GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response.

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits. Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs. Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p < 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p < 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; -0.92 ± 0.74; p < 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits. Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge.

Metabolites in plasma of healthy nursery pigs were quantified using nuclear magnetic resonance. Heritabilities of metabolite concentration were estimated along with their phenotypic and genetic correlations with performance, resilience, and carcass traits in growing pigs exposed to a natural polymicrobial disease challenge. Variance components were estimated by GBLUP. Heritability estimates were low to moderate (0.11 ± 0.08 to 0.19 ± 0.08) for 14 metabolites, moderate to high (0.22 ± 0.09 to 0.39 ± 0.08) for 17 metabolites, and highest for L-glutamic acid (0.41 ± 0.09) and hypoxanthine (0.42 ± 0.08). Phenotypic correlation estimates of plasma metabolites with performance and carcass traits were generally very low. Significant genetic correlation estimates with performance and carcass traits were found for several measures of growth and feed intake. Interestingly the plasma concentration of oxoglutarate was genetically negatively correlated with treatments received across the challenge nursery and finisher (- 0.49 ± 0.28; P < 0.05) and creatinine was positively correlated with mortality in the challenge nursery (0.85 ± 0.76; P < 0.05). These results suggest that some plasma metabolite phenotypes collected from healthy nursery pigs are moderately heritable and genetic correlations with measures of performance and resilience after disease challenge suggest they may be potential genetic indicators of disease resilience.

Accuracy of genomic prediction of shell quality in a White Leghorn line.

Several genomic methods were applied for predicting shell quality traits recorded at 4 different hen ages in a White Leghorn line. The accuracies of genomic prediction of single-step GBLUP and single-trait Bayes B were compared with predictions of breeding values based on pedigree-BLUP under single-trait or multitrait models. Breaking strength (BS) and dynamic stiffness (Kdyn) measurements were collected on 18,524 birds from 3 consecutive generations, of which 4,164 animals also had genotypes from an Affymetrix 50K panel containing 49,591 SNPs after quality control edits. All traits had low to moderate heritability, ranging from 0.17 for BS to 0.34 for Kdyn. The highest accuracies of prediction were obtained for the multitrait single-step model. The use of marker information resulted in higher prediction accuracies than pedigree-based models for almost all traits. A genome-wide association study based on a Bayes B model was conducted to detect regions explaining the largest proportion of genetic variance. Across all 8 shell quality traits analyzed, 7 regions each explaining over 2% of genetic variance and 54 regions each explaining over 1% of genetic variance were identified. The windows explaining a large proportion of genetic variance overlapped with several potential candidate genes with biological functions linked to shell formation. A multitrait repeatability model using a single-step method is recommended for genomic evaluation of shell quality in layer chickens.

Vaginal microbiota diverges in sows with low and high reproductive performance after porcine reproductive and respiratory syndrome vaccination.

Previous studies have demonstrated evidence for a relationship between the vaginal microbiome and reproductive performance, suggesting the vaginal microbiota may serve as a tool to predict farrowing outcomes in commercial pigs. In this study, we compared the vaginal microbiome in sows with low and high farrowing performance and used it to classify animals with contrasting reproductive outcomes in commercial sows following immune challenge with porcine respiratory and reproductive syndrome (PRRS) vaccination. Eighteen microbes were differentially abundant (q-value < 0.05) between the Low and High farrowing performance groups. Among them, Campylobacter, Bacteroides, Porphyromonas, Lachnospiraceae unclassified, Prevotella, and Phascolarctobacterium were also selected in the discriminant and linear regression analyses, and could be used as potential biomarkers for reproductive outcomes. The correct classification rate in the two groups was 100%. In conclusion, this study demonstrates that vaginal microbiota collected after PRRS vaccination could be potentially used to classify sows into having low or high farrowing performance in commercial herds.

Investigating the genetic determination of clutch traits in laying hens.

Clutch traits were proposed as a more detailed description of egg-laying patterns than simple total egg production. In this study, egg production of 23,809 Rhode Island Red (RIR) and 22,210 White Leghorn (WL) hens was described in terms of number of clutches, average and maximum clutch size, age at first egg, total saleable egg production, and percentage of egg defects. Genetic parameters were estimated using a six-trait animal model. Of the phenotyped birds, 1433 RIR hens and 1515 WL hens were genotyped with line specific 50K Affymetrix Axiom single nucleotide polymorphism chips to perform genome-wide association analyses. Moderate heritabilities were estimated for clutch traits of 0.20 to 0.42 in the RIR line and 0.29 to 0.41 in the WL line. Average and maximum clutch size was positively genetically correlated with total saleable egg number in both lines. Genome-wide association analysis identified seven regions that were associated with egg production in the RIR line and 12 regions in the WL line. The regions identified were line and trait specific, except for one region on chromosome 6 from 28 to 29 Mb that influenced number of clutches and maximum and average clutch size in WL hens. Regions associated with egg production identified here overlapped with 260 genes, with some strong positional candidates based on gene ontology including WASH1, which is involved in oocyte maturation, NPVF, involved in regulation of follicle-stimulating hormone secretion, and FOXO3, involved in oocyte maturation and ovulation from the ovarian follicle. Confirmation of the role of these genes in regulation of egg production pattern will require further studies.

Using quantile regression methodology to evaluate changes in the shape of growth curves in pigs selected for increased feed efficiency based on residual feed intake.

Growth rate is a major component of feed efficiency when estimating residual feed intake (RFI). Quantile regression (QR) methodology can be used to identify animals with different growth trajectories. The objective of this study was to evaluate the use of QR to identify phenotypic and genetic differences in pigs selected for low RFI. Using performance data on 750 Yorkshire pigs selected for low RFI, individual average daily gain (ADG), average daily feed intake (ADFI), RFI and Gompertz growth curve parameters (asymptotic weight (a), inflection point (b) and decay parameter (c)) were estimated for each pig. Using QR methodology, three Gompertz growth curves were estimated for the whole population for three quantiles (0.1, 0.5 and 0.9) of the BW data. Each animal was classified into one of the quantile regression groups (QRG) based on their overall Euclidian distance between each observed and estimated BW from the quantile growth curves. These three curves were also estimated using only part of the data (generations -1 to 3, and -1 to 4) in order to evaluate the agreement classification rate of animals from later generations into QRGs. We evaluated the effect of QRG on growth parameters and performance traits. Genetic parameters were estimated for these traits, as well as for QRG. In addition, genetic trends for each QRG were estimated. Three distinct growth curves were observed for animals classified into either quantiles 0.1 (QRG0.1), 0.5 (QRG0.5) or 0.9 (QRG0.9). When only part of the data was used to estimate quantile growth curves, all animals from QRG0.1 were correctly classified in their group. Animals in QRG0.1 had significantly lower ADFI, ADG and RFI, and greater a, b and c than animals in the other groups. Quantile regression groups analysed as a trait was highly heritable (0.41) and had high (0.8) and moderate (0.46) genetic correlations with ADG and RFI, respectively. Selection for reduced RFI increased the number of animals classified as QRG0.1 in the population. Overall, downward genetic trends were observed for all traits as a function of selection for reduced RFI. However, QRG0.1 was the only group that had a positive genetic trend for ADG. Altogether, these results indicate that selection for reduced RFI changes the shape of growth curves in Yorkshire in pigs, and that QR methodology was able to identify animals having different genetic potential for feed efficiency, bringing a new opportunity to improve selection for reduced RFI.

Genome wide association study for heat stress induced mortality in a white egg layer line.

High environmental temperature is a serious stress affecting economic and biological efficiency of poultry production in tropical and subtropical countries that is expected to become more prominent with global climate change. Iowa experienced 3 acute heat waves of 11, 3, and 4 d of heat index above 38°C in the summer of 2012, which led to production losses and increased bird mortality. For the current study, the proportion of daughters that died from heat stress during this period was calculated for 118 sire families of an elite White Leghorn layer line. The number of daughters per sire ranged from 25 to 111 and averaged 68. Average mortality due to heat stress was 8.2%, ranging from 0 to 24.6%. All sires were genotyped using a 600 K Affymetrix chip. After stringent quality filtering (clustering quality, parentage, missing genotypes, MAF) 113,344 SNPs were retained for the analysis. Method BayesB with π equal to 0.999, for the number of markers fitted not to exceed the number of observations, was applied. Markers explained 8% of the phenotypic variance. One 1-Mb window on chromosome 5 explained 1.2% of genetic variance. When the number of daughters was fitted as a weight in the analysis, the proportion of variance explained by markers dropped to 1%, but 9 1-Mb windows explained more than 1% of genetic variance on chromosomes 1, 3, 5 (the same top window as in the unweighted analysis), 9, 17, and 18. Although the support of the genomic regions associated with heat stress resistance identified in this study was not very strong, they overlapped with previously reported quantitative trait loci regions for immune response and physiological traits in chickens and contained genes that have been associated with response to heat stress in other studies. Further research is needed to validate the results.

Effect of lower-energy, higher-fiber diets on pigs divergently selected for residual feed intake when fed higher-energy, lower-fiber diets.

Residual feed intake (RFI) is the difference between observed and predicted feed intake of an animal, based on growth and maintenance requirements. In Yorkshire pigs, divergent selection for increased (Low RFI) and decreased (High RFI) RFI was carried out over 10 generations (G) while feeding a corn- and soybean-meal-based, higher-energy, lower-fiber (HELF) diet. In G8 to G10, representing 4 replicates, barrows and gilts (n = 649) of the RFI lines were fed the HELF diet and a diet incorporating coproducts that were lower in energy and higher in dietary fiber (LEHF). The diets differed in ME, 3.32 vs. 2.87 Mcal/kg, and in neutral detergent fiber (NDF), 9.4% vs. 25.9%, respectively. The impact of the LEHF diet on 1) performance and growth, 2) diet digestibility, 3) genetic parameter estimates, and 4) responses to selection for RFI, when fed the HELF, was assessed. In general, the LEHF diet reduced the performance of both lines. When fed the HELF diet, the Low RFI pigs had lower (P < 0.05) ADFI (-12%), energy intake (-12%), ADG (-6%), and backfat depth (-12%); similar (P > 0.05) loin muscle area (LMA; +5%); and greater (P < 0.05) feed efficiency (i.e., 8% higher G:F and 7% lower RFI) than the High RFI line. These patterns of line differences were still present under the LEHF diet but differences for ADFI (-11%), energy intake (-10%), G:F (+2%), and RFI (-6%) were reduced compared to the HELF diet. Apparent total tract digestibility (ATTD) of the HELF and LEHF diets was assessed using 116 barrows and gilts from G8. When fed the HELF diet, ATTD of DM, GE, N, and NDF were similar between lines (P ≥ 0.27), but when fed the LEHF diet, the Low RFI pigs had greater digestibility (7%, 7%, 10%, and 32%) than the High RFI line (P ≤ 0.04). To measure responses to selection for RFI and estimate genetic parameters, data from all 10 generations were used (HELF; n = 2,310; LEHF, n = 317). Heritability estimates of performance traits ranged from 0.19 to 0.63, and genetic correlations of traits between diets were high and positive, ranging from 0.87 (RFI) to 0.99 (LMA). By G10, RFI in the Low RFI line was 3.86 and 1.50 genetic SD lower than in the High RFI line when fed the HELF and LEHF diets, respectively. Taken together, the results of this study demonstrate that responses to selection for RFI when fed a HELF diet are not fully realized when pigs are fed an extremely LEHF diet. Thus, feeding diets that differ from those used for selection may not maximize genetic potential for feed efficiency.

Identifying the genetic basis for resistance to avian influenza in commercial egg layer chickens.

Two highly pathogenic avian influenza (HPAI) outbreaks have affected commercial egg production flocks in the American continent in recent years; a H7N3 outbreak in Mexico in 2012 that caused 70% to 85% mortality and a H5N2 outbreak in the United States in 2015 with over 99% mortality. Blood samples were obtained from survivors of each outbreak and from age and genetics matched non-affected controls. A total of 485 individuals (survivors and controls) were genotyped with a 600 k single nucleotide polymorphism (SNP) array to detect genomic regions that influenced the outcome of highly pathogenic influenza infection in the two outbreaks. A total of 420458 high quality, segregating SNPs were identified across all samples. Genetic differences between survivors and controls were analyzed using a logistic model, mixed models and a Bayesian variable selection approach. Several genomic regions potentially associated with resistance to HPAI were identified, after performing multidimensional scaling and adjustment for multiple testing. Analysis conducted within each outbreak identified different genomic regions for resistance to the two virus strains. The strongest signals for the Iowa H5N2 survivor samples were detected on chromosomes 1, 7, 9 and 15. Positional candidate genes were mainly coding for plasma membrane proteins with receptor activity and were also involved in immune response. Three regions with the strongest signal for the Mexico H7N3 samples were located on chromosomes 1 and 5. Neuronal cell surface, signal transduction and immune response proteins coding genes were located in the close proximity of these regions.

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows.

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain ß-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.

A major gene for host response to porcine reproductive and respiratory syndrome is not unfavorably associated with overall performance under nonchallenging conditions in commercial pig lines.

A QTL for host response to porcine reproductive and respiratory syndrome (PRRS) was identified in a previous study. The SNP WUR10000125 (WUR) is used as a tag SNP for this QTL. The favorable (B) allele at this SNP is in low frequency in commercial populations, possibly because this allele is unfavorably associated with an important trait under nonchallenging conditions and, therefore, may have been selected against. Therefore, objectives of this study were to estimate the effect of WUR on traits under selection in commercial lines under nonchallenging conditions and to estimate the effect of WUR genotype of parents on performance of crossbred progeny in a commercial-like environment. Data were collected on 4 purebred lines: a Landrace dam line (D1), a Large White dam line (D2), a synthetic sire line (S1), and a Pietrain sire line (S2). Traits analyzed included total number born, number stillborn, farrowing survival, lactation survival, litter mortality, daily feed intake (DFI), backfat, average test daily gain (TGR), average lifetime daily gain (LGR), and Topigs Norsvin selection index (TSI) value, indicative of overall economic value. Deregressed EBV were calculated for each trait (except TSI) and analyzed within line. In the S1 line, AB and BB pigs had significantly lower TGR ( = 0.002) and LGR ( = 0.001) than AA pigs but also lower DFI ( = 0.004). Conversely, AB and BB pigs had significantly higher DFI ( < 0.001) and AB pigs had significantly higher TGR ( = 0.03) than AA pigs in the S2 line. The effect of WUR on TSI was not significant for any line ( ≥ 0.15). Analyses of phenotypic records collected on crossbred progeny of S1 sires and D1 × D2 F females showed no significant effect of parent WUR genotype on DFI, backfat, TGR, or LGR ( ≥ 0.07). In conclusion, the effect of WUR was nonsignificant for most traits but the magnitude and direction of the effect differed by trait and by line. The favorable allele for host response to PRRS was associated with greater DFI and a tendency for greater TGR in the S2 line, but the opposite direction of effect was detected for the S1 line. Regardless of the effect on individual traits, no significant effect of WUR on TSI was detected for any line. Therefore, selecting for the B allele is expected to result in progeny with increased resistance to PRRS without compromising overall economic value under normal, nonchallenging conditions.

Effect of a major quantitative trait locus for porcine reproductive and respiratory syndrome (PRRS) resistance on response to coinfection with PRRS virus and porcine circovirus type 2b (PCV2b) in commercial pigs, with or without prior vaccination for PRRS.

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.

Genomewide association of piglet responses to infection with one of two porcine reproductive and respiratory syndrome virus isolates.

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.

Repeatability vs. multiple-trait models to evaluate shell dynamic stiffness for layer chickens.

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.

Effect of selection for residual feed intake during the grow/finish phase of production on sow reproductive performance and lactation efficiency.

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.

Estimation of genetic parameters for traits associated with reproduction, lactation, and efficiency in sows.

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.

Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers.

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.

Genomewide association analysis of sow lactation performance traits in lines of Yorkshire pigs divergently selected for residual feed intake during grow-finish phase.

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 potential serum biomarkers to predict feed efficiency in young pigs.

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.

Composition and quality characteristics of carcasses from pigs divergently selected for residual feed intake on high- or low-energy diets.

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.