Five genomic regions have a major impact on fat composition in Iberian pigs

The adipogenic nature of the Iberian pig defines many quality attributes of its fresh meat and dry-cured products. The distinct varieties of Iberian pig exhibit great variability in the genetic parameters for fat deposition and composition in muscle. The aim of this work is to identify common and distinct genomic regions related to fatty acid composition in Retinto, Torbiscal, and Entrepelado Iberian varieties and their reciprocal crosses through a diallelic experiment. In this study, we performed GWAS using a high density SNP array on 382 pigs with the multimarker regression Bayes B method implemented in GenSel. A number of genomic regions showed strong associations with the percentage of saturated and unsaturated fatty acid in intramuscular fat. In particular, five regions with Bayes Factor >100 (SSC2 and SSC7) or >50 (SSC2 and SSC12) explained an important fraction of the genetic variance for miristic, palmitoleic, monounsaturated (>14%), oleic (>10%) and polyunsaturated (>5%) fatty acids. Six genes (RXRB, PSMB8, CHGA, ACACA, PLIN4, PLIN5) located in these regions have been investigated in relation to intramuscular composition variability in Iberian pigs, with two SNPs at the RXRB gene giving the most consistent results on oleic and monounsaturated fatty acid content.

Efecto de la genética y de la dieta sobre el lomo fresco del cerdo Ibérico (m. Longissimus dorsi)

El objetivo de este estudio fue evaluar el efecto de la línea genética, la dieta y su interacción sobre el peso, rendimiento, contenido en grasa intramuscular y color del lomo (m. Longissimus dorsi) del cerdo Ibérico. Se utilizaron un total de 96 cerdos Ibéricos machos y castrados, que fueron divididos en 12 lotes (n=8) siguiendo un diseño factorial 4×3, con dos líneas genéticas (Retinto, RR, y Torbiscal, TT) y sus cruces recíprocos (R×T y T×R). Los cerdos fueron cebados en intensivo con tres tipos de piensos enriquecidos con tres niveles de ácido oleico (bajo, L, medio, M y alto, H). Se observó un efecto significativo (P

Efecto de la línea genética y de dietas enriquecidas en ácido oleico sobre los parámetros productivos del cerdo Ibérico

La genética y la alimentación son dos de los principales factores que afectan a la producción del cerdo Ibérico, así como a la calidad de su carne y de sus productos cárnicos. El objetivo de este estudio fue evaluar el efecto de la línea genética y de la alimentación durante el cebo, así como su interacción, sobre los parámetros productivos del cerdo Ibérico. Para ello, se utilizaron un total de 96 cerdos Ibéricos machos y castrados, que fueron divididos en 12 lotes (n=8) siguiendo un diseño factorial 4×3 con dos líneas genéticas (Retinto, RR, y Torbiscal, TT) y sus cruces recíprocos (R×T and T×R). Los cerdos fueron cebados en intensivo con tres tipos de piensos enriquecidos con tres niveles de ácido oleico (bajo, L, medio, M y alto, H). Los resultados mostraron un menor (p

Modulating birth weight heritability in mice

Expected genetic response is proportional to the heritability of the trait, and this parameter is considered inherent of a specific trait in a particular population. However, models assuming heterogeneity in residual variance lead to different estimates of heritability across combinations of systematic (environmental) effects. Modifying the residual variance of the birth weight by artificial selection was shown to be feasible in a divergent selection experiment in mice. The objectives of this work were to 1) estimate the evolution of the heritability of birth weight in mice in the mentioned experiment, and 2) estimate different heritability regarding systematic effects. Data came from eleven generations of a divergent selection experiment to modify the residual variability of birth weight in mice. A total of 15,431 birth weight records from 959 females and 1,641 litters in combination with 14,786 pedigree records were used. The model used for analysis included generation, litter size, sex, and parity number as systematic effects. Each record of birth weight was assigned to the mother of the pup in the model which assumes that the residual variance is heterogeneous and partially under genetic control. Differences in heritability between lines reached values of 0.06 in the last generations. Choosing the most extreme values of systematic effects, the birth weight heritability ranged from 0.04 to 0.22. From these results, the possibility of modulating the heritability for this trait could be explored in 1 of 2 ways: selecting to decrease the residual variability, or choosing the specific levels of the systematic effects.

Genetic parameters and crossbreeding effects of fat deposition and fatty acid profiles in Iberian pig lines

The aim of this study was to estimate the genetic and environmental parameters and crossbreeding effects on fatty acid and fat traits in the Iberian pig. Our final goal is to explore target selection traits and define crossbreeding strategies. The phenotypes were obtained under intensive management from 470 animals in a diallelic experiment involving Retinto, Torbiscal, and Entrepelado lines. The data set was composed of backfat thickness at the fourth rib (BFT), intramuscular fat (IMF) in the longissimus thoracis (LT), and the fatty acid profile for IMF and subcutaneous fat (SCF) traits. Data were analyzed through a Bayesian bivariate animal model by using a reparameterization of Dickerson's model. The results obtained showed an important genetic determinism for all traits analyzed with heritability ranging from 0.09 to 0.67. The common environment litter effect also had an important effect on IMF (0.34) and its fatty acid composition (0.06-0.53) at slaughter. The additive genetic correlation between BFT and IMF (additive genetic correlation [] = 0.31) suggested that it would be possible to improve lean growth independent of the IMF with an appropriate selection index. Furthermore, the high additive genetic correlation ( = 0.68) found between MUFA tissues would seem to indicate that either the LT or SCF could be used as the reference tissue for MUFA selection. The relevance of the crossbreeding parameters varied according to the traits analyzed. Backfat thickness at the fourth rib and the fatty acid profile of the IMF showed relevant differences between crosses, mostly due to line additive genetic effects associated with the Retinto line. On the contrary, those for IMF crosses were probably mainly attributable to heterosis effects. Particularly, heterosis effects were relevant for the Retinto and Entrepelado crosses (approximately 16% of the trait), which could be valuable for a crossbreeding system involving these lines.

Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice

Data from seven generations of a divergent selection experiment designed for environmental variability of birth weight were analysed to estimate genetic parameters and to explore signs of selection response. A total of 10 783 birth weight records from 638 females and 1127 litters in combination with 10 007 pedigree records were used. Each record of birth weight was assigned to the mother of the pup in a heteroscedastic model, and after seven generations of selection, evidence of success in the selection process was shown. A Bayesian analysis showed that success of the selection process started from the first generation for birth weight and from the second generation for its environmental variability. Genetic parameters were estimated across generations. However, only from the third generation onwards were the records useful to consider the results to be reliable. The results showed a consistent positive and low genetic correlation between the birth weight trait and its environmental variability, which could allow an independent selection process. This study has demonstrated that the genetic control of the birth weight environmental variability is possible in mice. Nevertheless, before the results are applied directly in farm animals, it would be worth confirming any other implications on other important traits, such as robustness, longevity and welfare.

Transcriptional analysis of intramuscular fatty acid composition in the longissimus thoracis muscle of Iberian × Landrace back-crossed pigs

This study aimed at identifying differential gene expression conditional on the fatty acid profile of the longissimus thoracis (Lt) muscle, a prime cut of economic relevance for fresh and cured pork production. A population of 110 Iberian (25%) × Landrace (75%) back-crossed pigs was used, because these two breeds exhibit extreme profiles of intramuscular saturated fatty acid, monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) contents. Total RNA from Lt muscle was individually hybridized to GeneChip Porcine Genome arrays (Affymetrix). A principal component analysis was performed with data from the 110 animals to select 40 extreme animals based on the total fatty acid profile and the MUFA composition (MAP). Comparison of global transcription levels between extreme fatty acid profile pigs (n = 40) resulted in 219 differentially expressed probes (false discovery rate <0.10). Gene ontology, pathway and network analysis indicated that animals with higher percentages of PUFA exhibit a shift toward a more oxidative muscular metabolism state, with a raise in mitochondria function (PPARGC1A, ATF2), fatty acid uptake and oxidation (FABP5, MGLL). On the other hand, 87 probes were differentially expressed between MUFA composition groups (n = 40; false discovery rate <0.10). In particular, muscles rich in n-7 MUFA expressed higher levels of genes involved in lipid metabolism (GLUL, CRAT, PLA2G15) and lower levels of fatty acid elongation genes (ELOVL5). Moreover, the chromosomal position of FABP5, PAQR3, MGLL, PPARGC1A, GLUL and ELOVL5 co-localized with very relevant QTL for fat deposition and composition described in the same resource population. This study represents a complementary approach to identifying genes underlying these QTL effects.

Canalization analysis of birth weight in Bruna dels Pirineus beef cattle

Although heteroskedasticity has been a main topic of interest in beef cattle during recent decades, the current availability of canalization models provided new insights for animal breeding programs. Within this context, birth BW (BWT) was analyzed in the Bruna dels Pirineus beef cattle breed by implementing canalization models that accounted for heterogeneous residual variances due to systematic, permanent environmental effects and additive genetic effects. Analyses were performed on BWT data from 8,130 calves born in 12 commercial breeding herds contributing to the yield recording scheme of the Bruna dels Pirineus breed. Analytical models accounted for direct additive genetic, permanent environmental, and 4 systematic effects (i.e., age of the dam, sex of the calf, birth type, and herd-year-season), and the same effects were evaluated as potential sources of variation in the residual term. Their relevance was checked by the deviance information criterion (DIC), and only residual additive genetic, permanent environmental, birth type, and herd-year-season remained in the operational model, all of them originating relevant reductions in the DIC parameter. Bruna dels Pirineus calves showed a moderate heritability of 0.30 (95% high posterior density, 0.19 to 0.40) for BWT; additional additive genetic variability was revealed in the residual term, this being positively correlated with the direct additive genetic component (0.44; 95% high posterior density, 0.37 to 0.54). Genetic trends were evaluated on both sources of additive genetic variance, and relevant patterns were identified in several herds. Although this breed did not evidence a homogeneous genetic trend for the whole population, herd-specific positive and negative trends were revealed, suggesting the plausibility of genetic selection for canalization on BWT in beef cattle breeds. These results must be viewed as a contribution to the canalization research field, providing relevant information for the breeding scheme of the Bruna dels Pirineus breed, as well as important insights about the genetic background of BWT for the beef industry worldwide.

Genetic parameters for birthweight environmental variability in mice

Data from a divergent experiment for birthweight (BrW) environmental variability were used to estimate genetic parameters for BrW trait and its environmental variability by fitting both homoscedastic (HO) and heteroscedastic (HE) models. A total of 5 475 records of BrW from animals born from inbred dams, and 7 140 pedigree records were used. The heritability of BrW using the model HO was 0.27, with the litter effect much more important, 0.43. The model HE provided a genetic correlation between the trait and its environmental variability that was very high and negative, -0.97, and a high value for the additive genetic variance for environmental variability, suggesting an artefact in the model. The residual skewness was found to be essentially null. A model considering the genetic correlation null was also fitted, and used to obtain the breeding values for the selection process. Moreover, the trait was considered as maternal resulting in similar estimates under the model HO, but more reasonable for the genetic correlation between the trait and its environmental variability of 0.48 with a value of 0.25 for the additive genetic variance regarding environmental variability under the model HE. This led to the conclusion that environmental variability of BrW in mice must be selected via dams. Estimated parameters in a reduced dataset without inbred animals did not substantially change this conclusion.

Bayesian recursive mixed linear model for gene expression analyses with continuous covariates

The analysis of microarray gene expression data has experienced a remarkable growth in scientific research over the last few years and is helping to decipher the genetic background of several productive traits. Nevertheless, most analytical approaches have relied on the comparison of 2 (or a few) well-defined groups of biological conditions where the continuous covariates have no sense (e.g., healthy vs. cancerous cells). Continuous effects could be of special interest when analyzing gene expression in animal production-oriented studies (e.g., birth weight), although very few studies address this peculiarity in the animal science framework. Within this context, we have developed a recursive linear mixed model where not only are linear covariates accounted for during gene expression analyses but also hierarchized and the effects of their genetic, environmental, and residual components on differential gene expression inferred independently. This parameterization allows a step forward in the inference of differential gene expression linked to a given quantitative trait such as birth weight. The statistical performance of this recursive model was exemplified under simulation by accounting for different sample sizes (n), heritabilities for the quantitative trait (h(2)), and magnitudes of differential gene expression (λ). It is important to highlight that statistical power increased with n, h(2), and λ, and the recursive model exceeded the standard linear mixed model with linear (nonrecursive) covariates in the majority of scenarios. This new parameterization would provide new insights about gene expression in the animal science framework, opening a new research scenario where within-covariate sources of differential gene expression could be individualized and estimated. The source code of the program accommodating these analytical developments and additional information about practical aspects on running the program are freely available by request to the corresponding author of this article.

Genetic evaluation combining purebred and crossbred data in a pig breeding scheme

Genetic evaluations using purebred data alone and combined purebred and crossbred information were performed for lean meat percentage in a pig breeding scheme. One purebred (PB) model and 2 crossbred models (CCPS1 and CCPS2) were used in the analyses. Data were obtained from the Selección Batallé S.A. Company (Riudarenes, Spain) and spanned a period of 4 yr (2006 to 2009). The data corresponded to 3 nuclei of purebred populations, Landrace (LD), Duroc (DU), and Pietrain (PI); 1 multiplying farm with animals from a 2-way cross (TB1; DU × LD); and commercial farms with animals from a 3-way cross (TB2; TB1 × PI). Genetic parameters were similar across the models, with the exception of purebred PI. The DU and LD purebreds presented large heritabilities (0.5 to 0.6) for lean meat percentage, whereas the PI purebred showed a lower heritability (approximately 0.1) for the PB model and moderate heritability for the CCPS1 and CCPS2 models (0.2 to 0.3). The mean reliability of the predicted purebred breeding values was clearly increased when the CCPS1 and CCPS2 models were used. Moreover, a reranking of the animals with important changes in the selection decisions was observed in the PI purebred. In a simulation study, the CCPS1 model achieved a greater response to selection than the PB model for the PI purebred. On another hand, between the CCPS1 and CCPS2 models, CCPS1 was slightly superior in terms of predictive ability, exhibiting a greater robustness. These results illustrate the usefulness of using crossbred models to evaluate lean meat percentage in this pig breeding scheme.

Restricting inbreeding while maintaining selection response for weight gain in Mus musculus

An experiment with mice was designed to test the relative efficiency of three selection methods that help to minimize the rate of inbreeding during selection. A common house mice (Mus musculus) population was selected for 17 generations to increase the weight gain between 21 and 42 days. The population was split at random into three lines A, B and C where three selection methods were applied: individual selection and random mating, weighted selection with random mating and individual selection with minimum coancestry mating, respectively. There were three replicates for each line. Cumulated selection response was similar in the three lines, but there were differences in the level of inbreeding attained (in percentage): 31.24 (method A), 24.72 (method B) and 27.88 (method C). As consequence, lines B and C (weighted selection and minimum coancestry) showed a lower value of deterioration of fitness traits (the intrauterine mortality and the mortality at birth) than line A (random mating).

GSEVM v.2: MCMC software to analyze genetically structured environmental variance models

This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix executable programs, the user's guide, and some example files are freely available for research purposes at http://www.bdporc.irta.es/estudis.jsp. The main feature of the program is to compute Monte Carlo estimates of marginal posterior distributions of parameters of interest. The program is quite flexible, allowing the user to fit a variety of linear models at the level of the mean and the logvariance.

Modifying growth curve parameters by multitrait genomic selection

The use of genomic selection for changing the growth curve shape of animals, acting simultaneously on the 3 parameters of a Gompertz growth curve, was studied using computer simulation. Results showed that genomic selection modified the growth curve. Responses to all selection criteria were accompanied with a correlated response in mature weight due to the high genetic correlations between mature weight and the 2 rate parameters. Responses to selection were affected by the loss of accuracy over generations of genomic selection due to the loss of gametic disequilibrium between SNP and genes determining the parameters. In conclusion, genomic selection can be used for changing growth curve parameters. However, changing the whole curve (birth weight, adult BW, and curve shape) is not easy due to the correlation between all BW along the growth of the animal. Applying genomic selection will require a constant reevaluation of the associations between SNP and genes determining the curve parameters.

An application of change-point recursive models to the relationship between litter size and number of stillborns in pigs

We developed and implemented change-point recursive models and compared them with a linear recursive model and a standard mixed model (SMM), in the scope of the relationship between litter size (LS) and number of stillborns (NSB) in pigs. The proposed approach allows us to estimate the point of change in multiple-segment modeling of a nonlinear relationship between phenotypes. We applied the procedure to a data set provided by a commercial Large White selection nucleus. The data file consisted of LS and NSB records of 4,462 parities. The results of the analysis clearly identified the location of the change points between different structural regression coefficients. The magnitude of these coefficients increased with LS, indicating an increasing incidence of LS on the NSB ratio. However, posterior distributions of correlations were similar across subpopulations (defined by the change points on LS), except for those between residuals. The heritability estimates of NSB did not present differences between recursive models. Nevertheless, these heritabilities were greater than those obtained for SMM (0.05) with a posterior probability of 85%. These results suggest a nonlinear relationship between LS and NSB, which supports the adequacy of a change-point recursive model for its analysis. Furthermore, the results from model comparisons support the use of recursive models. However, the adequacy of the different recursive models depended on the criteria used: the linear recursive model was preferred on account of its smallest deviance value, whereas nonlinear recursive models provided a better fit and predictive ability based on the cross-validation approach.

Bayesian threshold analysis of direct and maternal genetic parameters for piglet mortality at farrowing in Large White, Landrace, and Pietrain populations

A Bayesian threshold model was fitted to analyze the genetic parameters for farrowing mortality at the piglet level in Large White, Landrace, and Pietrain populations. Field data were collected between 1999 and 2006. They were provided by 3 pig selection nucleus farms of a commercial breeding company registered in the Spanish Pig Data Bank (BDporc). Analyses were performed on 3 data sets of Large White (60,535 piglets born from 4,551 litters), Landrace (57,987 piglets from 5,008 litters), and Pietrain (42,707 piglets from 4,328 litters) populations. In the analysis, farrowing mortality was considered as a binary trait at the piglet level and scored as 1 (alive piglet) or 0 (dead piglet) at farrowing or within the first 12 h of life. Each breed was analyzed separately, and operational models included systematic effects (year-season, sex, litter size, and order of parity), direct and maternal additive genetic effects, and common litter effects. Analyses were performed by Bayesian methods using Gibbs sampling. The posterior means of direct heritability were 0.02, 0.06, and 0.10, and the posterior means of maternal heritability were 0.05, 0.13, and 0.06 for Large White, Landrace, and Pietrain populations, respectively. The posterior means of genetic correlation between the direct and maternal genetic effects for Landrace and Pietrain populations were -0.56 and -0.53, and the highest posterior intervals at 95% did not include zero. In contrast, the posterior mean of the genetic correlation between direct and maternal effects was 0.15 in the Large White population, with the null correlation included in the highest posterior interval at 95%. These results suggest that the genetic model of evaluation for the Landrace and Pietrain populations should include direct and maternal genetic effects, whereas farrowing mortality could be considered as a sow trait in the Large White population.