Renata Veroneze

Candidate gene expression and intramuscular fat content in pigs

Seventy-two pigs of three genetic groups (Brazilian indigenous breed Piau, Commercial line and Crossbred) of both sexes were slaughtered at four live weights (30, 60, 90 and 120 kg). Intramuscular fat (IMF) content in Longissimus dorsi muscle of each animal was extracted and correlated with candidate gene mRNA expression (ATN1, EEF1A2, FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1). Within slaughter weight of 120 kg, Piau and Crossbred pigs showed higher IMF content (p < 0.05) than commercial animals, with 2.48, 2.08 and 1.00% respectively. Barrows presented higher values of IMF (p < 0.05) than gilts (1.54 and 1.30% respectively). Gene expression of EEF1A2, FABP3, LDLR, OBSCN, PDHB, TRDN and RYR1 were correlated with IMF (p < 0.05) using the whole dataset. For Piau data only, expression of FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1 showed correlation with IMF (p < 0.05). Genes that have important roles in lipid transportation inside the cell (FABP3) and tissues (LDLR) showed correlation with IMF of, respectively, 0.68 and 0.63 using the whole data set, and 0.90 and 0.91 using data from Piau animals. The highly positive correlation of the LDLR and FAPB3 expression with IMF content may confirm that these genes are important for fat deposition in the porcine L. dorsi muscle.

Linkage disequilibrium and haplotype block structure in six commercial pig lines

Linkage disequilibrium (LD) across the genome is critical information for association studies and genomic selection because it determines the number of SNP that should be used for a successful association analysis and genomic selection. Linkage disequilibrium also influences the accuracy of genomic breeding values. Some studies have demonstrated that SNP in strong LD are organized into discrete blocks of haplotypes, which are separated by possibly hot spots of recombination. To reduce the number of markers needed to be genotyped for association mapping, a set of SNP can be selected that labels all haplotype blocks. We estimated the LD, calculated the average haplotype block size for 6 pig lines, and compared the block size between lines. Six commercial pig lines were genotyped using the Illumina PorcineSNP60 (number of markers M = 62,163) Genotyping BeadChip (Illumina Inc.); on average, a panel of 37,623 SNP with an average minor allelic frequency (MAF) of 0.283 was included in the analysis. The LD declined as a function of distance. All pig lines had an average r(2) above 0.3 for markers 100 to 150 apart. The estimated average block size was 394.885 kb, and blocks between 100 and 400 kb were most prominent (49.96%) in all lines. These results showed that the extent of LD in pigs is much larger than in the cattle population, in accordance with the genetic map length of pigs, which is much shorter than cattle. The evaluated lines have 2,640 to 3,037 blocks, covering 45% of the pig genome, on average. Differences in haplotype block size between lines were observed for some chromosomes (i.e., SSC 3, 5, 7, 13, 14, and 18), which provide a direction for future studies of haplotype block conservation or divergence across lines.

Toll-Like Receptor 6 differential expression in two pig genetic groups vaccinated against Mycoplasma hyopneumoniae

BackgroundMycoplasma hyopneumoniae is the etiologic agent of enzootic pneumonia, which causes important economic losses to swine industry. The Toll-like receptors (TLRs) are pattern-recognition receptors which detect microbial presence and initiate the innate as well as the adaptative immune defense. Toll-like receptor 6 is a type I transmembrane protein that recognizes bacterial components. The aim of this study was to compare mRNA expression pattern of TLR6 gene in two genetically distinct groups of pigs vaccinated against Mycoplasma hyopneumoniae.MethodsFor each genetic group, peripheral blood was collected just before and 10 days after vaccination from 10 Naturalized Brazilian Piau breed and 10 Commercial White Line serum-negative female piglets. RNA was extracted from peripheral blood mononuclear cells (PBMCs), reverse transcripted and the qRT-PCR performed using SYBR green fluorescence system, using GAPDH gene as endogenous control. Analyses were performed by UNIVARIATE (Shapiro-Wilk test) and MIXED procedures of SAS software (version 9.0).ResultsIt was observed significant interaction between breed and vaccination, being the TLR6 mRNA expression higher in the Commercial White line than in the Piau breed after vaccination. Furthermore, there was differential expression before and after vaccination in the Commercial White line.ConclusionsAnalysis of in TLR6 gene expression showed difference between the two distinct genetic groups, however, other TLRs gene expression must be evaluated for a better understanding of innate resistance in the pig concerning Mycoplasma hyopneumoniae infection.

Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs

Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.

Estimação de parâmetros genéticos em tamanho de leitegada de suínos utilizando análises de características múltiplas

Data from the first four parities of Large White pigs were used to estimate (co)variance components and genetic parameters for litter size (LS) in single trait and multi-trait analyses. The (co)variance components and genetic parameters were estimated by restricted maximum likelihood using the MTDFREML program. LS in each parity was considered a different trait and the models included contemporary group as fixed effect and additive direct genetic and residual as random effects. Heritability estimates of LS in different parities in single trait analyses ranged from 0.14 to 0.20. Estimates of heritability in multi-trait analyses were similar to those obtained in single trait analyses. Phenotypic correlation estimates were lower than the genetic ones. Genetic correlations between parities were lower than 0.75, except for the estimate between the third and fourth parities, which was the highest one (0.91). The smallest genetic correlation (0.60) was observed between the first and second parities.

Accuracy of genome-enabled prediction exploring purebred and crossbred pig populations

Pig breeding companies keep relatively small populations of pure sire and dam lines that are selected to improve the performance of crossbred animals. This design of the pig breeding industry presents challenges to the implementation of genomic selection, which requires large data sets to obtain highly accurate genomic breeding values. The objective of this study was to evaluate the impact of different reference sets (across population and multipopulation) on the accuracy of genomic breeding values in 3 purebred pig populations and to assess the potential of using crossbreed performance in genomic prediction. Data consisted of phenotypes and genotypes on animals from 3 purebred populations (sire line [SL] 1, = 1,146; SL2, = 682; and SL3, = 1,264) and 3 crossbred pig populations (Terminal cross [TER] 1, = 183; TER2, = 106; and TER3, = 177). Animals were genotyped using the Illumina Porcine SNP60 Beadchip. For each purebred population, within-, across-, and multipopulation predictions were considered. In addition, data from the paternal purebred populations were used as a reference set to predict the performance of crossbred animals. Backfat thickness phenotypes were precorrected for fixed effects and subsequently included in the genomic BLUP model. A genomic relationship matrix that accounted for the differences in allele frequencies between lines was implemented. Accuracies of genomic EBV obtained within the 3 different sire lines varied considerably. For within-population prediction, SL1 showed higher values (0.80) than SL2 (0.61) and SL3 (0.67). Multipopulation predictions had accuracies similar to within-population accuracies for the validation in SL1. For SL2 and SL3, the accuracies of multipopulation prediction were similar to the within-population prediction when the reference set was composed by 900 animals (600 of the target line plus 300 of another line). For across-population predictions, the accuracy was mostly close to zero. The accuracies of predicting crossbreed performance were similar for the 3 different crossbred populations (ranging from 0.25 to 0.29). In summary, the differences in accuracy of the within-population scenarios may be due to line divergences in heritability and genetic architecture of the trait. Within- and multipopulation predictions yield similar accuracies. Across-population prediction accuracy was negligible. The moderate accuracy of prediction of crossbreed performance appears to be a result of the relationship between the crossbreed and its parental lines.

Estimation of variance components, genetic parameters and genetic trends for litter size of swines

Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).

Estimação de parâmetros genéticos em suínos usando Amostrador de Gibbs

Data consisting of 38,865 records of Large White pigs were used to estimate genetic parameters for days to 100 kg (DAYS) and backfat thickness adjusted to 100 kg (BF). Covariance components were estimated by a bivariate mixed model including the fixed effect of contemporary group and the direct and maternal additive genetic, common litter and residual random effects using the Gibbs Sampling algorithm of the MTGSAM program. Estimates of direct and common litter effects for DAYS and BF were 0.33 and 0.44 and 0.09 and 0.02, respectively. Additive genetic correlation between DAYS and BF was close to zero (-0.015). The heritability estimates indicate that genetic gains may be obtained by selection and that both traits should be considered in a breeding program for the Large White breed.

Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information.

Knowledge of dominance effects should improve ge-netic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of het-erosis in crossbreeds. In this study, we combined genomic and pedi-gree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respec-tively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age.

Estimação de parâmetros genéticos de uma população F2 de suínos

The aim of this work was to estimate genetic parameters for carcass, carcass cuts, meat quality and performance traits in an F2 swine population (Piau x commercial strain) in order to understand the inheritance of the traits and the association among them. Heritability estimates and genetic correlations were obtained using univariate and bivariate animal models, respectively, and (co)covariance components were obtained by means of restricted maximum likelihood analyses using the software MTDFREML. The heritability estimates using single trait model ranged from 0.10 to 0.43 for carcass, 0.07 to 0.47 for carcass cuts, 0.14 to 0.40 for meat quality and 0.18 to 0.86 for performance traits. The genetic correlation estimates using bi-trait model were high for several traits, showing that they are controlled by the same genes or linked genes. These results suggest that a better understanding of the genetic correlation among the traits, as well as, the quantitative trait loci position can be obtained by mapping studies in this population.