Equivalence of variance components between standard and recursive genetic models using LDL' transformations.

BACKGROUND: Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL' or block-LDL' transformations. RESULTS: The procedure was employed on a dataset comprising five traits (birth weight-BW, weight at 90 days-W90, weight at 210 days-W210, cold carcass weight-CCW and conformation-CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models. CONCLUSIONS: The LDL' or block-LDL' transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models.

Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed.

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131-132 Mb), BTA2 (1-11 Mb), BTA3 (32-33 Mb), BTA6 (36-38 Mb), BTA16 (24-26 Mb), and BTA 21 (56-57 Mb). These regions contain, amongst others, the following candidate genes: NCK1, MSTN, KCNA3, LCORL, NCAPG, and RIN3.

Mapping Recombination Rate on the Autosomal Chromosomes Based on the Persistency of Linkage Disequilibrium Phase Among Autochthonous Beef Cattle Populations in Spain.

In organisms with sexual reproduction, genetic diversity, and genome evolution are governed by meiotic recombination caused by crossing-over, which is known to vary within the genome. In this study, we propose a simple method to estimate the recombination rate that makes use of the persistency of linkage disequilibrium (LD) phase among closely related populations. The biological material comprised 171 triplets (sire/dam/offspring) from seven populations of autochthonous beef cattle in Spain (Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta, and Rubia Gallega), which were genotyped for 777,962 SNPs with the BovineHD BeadChip. After standard quality filtering, we reconstructed the haplotype phases in the parental individuals and calculated the LD by the correlation -r- between each pair of markers that had a genetic distance < 1 Mb. Subsequently, these correlations were used to calculate the persistency of LD phase between each pair of populations along the autosomal genome. Therefore, the distribution of the recombination rate along the genome can be inferred since the effect of the number of generations of divergence should be equivalent throughout the genome. In our study, the recombination rate was highest in the largest chromosomes and at the distal portion of the chromosomes. In addition, the persistency of LD phase was highly heterogeneous throughout the genome, with a ratio of 25.4 times between the estimates of the recombination rates from the genomic regions that had the highest (BTA18-7.1 Mb) and the lowest (BTA12-42.4 Mb) estimates. Finally, an overrepresentation enrichment analysis (ORA) showed differences in the enriched gene ontology (GO) terms between the genes located in the genomic regions with estimates of the recombination rate over (or below) the 95th (or 5th) percentile throughout the autosomal genome.

A multivariate analysis with direct additive and inbreeding depression load effects.

BACKGROUND: Inbreeding is caused by mating between related individuals and its most common consequence is inbreeding depression. Several studies have detected heterogeneity in inbreeding depression among founder individuals, and recently a procedure for predicting hidden inbreeding depression loads associated with founders and the Mendelian sampling of non-founders has been developed. The objectives of our study were to expand this model to predict the inbreeding loads for all individuals in the pedigree and to estimate the covariance between the inbreeding loads and the additive genetic effects for the trait of interest. We tested the proposed approach with simulated data and with two datasets of records on weaning weight from the Spanish Pirenaica and Rubia Gallega beef cattle breeds. RESULTS: The posterior estimates of the variance components with the simulated datasets did not differ significantly from the simulation parameters. In addition, the correlation between the predicted and simulated inbreeding loads were always positive and ranged from 0.27 to 0.82. The beef cattle datasets comprised 35,126 and 75,194 records on weights between 170 and 250 days of age, and pedigrees of 308,836 and 384,434 individual-sire-dam entries for the Pirenaica and Rubia Gallega breeds, respectively. The posterior mean estimates of the variance of inbreeding depression loads were 29,967.8 and 28,222.4 for the Pirenaica and Rubia Gallega breeds, respectively. They were larger than those of the additive variance (695.0 and 439.8 for Pirenaica and Rubia Gallega, respectively), because they should be understood as the variance of the inbreeding depression achieved by a fully inbred (100%) descendant. Therefore, the inbreeding loads have to be rescaled for smaller inbreeding coefficients. In addition, a strong negative correlation (- 0.43 ± 0.10) between additive effects and inbreeding loads was detected in the Pirenaica, but not in the Rubia Gallega breed. CONCLUSIONS: The results of the simulation study confirmed the ability of the proposed procedure to predict inbreeding depression loads for all individuals in the populations. Furthermore, the results obtained from the two real datasets confirmed the variability in the inbreeding depression loads in both breeds and suggested a negative correlation of the inbreeding loads with the additive genetic effects in the Pirenaica breed.

On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations.

BACKGROUND: Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations. RESULTS: Analysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic-pituitary-thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors. CONCLUSIONS: We show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits.

Consequences of paternally inherited effects on the genetic evaluation of maternal effects.

BACKGROUND: Mixed models are commonly used for the estimation of variance components and genetic evaluation of livestock populations. Some evaluation models include two types of additive genetic effects, direct and maternal. Estimates of variance components obtained with models that account for maternal effects have been the subject of a long-standing controversy about strong negative estimates of the covariance between direct and maternal effects. Genomic imprinting is known to be in some cases statistically confounded with maternal effects. In this study, we analysed the consequences of ignoring paternally inherited effects on the partitioning of genetic variance. RESULTS: We showed that the existence of paternal parent-of-origin effects can bias the estimation of variance components when maternal effects are included in the evaluation model. Specifically, we demonstrated that adding a constraint on the genetic parameters of a maternal model resulted in correlations between relatives that were the same as those obtained with a model that fits only paternally inherited effects for most pairs of individuals, as in livestock pedigrees. The main consequence is an upward bias in the estimates of the direct and maternal additive genetic variances and a downward bias in the direct-maternal genetic covariance. This was confirmed by a simulation study that investigated five scenarios, with the trait affected by (1) only additive genetic effects, (2) only paternally inherited effects, (3) additive genetic and paternally inherited effects, (4) direct and maternal additive genetic effects and (5) direct and maternal additive genetic plus paternally inherited effects. For each scenario, the existence of a paternally inherited effect not accounted for by the estimation model resulted in a partitioning of the genetic variance according to the predicted pattern. In addition, a model comparison test confirmed that direct and maternal additive models and paternally inherited models provided an equivalent fit. CONCLUSIONS: Ignoring paternally inherited effects in the maternal models for genetic evaluation can lead to a specific pattern of bias in variance component estimates, which may account for the unexpectedly strong negative direct-maternal genetic correlations that are typically reported in the literature.

A Bayesian model for the analysis of transgenerational epigenetic variation.

Epigenetics has become one of the major areas of biological research. However, the degree of phenotypic variability that is explained by epigenetic processes still remains unclear. From a quantitative genetics perspective, the estimation of variance components is achieved by means of the information provided by the resemblance between relatives. In a previous study, this resemblance was described as a function of the epigenetic variance component and a reset coefficient that indicates the rate of dissipation of epigenetic marks across generations. Given these assumptions, we propose a Bayesian mixed model methodology that allows the estimation of epigenetic variance from a genealogical and phenotypic database. The methodology is based on the development of a T: matrix of epigenetic relationships that depends on the reset coefficient. In addition, we present a simple procedure for the calculation of the inverse of this matrix ( T-1: ) and a Gibbs sampler algorithm that obtains posterior estimates of all the unknowns in the model. The new procedure was used with two simulated data sets and with a beef cattle database. In the simulated populations, the results of the analysis provided marginal posterior distributions that included the population parameters in the regions of highest posterior density. In the case of the beef cattle dataset, the posterior estimate of transgenerational epigenetic variability was very low and a model comparison test indicated that a model that did not included it was the most plausible.

The effects of two alleles of IGF2 on fat content in pig carcasses and pork.

The different fat infiltration capabilities of two alleles of IGF2 (G3072A) have been investigated in pigs of a Landrace-Large White×Duroc cross. Paternally inherited G allele carrier pigs show an increased content of adipose rich meat cuts such as the lard or the belly and 4mm larger backfat thickness values. Paternally inherited A carrier pigs on the other hand contain larger muscle tissue rich cuts such as the loin, the ham and the tenderloin and have 0.19 units lower feed conversion index. No substantial differences have been found neither in intramuscular fat content in several muscles nor in meat quality in both pig groups. Hams of paternally inherited G carrier pigs are richer in both subcutaneous adipose tissue (23.1 vs 19.1mm backfat thickness) and intermuscular fat content. The suitability and the economics of using any of the two of both genotypes for cured ham production are discussed.

Identification of 14 new single nucleotide polymorphisms in the bovine SLC27A1 gene and evaluation of their association with milk fat content.

The solute carrier family 27 member 1 (SLC27A1) is an integral membrane protein involved in the transport of long-chain fatty acids across the plasma membrane. This protein has been implicated in diet-induced obesity and is thought to be important in the control of energy homeostasis. In previous reports, our group described the isolation and characterization of the bovine SLC27A1 gene. The bovine gene is organized in 13 exons spanning over more than 40 kb of genomic DNA and maps in BTA 7 where several quantitative trait loci for fat related traits have been described. Because of its key role in lipid metabolism and its genomic localization, in the present work the search for variability in the bovine SLC27A1 gene was carried out with the aim of evaluating its potential association with milk fat content in dairy cattle. By sequencing analysis of all exons and flanking regions 14 new single nucleotide polymorphisms (SNPs) were identified: 1 in the promoter, 7 in introns and 6 in exons. Allele frequencies of all the SNPs were calculated by minisequencing analysis in two groups of Holstein-Friesian animals with highest and lowest milk-fat content estimated breeding values as well as in animals of two Spanish cattle breeds, Asturiana de los Valles and Menorquina. In the conditions assayed, no significant differences between Holstein-Friesian groups were found for any of the SNPs, suggesting that the SLC27A1 gene may have a poor or null effect on milk fat content. In Asturiana and Menorquina breeds all the positions were polymorphic with the exception of SNPs 1 and 8 in which C allele was fixed in both of them.

Effect of different Duroc line sires on carcass composition, meat quality and dry-cured ham acceptability.

Carcasses of 399 malignant hyperthermia gene free pigs from crosses sired by three types of Duroc (Virgen de la Fuente, DU1; Diputación de Teruel, DU2; DanBred, DU3) were analyzed for carcass and meat quality. Carcass leanness and fat parameters were measured at the last rib and at the space between the 3rd and 4th last ribs counting from the last one. Weights, pH, electrical conductivity, colour and intramuscular fat were also measured. A sample of 133 legs per cross were processed by dry-curing. The ham portion including Biceps femoris, Semimembranosus and Semitendinosus muscles was evaluated for instrumental texture and colour, biochemical and sensory analyses and acceptability (trained panel and consumers). DU3 carcasses were well conformed but lean. DU1 carcasses had a lower conformation but higher marbling. DU2 carcasses were intermediate. Dry-cured hams from DU1-sired pigs had a higher overall acceptability, although fat content influenced a consumers group negatively. Leaner DU3 hams had the lowest acceptability.

Allelic incidence in several pig breeds of a missense variant of pig melanocortin-4 receptor (MC4R) gene associated with carcass and productive traits; its relation to IGF2 genotype.

MC4R, melanocortin-4 receptor, is involved in feed intake regulation. A mutation in a single base of MC4R, a G/A substitution in position 1426, has been linked to enhanced backfat thickness, average daily gain and daily feed intake. We present in this work a method to diagnose this mutation using real time PCR (RT-PCR) which allows rapid, cheap and reliable analysis of hundreds of samples in just 2h after DNA extraction. We have used this RT-PCR based assay to study the incidence of the mutation in several pig breeds or crosses (Iberian, Duroc, Pietrain, Large White, Large White×Pietrain) and wild boars. IGF2, insuline like growth factor 2, a gene with well demonstrated effects on carcass composition, of all these animals has also been analyzed and we show, using linkage disequilibrium analysis that both genes are independent. The implications of our results for pig selection toward fatty or lean carcasses are discussed.

Pedigree analysis of eight Spanish beef cattle breeds.

The genetic structure of eight Spanish autochthonous populations (breeds) of beef cattle were studied from pedigree records. The populations studied were: Alistana and Sayaguesa (minority breeds), Avileña - Negra Ibérica and Morucha ("dehesa" breeds, with a scarce incidence of artificial insemination), and mountain breeds, including Asturiana de los Valles, Asturiana de la Montaña and Pirenaica, with extensive use of AI. The Bruna dels Pirineus breed possesses characteristics which make its classification into one of the former groups difficult. There was a large variation between breeds both in the census and the number of herds. Generation intervals ranged from 3.7 to 5.5 years, tending to be longer as the population size was larger. The effective numbers of herds suggest that a small number of herds behaves as a selection nucleus for the rest of the breed. The complete generation equivalent has also been greatly variable, although in general scarce, with the exception of the Pirenaica breed, with a mean of 3.8. Inbreeding effective population sizes were actually small (21 to 127), especially in the mountain-type breeds. However, the average relatedness computed for these breeds suggests that a slight exchange of animals between herds will lead to a much more favourable evolution of inbreeding. The effective number of founders and ancestors were also variable among breeds, although in general the breeds behaved as if they were founded by a small number of animals (25 to 163).