumin depleted sera. Of the 204 protein spots significantly altered in abundance, 59 were changed over 400%. However, albumin removal also altered the serum proteome in an unpredictable manner; in the depleted sera, 86 protein spots were increased in abundance and 118 were decreased. Furthermore, the abundance of 59.4% of the protein spots in the albumin depleted samples had a larger standard error than whole sera. However, the resolution of albumin in 2D-DIGE analysis of whole sera permitted the detection and quantification of substantial numbers of proteins. Thus, it is proposed that whole serum can be used in a gel-based proteomics system for the identification of porcine biomarkers.

The cost of feed is a serious issue in the pork industry, contributing about 65 to 75% of the total production cost. To prevent economic losses and decreased productivity of the herd, it is important to select for animals that eat less for the same lean gain, or more efficient animals. Residual feed intake (RFI) is the difference between observed feed intake and expected feed intake based on estimated maintenance and production requirements. Selection for decreased RFI, or more efficient animals, is a potential solution to higher feed costs in pig production. However, animals that are highly selected for decreased RFI may have reduced energy input to the immune system and fail to withstand diseases and stressors after infection that negatively impact profitability. The objective of this study was to evaluate differences in circulating blood cell profiles at a young age between 2 lines of Yorkshire pigs that were divergently selected for RFI as well as the heritability of these traits, to investigate effects of selection for RFI on immune system parameters, and to identify potential biomarkers for feed efficiency. Previous work has shown that the 2 lines had diverged for IGF-1 in serum in young pigs and, therefore, this stage was investigated for other potential physiological differences. Blood samples were drawn for a complete blood count (CBC) analysis from 517 gilts and barrows, ages 35 to 42 d, across the 2 lines. In general, the low-RFI line had lower numbers of specific types of white blood cells but higher hemoglobin concentration and red blood cell volume compared to the high-RFI line. No significant correlations were found between CBC traits and RFI across and within the lines (0.05 < < 0.1). Of the 15 CBC traits that were measured, 3 were highly heritable (0.56 < < 0.62), 9 were moderately heritable (0.12 < < 0.47), and 3 were lowly heritable ( < 0.12), suggesting a substantial genetic component for CBC traits and that selection for CBC traits could be effective. Our results also show that selection for RFI has significantly impacted the number of circulating blood cells. In this experiment, we studied only healthy animals that were not under known pathogen challenge; therefore, our results cannot be directly applied to a disease challenge situation. Future work will be to challenge the animals and determine the effect of challenge on CBC levels.

Background: Both genome-wide association (GWA) studies and genomic selection depend on the level of non-random association of alleles at different loci, i.e. linkage disequilibrium (LD), across the genome. Therefore, characterizing LD is of fundamental importance to implement both approaches. In this study, using a 60K single nucleotide polymorphism (SNP) panel, we estimated LD and haplotype structure in crossbred broiler chickens and their component pure lines (one male and two female lines) and calculated the consistency of LD between these populations., Results: The average level of LD (measured by r(2)) between adjacent SNPs across the chicken autosomes studied here ranged from 0.34 to 0.40 in the pure lines but was only 0.24 in the crossbred populations, with 28.4% of adjacent SNP pairs having an r(2) higher than 0.3. Compared with the pure lines, the crossbred populations consistently showed a lower level of LD, smaller haploblock sizes and lower haplotype homozygosity on macro-, intermediate and micro-chromosomes. Furthermore, correlations of LD between markers at short distances (0 to 10 kb) were high between crossbred and pure lines (0.83 to 0.94)., Conclusions: Our results suggest that using crossbred populations instead of pure lines can be advantageous for high-resolution QTL (quantitative trait loci) mapping in GWA studies and to achieve good persistence of accuracy of genomic breeding values over generations in genomic selection. These results also provide useful information for the design and implementation of GWA studies and genomic selection using crossbred populations.

The replication of porcine reproductive and respiratory syndrome virus (PRRSV) was studied in a line of pigs possessing a severe combined immunodeficiency (SCID). Real-time RT-PCR revealed a unique course of infection for the SCID group. During the course of infection, viremia was initially significantly lower than normal littermates, but by 21 days was significantly elevated. Deep sequencing of the viral structural genes at days 11 and 21 identified seven amino acid substitutions in both normal and SCID pigs. The most significant change was a W99R substitution in GP2, which was present in the inoculum at a frequency of 35%, but eventually disappeared from all pigs regardless of immune status. Therefore, amino acid substitutions that appear during acute infection are likely the result of the adaptation of the virus to replication in pigs and not immune selection., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Severe combined immunodeficiency (SCID) is the result of a set of inherited genetic defects which render components of the immune response nonfunctional. In Arabian horses, Jack Russell terriers, and mice, the disorder is a consequence of the absence of T and B lymphocytes, while natural killer (NK) cell and other leukocyte populations remain intact. Preliminary analysis of a naturally acquired form of inherited SCID in a line of pigs showed several defects in the architecture and composition of secondary lymphoid organs. In this study, a quantitative assessment of lymphocyte populations in affected and normal littermates showed depleted T or B lymphocyte populations in affected pigs; however, NK cells and neutrophils were present in numbers comparable to unaffected littermates. The results indicate that the immune defect in pigs shares the same features as other SCID-affected species., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Background: To obtain predictions that are not biased by selection, the conditional mean of the breeding values must be computed given the data that were used for selection. When single nucleotide polymorphism (SNP) effects have a normal distribution, it can be argued that single-step best linear unbiased prediction (SS-BLUP) yields a conditional mean of the breeding values. Obtaining SS-BLUP, however, requires computing the inverse of the dense matrix G of genomic relationships, which will become infeasible as the number of genotyped animals increases. Also, computing G requires the frequencies of SNP alleles in the founders, which are not available in most situations. Furthermore, SS-BLUP is expected to perform poorly relative to variable selection models such as BayesB and BayesC as marker densities increase., Methods: A strategy is presented for Bayesian regression models (SSBR) that combines all available data from genotyped and non-genotyped animals, as in SS-BLUP, but accommodates a wider class of models. Our strategy uses imputed marker covariates for animals that are not genotyped, together with an appropriate residual genetic effect to accommodate deviations between true and imputed genotypes. Under normality, one formulation of SSBR yields results identical to SS-BLUP, but does not require computing G or its inverse and provides richer inferences. At present, Bayesian regression analyses are used with a few thousand genotyped individuals. However, when SSBR is applied to all animals in a breeding program, there will be a 100 to 200-fold increase in the number of animals and an associated 100 to 200-fold increase in computing time. Parallel computing strategies can be used to reduce computing time. In one such strategy, a 58-fold speedup was achieved using 120 cores., Discussion: In SSBR and SS-BLUP, phenotype, genotype and pedigree information are combined in a single-step. Unlike SS-BLUP, SSBR is not limited to normally distributed marker effects; it can be used when marker effects have a t distribution, as in BayesA, or mixture distributions, as in BayesB or BayesC π. Furthermore, it has the advantage that matrix inversion is not required. We have investigated parallel computing to speedup SSBR analyses so they can be used for routine applications.

Porcine reproductive and respiratory syndrome (PRRS) is the most economically significant disease impacting pig production in North America, Europe, and Asia, causing reproductive losses such as increased rates of stillbirth and mummified piglets. The objective of this study was to explore the genetic basis of host response to the PRRS virus (PRRSV) in a commercial multiplier sow herd before and after a PRRS outbreak, using antibody response and reproductive traits. Reproductive data comprising number born alive (NBA), number alive at 24 h (NA24), number stillborn (NSB), number born mummified (NBM), proportion born dead (PBD), number born dead (NBD), number weaned (NW), and number of mortalities through weaning (MW) of 5,227 litters from 1,967 purebred Landrace sows were used along with a pedigree comprising 2,995 pigs. The PRRS outbreak date was estimated from rolling averages of farrowing traits and was used to split the data into a pre-PRRS phase and a PRRS phase. All 641 sows in the herd during the outbreak were blood sampled 46 d after the estimated outbreak date and were tested for anti-PRRSV IgG using ELISA (sample-to-positive [S/P] ratio). Genetic parameters of traits were estimated separately for the pre-PRRS and PRRS phase data sets. Sows were genotyped using the PorcineSNP60 BeadChip, and genome-wide association studies (GWAS) were performed using method Bayes B. Heritability estimates for reproductive traits ranged from 0.01 (NBM) to 0.12 (NSB) and from 0.01 (MW) to 0.12 (NBD) for the pre-PRRS and PRRS phases, respectively. S/P ratio had heritability (0.45) and strong genetic correlations with most traits, ranging from -0.72 (NBM) to 0.73 (NBA). In the pre-PRRS phase, regions associated with NSB and PBD explained 1.6% and 3% of the genetic variance, respectively. In the PRRS phase, regions associated with NBD, NSB, and S/P ratio explained 0.8%, 11%, and 50.6% of the genetic variance, respectively. For S/P ratio, 2 regions on SSC 7 (SSC7) separated by 100 Mb explained 40% of the genetic variation, including a region encompassing the major histocompatibility complex, which explained 25% of the genetic variance. These results indicate a significant genomic component associated with PRRSV antibody response and NSB in this data set. Also, the high heritability and genetic correlation estimates for S/P ratio during the PRRS phase suggest that S/P ratio could be used as an indicator of the impact of PRRS on reproductive traits.

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome-wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13,000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. (2012). The Bayesian whole genome prediction model--BayesB (Meuwissen et al. 2001) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non-zero effect with posterior probability > 0.9 for one or more traits., (© 2014 Blackwell Verlag GmbH.)

Background: Determining an animal's genetic merit using genomic information can improve estimated breeding value (EBV) accuracy; however, the magnitude of the accuracy improvement must be large enough to recover the costs associated with implementing genome-enabled selection. One way to reduce costs is to genotype nucleus herd selection candidates using a low-density chip and to use high-density chip genotyping for animals that are used as parents in the nucleus breeding herd. The objective of this study was to develop a tool to estimate the cost structure associated with incorporating genome-enabled selection into multi-level commercial breeding programs., Results: For the purpose of this deterministic study, it was assumed that a commercial pig is created from a terminal line sire and a dam that is a cross between two maternal lines. It was also assumed that all male and female selection candidates from the 1000 sow maternal line nucleus herds were genotyped at low density and all animals used for breeding at high density. With the assumptions used in this analysis, it was estimated that genome-enabled selection costs for a maternal line would be approximately US$0.082 per weaned pig in the commercial production system. A total of US$0.164 per weaned pig is needed to incorporate genome-enabled selection into the two maternal lines. Similarly, for a 600 sow terminal line nucleus herd and genotyping only male selection candidates with the low-density panel, the cost per weaned pig in the commercial herd was estimated to be US$0.044. This means that US$0.21 per weaned pig produced at the commercial level and sired by boars obtained from the nucleus herd breeding program needs to be added to the genetic merit value in order to break even on the additional cost required when genome-enabled selection is used in both maternal lines and the terminal line., Conclusions: By modifying the input values, such as herd size and genotyping strategy, a flexible spreadsheet tool developed from this work can be used to estimate the additional costs associated with genome-enabled selection. This tool will aid breeders in estimating the economic viability of incorporating genome-enabled selection into their specific breeding program.

Animals selected for residual feed intake (RFI) can be used as a model to elucidate molecular explanations for differences in growth efficiency. The objective of this study was to determine the extent to which the protein profile and posttranslational modifications of mitochondria from skeletal muscle and liver relate to feed efficiency gains in pigs divergently selected for RFI. Mitochondria were isolated from the longissimus dorsi (LD) muscle and the liver from pigs (n = 9 each for the high and low RFI line; BW = 95.8 kg). Mitochondria protein profile differences were determined using two-dimensional difference in gel electrophoresis. Proteins were identified using electrospray ionization mass spectrometry. In the line comparison, the β subunit of ATP synthase, heat shock protein (HSP) 60, and HSP70, were identified as being increased in mitochondria from the liver of the low RFI line (23 to 50%; P < 0.1). These differences were not observed in the other comparisons. In the LD, proteins identified as being different between RFI phenotypes included HSP70 and subunit 1 of the cytochrome bc1 complex. These data indicate that genetic selection for RFI tends to result in a consistent change in mitochondrial protein profile. In contrast, classification by phenotype demonstrates that phenotypic differences in RFI are not specifically associated with alterations of the mitochondria protein profile.

Background: Host genetics has been shown to play a role in porcine reproductive and respiratory syndrome (PRRS), which is the most economically important disease in the swine industry. A region on Sus scrofa chromosome (SSC) 4 has been previously reported to have a strong association with serum viremia and weight gain in pigs experimentally infected with the PRRS virus (PRRSV). The objective here was to identify haplotypes associated with the favorable phenotype, investigate additional genomic regions associated with host response to PRRSV, and to determine the predictive ability of genomic estimated breeding values (GEBV) based on the SSC4 region and based on the rest of the genome. Phenotypic data and 60 K SNP genotypes from eight trials of ~200 pigs from different commercial crosses were used to address these objectives., Results: Across the eight trials, heritability estimates were 0.44 and 0.29 for viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain to 42 days post infection (WG), respectively. Genomic regions associated with VL were identified on chromosomes 4, X, and 1. Genomic regions associated with WG were identified on chromosomes 4, 5, and 7. Apart from the SSC4 region, the regions associated with these two traits each explained less than 3% of the genetic variance. Due to the strong linkage disequilibrium in the SSC4 region, only 19 unique haplotypes were identified across all populations, of which four were associated with the favorable phenotype. Through cross-validation, accuracies of EBV based on the SSC4 region were high (0.55), while the rest of the genome had little predictive ability across populations (0.09)., Conclusions: Traits associated with response to PRRSV infection in growing pigs are largely controlled by genomic regions with relatively small effects, with the exception of SSC4. Accuracies of EBV based on the SSC4 region were high compared to the rest of the genome. These results show that selection for the SSC4 region could potentially reduce the effects of PRRS in growing pigs, ultimately reducing the economic impact of this disease.

Infectious diseases are costly to the swine industry; porcine reproductive and respiratory syndrome (PRRS) is the most devastating. In earlier work, a quantitative trait locus associated with resistance/susceptibility to PRRS virus was identified on Sus scrofa chromosome 4 using approximately 560 experimentally infected animals from a commercial cross. The favorable genotype was associated with decreased virus load and increased weight gain (WG). The objective here was to validate and further characterize the association of the chromosome 4 region with PRRS resistance using data from two unrelated commercial crossbred populations. The validation populations consisted of two trials each of approximately 200 pigs sourced from different breeding companies that were infected with PRRS virus and followed for 42 days post-infection. Across all five trials, heritability estimates were 0.39 and 0.34 for viral load (VL; area under the curve of log-transformed viremia from 0 to 21 days post-infection) and WG to 42 days post-infection respectively. Effect estimates of SNP WUR10000125 in the chromosome 4 region were in the same directions and of similar magnitudes in the two new trials as had been observed in the first three trials. Across all five trials, the 1-Mb region on chromosome 4 explained 15 percent of genetic variance for VL and 11 percent for WG. The effect of the favorable minor allele at SNP WUR10000125 was dominant. Ordered genotypes for SNP WUR10000125 showed that the effect was present irrespective of whether the favorable allele was paternally or maternally inherited. These results demonstrate that selection for host response to PRRS virus infection could reduce the economic impact of PRRS., (© 2013 The Authors, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics.)

Genomic selection (GS) is the use of statistical methods to estimate the genetic merit of a genotyped animal based on prediction equations derived from large ancestral populations with both phenotypes and genotypes. It has revolutionized the dairy cattle breeding industry and has been implemented with varying degrees of success in other animal breeding programs, including swine, poultry, and beef cattle. The findings of empirical field studies applying GS to the breeding sectors of these main animal protein industries are reviewed. Several translational considerations must be addressed before implementing GS in genetic improvement programs. These include determining and obtaining economically relevant phenotypes and determining the optimal size of the training population, cost-effective genotyping strategies, the practicality of field implementation, and the relative costs versus the benefits of the realized rate of genetic gain. GS may additionally change the optimal breeding scheme design, and studies that address this consideration are also reviewed briefly.

Pig on-farm behavior has important repercussions on pig welfare and performance, but generally its relationship with meat quality is not well understood. We used principal component analysis to determine the relationship between meat quality traits, feeding patterns, scale activity, and number of conflict-avoidance interactions. The first principal component indicated that gilts with greater daily feed intake stayed longer in the feeder and their meat had increased intramuscular fat (IMF), was lighter in color, and, in the second principal component, had better juiciness, tenderness, chewiness, and flavor. Meat from gilts with lower scale activity scores appeared to have more IMF but greater drip losses (DL). The third principal component suggested that dominant gilts could gain priority access to the feeder, eating more and growing fatter. In conclusion, except for the slight associations with IMF and DL, gilt scale activity and conflict-avoidance behaviors were not good indicators of final meat quality attributes., (© 2013.)

A least squares regression interval mapping model was derived to detect quantitative trait loci (QTL) with a unique mode of genomic imprinting, polar overdominance (POD), under a breed cross design model in outbred mammals. Tests to differentiate POD QTL from Mendelian, paternal or maternal expression QTL were also developed. To evaluate the power of the POD models and to determine the ability to differentiate POD from non-POD QTL, phenotypic data, marker data and a biallelic QTL were simulated on 512 F2 offspring. When tests for Mendelian versus parent-of-origin expression were performed, most POD QTL were classified as partially imprinted QTL. The application of the series of POD tests showed that more than 90% and 80% of medium and small POD QTL were declared as POD type. However, when breed-origin alleles were segregating in the grand parental breeds, the proportion of declared POD QTL decreased, which was more pronounced in a mating design with a small number of parents (F0 and F1). Non-POD QTL, i.e. with Mendelian or parent-of-origin expression (complete imprinting) inheritance, were well classified (>90%) as non-POD QTL, except for QTL with small effects and paternal or maternal expression in the design with a small number of parents, for which spurious POD QTL were declared.

Background: Shifts in body composition, such as accumulation of body fat, can be a symptom of many chronic human diseases; hence, efforts have been made to investigate the genetic mechanisms that underlie body composition. For example, a few quantitative trait loci (QTL) have been discovered using genome-wide association studies, which will eventually lead to the discovery of causal mutations that are associated with tissue traits. Although some body composition QTL have been identified in mice, limited research has been focused on the imprinting and interaction effects that are involved in these traits. Previously, we found that Myostatin genotype, reciprocal cross, and sex interacted with numerous chromosomal regions to affect growth traits., Results: Here, we report on the identification of muscle, adipose, and morphometric phenotypic QTL (pQTL), translation and transcription QTL (tQTL) and expression QTL (eQTL) by applying a QTL model with additive, dominance, imprinting, and interaction effects. Using an F2 population of 1000 mice derived from the Myostatin-null C57BL/6 and M16i mouse lines, six imprinted pQTL were discovered on chromosomes 6, 9, 10, 11, and 18. We also identified two IGF1 and two Atp2a2 eQTL, which could be important trans-regulatory elements. pQTL, tQTL and eQTL that interacted with Myostatin, reciprocal cross, and sex were detected as well. Combining with the additive and dominance effect, these variants accounted for a large amount of phenotypic variation in this study., Conclusions: Our study indicates that both imprinting and interaction effects are important components of the genetic model of body composition traits. Furthermore, the integration of eQTL and traditional QTL mapping may help to explain more phenotypic variation than either alone, thereby uncovering more molecular details of how tissue traits are regulated.

Efficiency of production is increasingly important with the current escalation of feed costs and demands to minimize the environmental footprint. The objectives of this study were 1) to estimate heritabilities for daily feed consumption and residual feed intake and their genetic correlations with production and egg-quality traits; 2) to evaluate accuracies of estimated breeding values from pedigree- and marker-based prediction models; and 3) to localize genomic regions associated with feed efficiency in a brown egg layer line. Individual feed intake data collected over 2-wk trial periods were available for approximately 6,000 birds from 8 generations. Genetic parameters were estimated with a multitrait animal model; methods BayesB and BayesCπ were used to estimate marker effects and find genomic regions associated with feed efficiency. Using pedigree information, feed efficiency was found to be moderately heritable (h(2) = 0.46 for daily feed consumption and 0.47 for residual feed intake). Hens that consumed more feed and had greater residual feed intake (lower efficiency) had a genetic tendency to lay slightly more eggs with greater yolk weights and albumen heights. Regions on chromosomes 1, 2, 4, 7, 13, and Z were found to be associated with feed intake and efficiency. The accuracy from genomic prediction was higher and more persistent (better maintained across generations) than that from pedigree-based prediction. These results indicate that genomic selection can be used to improve feed efficiency in layers.

The objective of this study was to evaluate the contribution of muscle protein turnover (synthesis and degradation) to the biological basis for genetic differences in finisher pigs selected for residual feed intake (RFI). Residual feed intake is defined as the difference between expected feed intake (based on the achieved rate of BW gain and backfat depth of individual pigs) and the observed feed intake of the individual pig. We hypothesized that protein turnover would be reduced in pigs selected for low RFI. Twelve gilts from a line selected for 7 generations for low RFI and 12 from a contemporary line selected for 2 generations for high RFI were paired by age and BW and fed a standard corn-soybean diet for 6 wk. Pigs were euthanized, muscle and liver samples were collected, and insulin signaling, protein synthesis, and protein degradation proteins were analyzed for expression and activities. Muscle from low RFI pigs tended to have less μ- and m-calpain activities (P = 0.10 and 0.09, respectively) and had significantly greater calpastatin activity and a decreased μ-calpain:calpastatin activity ratio (P < 0.05). Muscle from low RFI pigs had less 20S proteasome activity compared with their high RFI counterparts (P < 0.05). No differences in insulin signaling intermediates and translation initiation signaling proteins [mammalian target of rapamycin (mTOR) pathway] were observed (P > 0.05). Postmortem proteolysis was determined in the LM from the eighth generation of the low RFI pigs versus their high RFI counterparts (n = 9 per line). Autolysis of μ-calpain was decreased in the low RFI pigs and less troponin-T degradation product was observed at 3 d postmortem (P < 0.05), indicating slowed postmortem proteolysis during aging in the low RFI pigs. These data provide significant evidence that less protein degradation occurs in pigs selected for reduced RFI, and this may account for a significant portion of the increased efficiency observed in these animals.

One approach for cost-effective implementation of genomic selection is to genotype training individuals with a high-density (HD) panel and selection candidates with an evenly spaced, low-density (ELD) panel. The purpose of this study was to evaluate the extent to which the ELD approach reduces the accuracy of genomic estimated breeding values (GEBV) in a broiler line, in which 1,091 breeders from 3 generations were used for training and 160 progeny of the third generation for validation. All birds were genotyped with an Illumina Infinium platform HD panel that included 20,541 segregating markers. Two subsets of HD markers, with 377 (ELD-1) or 766 (ELD-2) markers, were selected as ELD panels. The ELD-1 panel was genotyped using KBiosciences KASPar SNP genotyping chemistry, whereas the ELD-2 panel was simulated by adding markers from the HD panel to the ELD-1 panel. The training data set was used for 2 traits: BW at 35 d on both sexes and hen house production (HHP) between wk 28 and 54. Methods Bayes-A, -B, -C and genomic best linear unbiased prediction were used to estimate HD-marker effects. Two scenarios were used: (1) the 160 progeny were ELD-genotyped, and (2) the 160 progeny and their dams (117 birds) were ELD-genotyped. The missing HD genotypes in ELD-genotyped birds were imputed by a Gibbs sampler, capitalizing on linkage within families. In scenario (1), the correlation of GEBV for BW (HHP) of the 160 progeny based on observed HD versus imputed genotypes was greater than 0.94 (0.98) with the ELD-1 panel and greater than 0.97 (0.99) with the ELD-2 panel. In scenario (2), the correlation of GEBV for BW (HHP) was greater than 0.92 (0.96) with the ELD-1 panel and greater than 0.95 (0.98) with the ELD-2 panel. Hence, in a pedigreed population, genomic selection can be implemented by genotyping selection candidates with about 400 ELD markers with less than 6% loss in accuracy. This leads to substantial savings in genotyping costs, with little sacrifice in accuracy.