Genome-Wide Association Study for Weight Loss at the End of Dry-Curing of Hams Produced from Purebred Heavy Pigs.

Dissecting the genetics of production traits in livestock is of outmost importance, both to understand biological mechanisms underlying those traits and to facilitate the design of selection programs incorporating that information. For the pig industry, traits related to curing are key for protected designation of origin productions. In particular, appropriate ham weight loss after dry-curing ensures high quality of the final product and avoids economic losses. In this study, we analyzed data (N = 410) of ham weight loss after approximately 20 months of dry-curing. The animals used for ham production were purebred pigs belonging to a commercial line. A genome-wide association study (GWAS) of 29,844 SNP markers revealed the polygenic nature of the trait: 221 loci explaining a small percentage of the variance (0.3-1.65%) were identified on almost all Sus scrofa chromosomes. Post-GWAS analyses revealed 32 windows located within regulatory regions and 94 windows located in intronic regions of specific genes. In total, 30 candidate genes encoding receptors and enzymes associated with ham weight loss (MTHFD1L, DUSP8), proteolysis (SPARCL1, MYH8), drip loss (TNNI2), growth (CDCA3, LSP1, CSMD1, AP2A2, TSPAN4), and fat metabolism (AGPAT4, IGF2R, PTDSS2, HRAS, TALDO1, BRSK2, TNNI2, SYT8, GTF2I, GTF2IRD1, LPCAT3, ATN1, GNB3, CMIP, SORCS2, CCSER1, SPP1) were detected.

Genetic Correlations between Boar Taint Compound Concentrations in Fat of Purebred Boars and Production and Ham Quality Traits in Crossbred Heavy Pigs.

Selecting pigs with reduced ability to accumulate boar taint (BT) compounds in their tissues is an alternative to male surgical castration. As the majority of slaughter pigs are crossbred, before selecting against BT in purebreds, it is essential to consider possible impacts on commercial traits in crossbreds. This study estimated the genetic correlations between BT compound levels measured in 1115 purebred pigs and carcass and ham quality traits collected in 26,577 crossbred Italian heavy pigs. Genetic correlations were estimated in bivariate Bayesian analyses including one BT trait and one production or ham quality trait at a time. Heritability of androstenone, skatole, and indole was 0.41, 0.49, and 0.37, respectively. A moderate negative correlation between skatole and carcass yield (-0.40), and between all BT compounds and backfat (from -0.26 to -0.55) was observed. Conversely, positive correlations (from 0.11 to 0.54) were found between skatole and ham fat thickness traits. Correlations between BT compounds and iodine number ranged from -0.07 (for androstenone) to -0.64 (for skatole), whereas those with PUFA ranged from -0.13 (for indole) to -0.33 (for skatole). Hence, reducing BT could decrease ham fat thickness and increase unsaturated fatty acids, with potential negative impacts on product quality.

Genomic Prediction and Genome-Wide Association Study for Boar Taint Compounds.

With a perspective future ban on surgical castration in Europe, selecting pigs with reduced ability to accumulate boar taint (BT) compounds (androstenone, indole, skatole) in their tissues seems a promising strategy. BT compound concentrations were quantified in the adipose tissue of 1075 boars genotyped at 29,844 SNPs. Traditional and SNP-based breeding values were estimated using pedigree-based BLUP (PBLUP) and genomic BLUP (GBLUP), respectively. Heritabilities for BT compounds were moderate (0.30-0.52). The accuracies of GBLUP and PBLUP were significantly different for androstenone (0.58 and 0.36, respectively), but comparable for indole and skatole (~0.43 and ~0.47, respectively). Several SNP windows, each explaining a small percentage of the variance of BT compound concentrations, were identified in a genome-wide association study (GWAS). A total of 18 candidate genes previously associated with BT (MX1), reproduction traits (TCF21, NME5, PTGFR, KCNQ1, UMODL1), and fat metabolism (CTSD, SYT8, TNNI2, CD81, EGR1, GIPC2, MIGA1, NEGR1, CCSER1, MTMR2, LPL, ERFE) were identified in the post-GWAS analysis. The large number of genes related to fat metabolism might be explained by the relationship between sexual steroid levels and fat deposition and be partially ascribed to the pig line investigated, which is selected for ham quality and not for lean growth.

Concentrations of Boar Taint Compounds Are Weakly Associated with Sexual Behavior of Young Boars.

Strategies to control boar taint (BT) in meat relies on the reduction of skatole, indole, and androstenone concentration. This might have unfavorable effects on the libido of breeding boars. The association between BT compound concentration in backfat and libido was investigated in 391 commercial breeding boars. Six sexual behavior traits (SBT; sexual arousal, salivation, mounting performance, interest in the dummy sow, penis unsheathing, and overall libido score) were scored during the training of the boars with the dummy sow. Variation in SBT was analyzed by proportional-odds cumulative logistic models. Overall, indole, skatole, and androstenone concentrations were weakly associated with libido. Farm of origin, age at training or body weight, and BT compound levels were poor predictors of boar performance (the area under the ROC curve ranged from 0.60 to 0.69). This indicates that BT compound concentrations were weakly associated with libido, even though the probability of observing good SBT scores increased with high levels of androstenone, intermediate or low levels of skatole, and intermediate to high levels of indole. Hence, practices aiming at reducing androstenone, and controlling the concentrations of skatole and indole to intermediate levels are not expected to impair the libido of young boars.

Infrared Predictions Are a Valuable Alternative to Actual Measures of Dry-Cured Ham Weight Loss in the Training of Genome-Enabled Prediction Models.

Selection to reduce ham weight losses during dry-curing (WL) requires individual traceability of hams throughout dry-curing, with high phenotyping costs and long generation intervals. Infrared spectroscopy enables cost-effective, high-throughput phenotyping for WL 24 h after slaughter. Direct genomic values (DGV) of crossbred pigs and their purebred sires were estimated, for observed (OB) and infrared-predicted WL (IR), through models developed from 640 and 956 crossbred pigs, respectively. Five Bayesian models and two pseudo-phenotypes (estimated breeding value, EBV, and adjusted phenotype) were tested in random cross-validation and leave-one-family-out validation. The use of EBV as pseudo-phenotypes resulted in the highest accuracies. Accuracies in leave-one-family-out validation were much lower than those obtained in random cross-validation but still satisfactory and very similar for both traits. For sires in the leave-one-family-out validation scenario, the correlation between the DGV for IR and EBV for OB was slightly lower (0.32) than the correlation between the DGV for OB and EBV for OB (0.38). While genomic prediction of OB and IR can be equally suggested to be incorporated in future selection programs aiming at reducing WL, the use of IR enables an early, cost-effective phenotyping, favoring the construction of larger reference populations, with accuracies comparable to those achievable using OB phenotype.

Genomic Predictions of Phenotypes and Pseudo-Phenotypes for Viral Nervous Necrosis Resistance, Cortisol Concentration, Antibody Titer and Body Weight in European Sea Bass.

In European sea bass (Dicentrarchus labrax L.), the viral nervous necrosis mortality (MORT), post-stress cortisol concentration (HC), antibody titer (AT) against nervous necrosis virus and body weight (BW) show significant heritability, which makes selective breeding a possible option for their improvement. An experimental population (N = 650) generated by a commercial broodstock was phenotyped for the aforementioned traits and genotyped with a genome-wide SNP panel (16,075 markers). We compared the predictive accuracies of three Bayesian models (Bayes B, Bayes C and Bayesian Ridge Regression) and a machine-learning method (Random Forest). The prediction accuracy of the EBV for MORT was approximately 0.90, whereas the prediction accuracies of the EBV and the phenotype were 0.86 and 0.21 for HC, 0.79 and 0.26 for AT and 0.71 and 0.38 for BW. The genomic prediction of the EBV for MORT used to classify the phenotype for the same trait showed moderate classification performance. Genome-wide association studies confirmed the polygenic nature of MORT and demonstrated a complex genetic structure for HC and AT. Genomic predictions of the EBV for MORT could potentially be used to classify the phenotype of the same trait, though further investigations on a larger experimental population are needed.

The Implications of Changing Age and Weight at Slaughter of Heavy Pigs on Carcass and Green Ham Quality Traits.

Italian dry-cured ham production requires pigs to be slaughtered at 160 ± 16 kg at 9 months of age (control, C). The study explored three alternatives, based on different feeding conditions: (1) allowing pigs to express their growth potential by letting them reach 160 ± 16 kg slaughter weight (SW) at younger slaughter age (SA) (younger Age, YA); (2) allowing pigs to express their growth potential by maximizing their SW at 9 months SA (greater weight, GW); (3) increasing the SA required to reach 160 ± 16 kg SW (older age, OA). Pigs (336 C21 Goland, 95 kg initial body weight) were slaughtered on average at 257, 230, 257, and 273 d SA and 172.7, 172.3, 192.9, and 169.3 SW kg for the four treatments, respectively. C pigs had an average daily gain (ADG) of 715 g/d and feed efficiency (FE) of 0.265 (gain to feed). Compared to C, YA pigs had higher ADG (+32%), FE (+7.5%), and better ham adiposity; GW pigs had higher carcass weight (+12%), ADG (+25%), trimmed ham weight (+10.9%), and better ham adiposity. OA treatment affected ADG (-16.4%), FE (-16.6%), and trimmed ham weight (-3.6%). YA and GW could be promising alternatives to C as they improved FE and ham quality traits.

Estimation of Additive and Dominance Genetic Effects on Body Weight, Carcass and Ham Quality Traits in Heavy Pigs.

Neglecting dominance effects in genetic evaluations may overestimate the predicted genetic response achievable by a breeding program. Additive and dominance genetic effects were estimated by pedigree-based models for growth, carcass, fresh ham and dry-cured ham seasoning traits in 13,295 crossbred heavy pigs. Variance components estimated by models including litter effects, dominance effects, or both, were compared. Across traits, dominance variance contributed up to 26% of the phenotypic variance and was, on average, 22% of the additive genetic variance. The inclusion of litter, dominance, or both these effects in models reduced the estimated heritability by 9% on average. Confounding was observed among litter, additive genetic and dominance effects. Model fitting improved for models including either the litter or dominance effects, but it did not benefit from the inclusion of both. For 15 traits, model fitting slightly improved when dominance effects were included in place of litter effects, but no effects on animal ranking and accuracy of breeding values were detected. Accounting for litter effects in the models for genetic evaluations would be sufficient to prevent the overestimation of the genetic variance while ensuring computational efficiency.

Association of polymorphisms in calpain 1, (mu/I) large subunit, calpastatin, and cathepsin D genes with meat quality traits in double-muscled Piemontese cattle.

Five single-nucleotide polymorphisms (SNPs) located in the calpain 1, (mu/I) large subunit (CAPN1), calpastatin (CAST), and cathepsin D (CTSD) genes were analyzed in a large sample of Piemontese cattle. The aim of this study was to evaluate allele and genotype frequencies of these SNPs and to investigate associations of CAPN1, CAST, and CTSD gene variants with meat quality traits. Minor allele frequencies ranged from 30 to 48%. The presence of the A allele at CAPN530 increased yellowness and drip loss. The CAST282 G allele was associated with an increased drip loss compared to the C allele, and the CAST2959 A allele decreased redness compared to the G allele.

Separation and quantification of water buffalo milk protein fractions and genetic variants by RP-HPLC.

A RP-HPLC method, developed for the separation and quantification of the most common genetic variants of bovine milk proteins, was successfully applied to the analysis of water buffalo milk. All the most common buffalo casein and whey proteins fractions, as well as their genetic variants, were detected and separated simultaneously in 40 min. Purified buffalo proteins were used as calibration standards and a total of 536 individual milk samples were analysed for protein composition. α(S1)-, α(S2)-, ßγ-, and κ-casein were 32.2%, 15.8%, 36.5%, and 15.5%, respectively, of total casein content, whereas content of ß-Lactoglobulin was approximately 1.3 times as high as that of α-Lactalbumin. The existence of a polymorphism of κ-casein was demonstrated in Mediterranean water buffalo and α(S1)- and κ-casein genetic variants were successfully detected by RP-HPLC.

Validation of a new reversed-phase high-performance liquid chromatography method for separation and quantification of bovine milk protein genetic variants.

A new RP-HPLC method for the separation and quantification of the most common genetic variants of bovine milk proteins is described. A reversed-phase analytical column C8 (Zorbax 300SB-C8 RP, 3.5 microm, 300A, 150 x 4.6 I.D.) was used. All the most common casein (CN) and whey protein genetic variants, including beta-CN(I) were detected and separated simultaneously in less then 40 min, with the exception of alpha(S1)-CN(B) and CN(C) variants. Purified protein genetic variants were employed in calibration and showed different absorbances at 214 nm. The procedure was developed using 40 raw individual milk samples of cows belonging to four different breeds and certified skim milk powder BCR-063R. Method validation consisted in testing linearity, repeatability, reproducibility and accuracy. A linear relationship (R(2)>0.99) between the concentrations of proteins and peak areas was observed over the concentration range, with low detection limits. Repeatability and reproducibility were satisfactory for both retention times and peak areas. The RSD of peak areas ranged from 0.92 to 4.32% within analytical day and from 0.85 to 9.52% across analytical days. The recoveries, calculated using mixtures of samples previously quantified, ranged from 98.1 to 103.7%.