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L Varona

Publications and source records attributed to L Varona.

At least 19 recordsLinked to original sources
PubMed2006

Malic enzyme 1 genotype is associated with backfat thickness and meat quality traits in pigs.

Malic enzyme 1 (ME1) is a part of the tricarboxylate shuttle that provides NADPH and acetyl-CoA required in fatty acid biosynthesis. The pig ME1 locus maps on the proximal end of chromosome 1, where a quantitative trait loci (QTL) affecting fat deposition has been previously described. We amplified fragments of 1457 and 1459 bp that corresponded to the complete coding region and the 3'-untranslated region (UTR), respectively, of the pig ME1 gene. The sequences of these two fragments in pigs from three breeds (Landrace, Large White and Piétrain) contained five single nucleotide polymorphisms (SNP) in the 3'-UTR: C1706T, G1762T, A1807C, C1857A and T1880A. Three haplotypes were found in two generations of a selected Landrace population: H1 (C1706 G1762 A1807 C1857 A1880), H2 (C1706 G1762 A1807 C1857 T1880) and H3 (T1706 T1762 C1807 A1857 T1880). Using Bayesian association analyses, significant associations (highest posterior density at 95%) between ME1 genotype and backfat (BF) thickness at 171 days and muscular pH were found in a Landrace population.

Animals↗
PubMed2006

Characterization of the porcine acyl-CoA synthetase long-chain 4 gene and its association with growth and meat quality traits.

Summary Long-chain acyl-CoA synthetase (ACSL) catalyses the formation of long-chain acyl-CoA from fatty acid, ATP and CoA, activating fatty acids for subsequent reactions. Long-chain acyl-CoA synthetase thus plays an essential role in both lipid biosynthesis and fatty acid degradation. The ACSL4 gene was evaluated as a positional candidate gene for the quantitative trait loci (QTL) located between SW2456 and SW1943 on chromosome X. We have sequenced 4906 bp of the pig ACSL4 mRNA. Sequence analysis allowed us to identify 10 polymorphisms located in the 3'-UTR region and to elucidate two ACSL4 haplotypes. Furthermore, a QTL and an association study between polymorphisms of the ACSL4 gene and traits of interest were carried out in an Iberian x Landrace cross. We report QTL that have not been previously identified, and we describe an association of the ACSL4 polymorphisms with growth and percentage of oleic fatty acid. Finally, we have determined allelic frequencies in 140 pigs belonging to the Iberian, Landrace, Large White, Meishan, Pietrain, Duroc, Vietnamese, Peccary and Babirusa populations.

Animals↗
PubMed2006

Comparison of genetic models for analysing the effects of a PvuII polymorphism in the oestrogen receptor 1 (ESR1) gene on prolificacy in an Iberian x Meishan pig population.

The effect of a previously reported PvuII polymorphism in oestrogen receptor 1 (ESR1) was analysed in an F(2) population of Iberian x Meishan pigs. We tested three hypotheses: (1) that a causal mutation was fixed in the parental populations, (2) that a causal mutation existed that was in complete linkage disequilibrium with the alleles of the PvuII polymorphism and (3) that a causal mutation existed in linkage disequilibrium within each parental population. The third model was the most plausible based on the available data. ESR1 alleles displayed different patterns of linkage disequilibrium with the causal mutation in each of the parental populations and the PvuII polymorphism was clearly not the causal mutation. As a consequence, the use of the ESR1 mutation for selection must be evaluated for a particular pig population before it is applied.

Alleles↗
PubMed2006

Characterization of the porcine FABP5 gene and its association with the FAT1 QTL in an Iberian by Landrace cross.

We have characterized and mapped the porcine fatty acid binding protein 5, epidermal (FABP5) gene. According to linkage and RH mapping, this gene is located close to the FABP4 (fatty acid binding protein 4, adipocyte) gene on swine chromosome 4. We resequenced 4.7 kb of the FABP5 gene in the parental population of an Iberian x Landrace cross (IBMAP), identifying seven SNPs arranged in two distinct FABP5 haplotypes. QTL and association analyses in the IBMAP population showed that this gene is strongly associated with fat deposition. QTL and haplotype analysis revealed that both FABP4 and FABP5 (clustered in mammals) are major candidate genes for the FAT1 QTL; the most likely position for the FAT1 QTL is between these two genes. Finally, our results suggest the presence of more than one QTL affecting fatness traits on porcine chromosome 4.

Animals↗
PubMed2006

Adipocyte fatty-acid binding protein is closely associated to the porcine FAT1 locus on chromosome 4.

We identified 22 polymorphisms in the adipocyte fatty-acid binding protein (FABP4) gene, a strong positional candidate gene for the FAT1 locus in porcine chromosome 4. The most informative polymorphism, an insertion/deletion in intron 1, together with a single nucleotide polymorphism in intron 3, was genotyped in a cross between Iberian and Landrace pigs. After performing QTL, single marker, and haplotype analyses, we showed that there were at least 2 quantitative trait genes in the FAT1 region and that the FABP4 polymorphism was tightly associated to fatness. A comparison of allelic frequencies in a panel of pig breeds suggested that the Del2634C polymorphism was under indirect selection. We also showed that FABP4 is tightly associated to fatness but not growth. Furthermore, a haplotype analysis suggests that there is genetic heterogeneity at the FAT1 locus within the Landrace breed.

Animals↗
PubMed2006

Parametric bootstrap for testing model fitting in the proportional hazards framework: an application to the survival analysis of Bruna dels Pirineus beef calves.

Given that correct assumptions on the baseline survival function are determinant for the validity of further inferences, specific tools to test the fit of a model to real data become essential in proportional hazards models. In this sense, we have proposed a parametric bootstrap to test the fit of survival models. Monte Carlo simulations are used to generate new data sets from the estimates obtained through the assumed models, and then bootstrap intervals can be established for the survival function along the time space studied. Significant fitting deficiencies are revealed when the real survival function is not included within the bootstrap interval. We tested this procedure in a survival data set of Bruna dels Pirineus beef calves, assuming 4 parametric models (exponential, Weibull, exponential time-dependent, Weibull time-dependent) and the Cox's semiparametric model. Fitting deficiencies were not observed for the Cox's model and the exponential time-dependent model, whereas the Weibull time-dependent model suffered from moderate overestimation at different ages. Thus, the exponential time-dependent model appears to be preferable because of its correct fit for survival data of beef calves and its smaller computational and time requirements. Exponential and Weibull models were completely rejected due to the continuous over- and underestimation of the survival probability reported. Results here highlighted the flexibility of parametric models with time-dependent effects, achieving a fit comparable to nonparametric models.

Animals↗
PubMed2005

Fine mapping of porcine chromosome 6 QTL and LEPR effects on body composition in multiple generations of an Iberian by Landrace intercross.

The leptin receptor gene (LEPR) is a candidate for traits related to growth and body composition, and is located on SSC6 in a region where fatness and meat composition quantitative trait loci (QTL) have previously been detected in several F2 experimental designs. The aims of this work were: (i) to fine map these QTL on a larger sample of animals and generations (F3 and backcross) of an Iberian x Landrace intercross and (ii) to examine the effects of LEPR alleles on body composition traits. Eleven single nucleotide polymorphisms (SNPs) were detected by sequencing LEPR coding regions in Iberian and Landrace pig samples. Three missense polymorphisms were genotyped by pyrosequencing in 33 F0, 70 F1, 418 F2, 86 F3 and 128 individuals coming from the backcross of four F2 males with 24 Landrace females. Thirteen microsatellites and one SNP were also genotyped. Traits analysed were: backfat thickness at different locations (BF(T)), intramuscular fat percentage (IMF(P)), eye muscle area (EM(A)), loin depth (LO(D)), weight of shoulder (SH(W)), weight of ribs (RIB(W)) and weight of belly bacon (BB(W)). Different statistical models were applied in order to evaluate the number and effects of QTL on chromosome 6 and the possible causality of the LEPR gene variants with respect to the QTL. The results support the presence of two QTL on SSC6. One, at position 60-100 cM, affects BF(T) and RIB(W). The other and more significant maps in a narrow region (130-132 cM) and affects BF(T), IMF(P), EM(A), LO(D), SH(W), RIB(W) and BB(W). Results also support the association between LEPR alleles and BF(T) traits. The possible functional implications of the analysed polymorphisms are considered.

Alleles↗
PubMed2005

QTL mapping for teat number in an Iberian-by-Meishan pig intercross.

The aim of this study was to investigate chromosomal regions affecting the number of teats in pigs and possible epistatic interactions between the identified quantitative trait loci (QTL). An experimental F2 cross between Iberian and Chinese Meishan lines was used for this purpose. A genomic scan was conducted with 117 markers covering the 18 porcine autosomes. Linkage analyses were performed by interval mapping using an animal model to estimate QTL and additive polygenic effects. Complementary analyses with models fitting two QTL were also carried out. The results showed three genomewide significant QTL mapping on chromosomes 5, 10 and 12, whose joint action control up to 30% of the phenotypic variance of the trait. Meishan alleles had a positive additive effect on teat number, and a positive-additive x additive-epistatic interaction was detected between QTL on chromosomes 10 and 12.

Animals↗
PubMed2005

A simulation study on the detection of causal mutations from F2 experiments.

A simulation study has been performed to evaluate the power and the rate of false positives for the detection of causal mutations under two different models of analysis. We used an F2 design generated from an F0 population of five sires of line 1 and 40 dams of line 2 to produce an F1 population of 10 sires and 80 dams. Two different locations of the causal mutation and several frequencies of the mutations in the parental populations were considered. The first model included only the genetic configuration of the mutation, while the second model also included the probability of line origin given the neutral markers. Both models performed well when the mutation at the candidate gene was the causal mutation, although a greater power was obtained using the first model, because of its relative simplicity compared to the second one. However, when the candidate gene mutation was a neutral mutation, the second model presented a lower rate of false positives than the first. Moreover, in some cases the second model allowed distinction between the neutral and the causal mutation. The F2 design has a great power to detect quantitative trait loci provided by linkage disequilibrium, but also makes it difficult to discriminate between causal and neutral mutations. Therefore a high percentage of false positives can be expected. The limitations of F2 designs for discriminating between neutral and causal mutations are discussed.

Animals↗
PubMed2005

The value of prior information for detection of QTL affecting longitudinal traits: an example using Von Bertalanffy growth function.

A Bayesian procedure is presented for detecting quantitative trait loci (QTL) affecting longitudinal traits. The statistical model assumes a QTL affecting the prior distribution of the parameters of a given production function, under a hierarchical Bayesian scheme. Marginal posterior distributions for the effects associated with the QTL are calculated using Markov chain Monte Carlo methods. Furthermore, the Bayesian analysis allows the use of some available relevant information that can improve the detection of the QTL substantially. To illustrate the procedure, an example of QTL detection using the Von Bertalanffy growth function is presented with a F2 pig population bred from Iberian boars and Landrace sows. Animals of the F2 population were genotyped for seven markers in chromosome 2 (SSC2). Two prior distributions for the mean effect of the parameters related with birth and adult weight were compared. On the one hand, vague prior distributions were used, and, on the other, there were assumed univariate Gaussian distributions that ensure biologically meaningful adult and birth weights on the posterior growth curves. Results from the second prior distribution supported the presence of QTL, by showing that individuals with both alleles of Iberian origin had lower rates of maturation. On the contrary, when vague priors were used, the procedure was not able to detect QTL.

Animals↗
PubMed2005

Large-scale, multibreed, multitrait analyses of quantitative trait loci experiments: the case of porcine X chromosome.

A QTL analysis of multibreed experiments (i.e., crossed populations involving more than two founder breeds) offers clear advantages over classical two-breed crosses, among them increased power and a more comprehensive coverage of the total genetic variability in the species. An alternative to designed multibreed crosses is to reanalyze jointly several experiments involving different breeds. We report a multibreed, multitrait QTL analysis of SSCX that involves five different crosses, six breeds, and almost 3,000 genotyped individuals using a truly multibreed strategy to allow for any number of founder breed origins. Traits analyzed were growth, fat thickness, carcass length, and shoulder and ham weights. Generally, the joint analysis resulted in more significant QTL than the single-experiment analyses. We show that the QTL for fatness, which is highly significant (nominal P < 10(-43)), is of Asiatic origin (Meishan). The next most significant QTL (nominal P < 10(-15)) affected ham weight and seems to be segregating only between Large White and the rest of the breeds. A multitrait, multi-QTL analysis suggests that these are two distinct loci. Additionally, a locus segregating only between Iberian and Landrace affects live weight. The advantages of joint, multibreed analyses clearly outweigh their potential risks.

Adipose Tissue↗
PubMed2005

Identification of carcass and meat quality quantitative trait loci in a Landrace pig population selected for growth and leanness.

The identification of QTL related to production traits that are relevant for the pig industry has been mostly performed by using divergent crosses. The main objective of the current study was to investigate whether these growth, fatness, and meat quality QTL, previously described in diverse experimental populations, were segregating in a Landrace commercial population selected for litter size, backfat thickness, and growth performance. We have found QTL for carcass weight (posterior P > 0.75), cutlet weight (posterior P > 0.99), weight of ham (posterior P > 0.75), shoulders weight (posterior probability > 0.99), and shear firm-ness (posterior P > 0.99) on pig Chromosome 2. Moreover, QTL with posterior P > 0.75 for fat thickness between the 3rd and 4th ribs (Chromosome 7), rib weights (Chromosome 8), backfat thickness (Chromosomes 8, 9, and 10), and b Minolta color component (Chromosome 7) were identified. These results indicate that commercial purebred populations retain a significant amount of genetic variation, even for traits that have been selected for many generations.

Adipose Tissue↗
PubMed2005

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population.

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.

Adipose Tissue↗
PubMed2005

Bayes factor analysis for the genetic background of physiological and vitality variables of F2 Iberian x Meishan newborn piglets.

The Bayes factor (BF) procedure was applied to examine the additive genetic component of several physiological and vitality variables for newborn pigs. Nine variables were studied: heart rate, arterial oxygen saturation, rectal temperature (all at birth and 60 min later), birth weight, interval between birth and first teats contact, and interval between birth and first colostrum intake. The available numbers of data ranged from 288 (heart rate at 60 min) to 839 records (birth weight) from F(2) Iberian x Meishan newborn pigs. We compared a model with zero heritability (nonheritable) with the one where the additive genetic background was included. The BF was used to discriminate between both candidate models. Very strong evidence of genetic background was detected for heart rate 60 min after birth (BF = 48.90), and strong evidence was detected for rectal temperature at birth (BF = 13.82). Posterior modes (means) of heritabilities were 0.29 (0.32) and 0.40 (0.39), respectively. In addition, substantial evidence of absence of genetic background was detected for arterial oxygen saturation at birth.

Animals↗
PubMed2005

Genetic parameters of fertility in two lines of rabbits with different reproductive potential.

A Bayesian analysis with a threshold model was performed for fertility defined as a binary trait (1 = successful mating, 0 = unsuccessful mating) in two populations of rabbits of different reproductive potential and different genetic origin: Line P selected for litter size and Line C selected for growth rate. There were 20,793 records of natural mating (86.2% successful) in Line C between 1983 and 2003, and 17,548 records (80.5% successful) in Line P, between 1992 and 2003. Data related to 5,388 and 3,848 females and 1,021 and 685 males in Lines C and P, respectively. The pedigree included 6,409 and 4,533 individuals in Lines C and P, respectively. The binary response was modeled under a probit approach. The model for the latent variable included male and female additive genetic effects, male and female permanent environmental effects, and the year-season and physiological status of the female (nulliparous, multiparous lactating, or multiparous nonlactating) as systematic effects. Means (standard deviation in parentheses) of the estimated marginal posterior distribution (EMPD) of male heritability were 0.013 (0.006) and 0.010 (0.008) in Lines C and P, respectively, and those of EMPD of female heritability were 0.056 (0.013) and 0.062 (0.018) in Lines C and P, respectively. Means of the EMPD of the proportion of the phenotypic variance due to environmental male and female effects were, respectively, 0.031 (0.007) and 0.128 (0.018) in Line C and 0.053 (0.010) and 0.231 (0.024) in Line P. Means (standard deviations in parentheses) of the EMPD of genetic correlation between male and female fertility were 0.733 (0.197) in Line C and 0.434 (0.381) in Line P. The posterior distribution of genetic correlations presents a huge dispersion, and the estimates should be taken with caution because of the almost negligible estimate of the male genetic component. Results indicate that little genetic variation exists for female fertility, and practically none for male fertility. It would, therefore, be possible to improve reproductive performance by including female fertility in a breeding program, but response to selection would be very small.

Animals↗
PubMed2005

Polymorphism of the pig 2,4-dienoyl CoA reductase 1 gene (DECR1) and its association with carcass and meat quality traits.

We characterized the nearly complete coding sequence of the pig 2,4-dienoyl CoA reductase 1 (DECR1) gene, which encodes an enzyme involved in the beta-oxidation of polyunsaturated fatty enoyl-CoA esters and maps on a linoleic QTL located on Chromosome 4. Sequencing of a 937-bp fragment encompassing exons 2 and 10 revealed the existence of two missense SNP at exon 2 (C181 --> G181) and exon 5 (C458 -->G458). These two SNP are associated with Val (C) --> Leu (G) and Ser (C) --> Thr (G) conservative AA replacements at positions 61 and 153 of the DECR1 protein, respectively. Moreover, DECR1 genotyping in a representative sample of 184 pigs from the Large White, Pietrain, Iberian, Duroc, and Landrace breeds demonstrated the existence of disequilibrium linkage between these two SNP (Haplotype 1: C181C458; Haplotype 2: G181G458). An association analysis between DECR1 genotype and growth, carcass, and meat quality traits in a highly selected Landrace population (n = 470) revealed differences among genotypes for isocitrate dehydrogenase activity (highest posterior density [HPD] of 90%), longissimus thoracis pH (HPD of 95%), lightness (HPD of 90 to 95%), and redness (HPD of 95%). Because these associations were not consistently found in the three available genotype comparisons, we believe that exon 2 and 5 polymorphisms at the DECR1 gene might be in linkage disequilibrium with the true causal mutation influencing isocitrate dehydrogenase activity and muscle color and pH.

Animals↗
PubMed2004

Derivation of a Bayes factor to distinguish between linked or pleiotropic quantitative trait loci.

A simple procedure to calculate the Bayes factor between linked and pleiotropic QTL models is presented. The Bayes factor is calculated from the marginal prior and posterior densities of the locations of the QTL under a linkage and a pleiotropy model. The procedure is computed with a Gibbs sampler, and it can be easily applied to any model including the location of the QTL as a variable. The procedure was compared with a multivariate least-squares method. The proposed procedure showed better results in terms of power of detection of linkage when low information is available. As information increases, the performance of both procedures becomes similar. An example using data provided by an Iberian by Landrace pig intercross is presented. The results showed that three different QTL segregate in SSC6: a pleiotropic QTL affects myristic, palmitic, and eicosadienoic fatty acids; another pleiotropic QTL affects palmitoleic, stearic, and vaccenic fatty acids; and a third QTL affects the percentage of linoleic acid. In the example, the Bayes factor approach was more powerful than the multivariate least-squares approach.

Animals↗