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Toxoplasmosis chorioretinitis is commonly diagnosed by an ophthalmologist through the evaluation of the fundus images of a patient. Early detection of these lesions may help to prevent blindness. In this article we present a data set of fundus images labeled into three categories: healthy eye, inactive and active chorioretinitis. The dataset was developed by three ophthalmologists with expertise in toxoplasmosis detection using fundus images. The dataset will be of great use to researchers working on ophthalmic image analysis using artificial intelligence techniques for the automatic detection of toxoplasmosis chorioretinitis., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Inc.)

Panoramic images are one of the most requested exams by dentists for allowing the visualization of the entire mouth. Interpreting X-ray images is a time-consuming task in which misdiagnoses can occur due to the inexperience or fatigue of professionals. In this work, we applied different image enhancement techniques as a pre-processing step to determine which image features correlate with improvements in teeth detection in panoramic images using deep learning architectures. We contrasted the performance of five object-detection architectures using 300 panoramic images of a public dataset. We evaluated the enhancement in the pre-processing step and the detection performance. Quality and detection metrics were considered, and the cross-correlation between them was computed for every object-detection method contemplated. We observe the dependence of the detection performance with some image enhancement techniques, especially those that introduce less noise and preserve the global contrast of the image.

INGA FOOD S. A., as a Spanish company that produces and commercializes fattened pigs, has produced a hybrid Iberian sow called CASTÚA by crossing the Retinto and Entrepelado varieties. The selection of the parental populations is based on selection criteria calculated from purebred information, under the assumption that the genetic correlation between purebred and crossbred performance is high; however, these correlations can be less than one because of a GxE interaction or the presence of non-additive genetic effects. This study estimated the additive and dominance variances of the purebred and crossbred populations for litter size, and calculated the additive genetic correlations between the purebred and crossbred performances. The dataset consisted of 2030 litters from the Entrepelado population, 1977 litters from the Retinto population, and 1958 litters from the crossbred population. The individuals were genotyped with a GeneSeek ® GGP Porcine70K HDchip. The model of analysis was a 'biological' multivariate mixed model that included additive and dominance SNP effects. The estimates of the additive genotypic variance for the total number born (TNB) were 0.248, 0.282 and 0.546 for the Entrepelado, Retinto and Crossbred populations, respectively. The estimates of the dominance genotypic variances were 0.177, 0.172 and 0.262 for the Entrepelado, Retinto and Crossbred populations. The results for the number born alive (NBA) were similar. The genetic correlations between the purebred and crossbred performance for TNB and NBA-between the brackets-were 0.663 in the Entrepelado and 0.881 in Retinto poplulations. After backsolving to obtain estimates of the SNP effects, the additive genetic variance associated with genomic regions containing 30 SNPs was estimated, and we identified four genomic regions that each explained > 2% of the additive genetic variance in chromosomes (SSC) 6, 8 and 12: one region in SSC6, two regions in SSC8, and one region in SSC12.

This paper presents a data set with information on meteorological data and electricity consumption in the department of Alto Paraná, Paraguay. The meteorological data were registered every three hours at the Aeropuerto Guarani, Department of Alto Paraná, which belongs to the Dirección Nacional de Aeronáutica Civil of Paraguay. The final data consists of a total of 22.445 records of temperature, relative humidity, wind speed and atmospheric pressure. On the other hand, the electrical energy consumption data set contains a total of 1.848.947 records, all of them coming from the one hundred and fifteen feeders located throughout the Alto Paraná region of Paraguay. Electrical energy consumption data was provided by Administración Nacional de Electricidad (ANDE). The analysis of this data can yield insights regarding the energy consumption in the area., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s). Published by Elsevier Inc.)

In the automatic diagnosis of ocular toxoplasmosis (OT), Deep Learning (DL) has arisen as a powerful and promising approach for diagnosis. However, despite the good performance of the models, decision rules should be interpretable to elicit trust from the medical community. Therefore, the development of an evaluation methodology to assess DL models based on interpretability methods is a challenging task that is necessary to extend the use of AI among clinicians. In this work, we propose a novel methodology to quantify the similarity between the decision rules used by a DL model and an ophthalmologist, based on the assumption that doctors are more likely to trust a prediction that was based on decision rules they can understand. Given an eye fundus image with OT, the proposed methodology compares the segmentation mask of OT lesions labeled by an ophthalmologist with the attribution matrix produced by interpretability methods. Furthermore, an open dataset that includes the eye fundus images and the segmentation masks is shared with the community. The proposal was tested on three different DL architectures. The results suggest that complex models tend to perform worse in terms of likelihood to be trusted while achieving better results in sensitivity and specificity.

Ocular toxoplasmosis (OT) is commonly diagnosed through the analysis of fundus images of the eye by a specialist. Despite Deep Learning being widely used to process and recognize pathologies in medical images, the diagnosis of ocular toxoplasmosis(OT) has not yet received much attention. A predictive computational model is a valuable time-saving option if used as a support tool for the diagnosis of OT. It could also help diagnose atypical cases, being particularly useful for ophthalmologists who have less experience. In this work, we propose the use of a deep learning model to perform automatic diagnosis of ocular toxoplasmosis from images of the eye fundus. A pretrained residual neural network is fine-tuned on a dataset of samples collected at the medical center of Hospital de Clínicas in Asunción, Paraguay. With sensitivity and specificity rates equal to 94% and 93%,respectively, the results show that the proposed model is highly promising. In order to replicate the results and advance further in this area of research, an open data set of images of the eye fundus labeled by ophthalmologists is made available.

This article presents a database containing 757 color fundus images acquired at the Department of Ophthalmology of the Hospital de Clínicas, Facultad de Ciencias Médicas (FCM), Universidad Nacional de Asunción (UNA), Paraguay. Firstly, the retinal images were acquired with a clinical procedure presented in this paper. The acquisition of the retinographies was made through the Visucam 500 camera of the Zeiss brand. Next, two expert ophthalmologists have classified the dataset. These data can help physicians and researchers in the detection of cases of Non-Proliferative Diabetic Retinopathy (NPDR) and Proliferative Diabetic Retinopathy (PDR), in their different stages. The dataset generated will be useful for ophthalmologists and researchers to work on automatic detection algorithms for Diabetic Retinopathy (DR)., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

The high deposition of intramuscular fat and the content of oleic fatty acid are characteristic of the Iberian pig. These two parameters present great variability and are differentiated amongst the varieties that make up the Iberian pig population. Although previous studies generated evidence for causal genes and polymorphisms associated to the adipogenic potential of the Iberian pig, there is little information about how genetic expression influences this trait's variability. The aim of this study was to analyses the expression profile between two varieties of Iberian pig (Torbiscal and Retinto) and their reciprocal crosses differentiated in their intramuscular fat (IMF) content and fatty acid (FA) composition in the Longissimus thoracis muscle using an RNA-seq approach. Our results corroborate that the Retinto variety is the fattiest amongst all studied varieties as its upregulated genes, such as FABP3 and FABP5 , SLC27A1 and VEGFA among others, contribute to increasing adiposity. In its turn, Torbiscal pigs showed an upregulation of genes associated with the inhibition of fat deposition such as ADIPOQ and CPT1A . Further genetic variation analysis in these Iberian varieties showed relevant associations for SNP located within the differentially expressed genes with IMF and FA content. Thus, the differences found in the genetic architecture and the muscle transcriptome of these Iberian varieties might explain the variability in their fat content and composition and hence, their meat quality.

Perinatal piglet mortality is an important factor in pig production from economic and animal welfare perspectives; however, the statistical analysis of mortality is difficult because of its categorical nature. Recent studies have suggested that a binomial model for the survival of each specific piglet with a logit approach is appropriate and that recursive relationships between traits are useful for taking into account non-genetic relationships with other traits. In this study, the recursive binomial model is expanded in two directions: (1) the recursive phenotypic dependence among traits is allowed to vary among groups of individuals or crosses, and (2) the binomial distribution is replaced by the multiplicative binomial distribution to account for over or underdispersion. In this study, five recursive multiplicative binomial models were used to obtain estimates of the Dickerson crossbreeding parameters in a diallel cross among three varieties of Iberian pigs [Entrepelado (EE), Torbiscal (TT), and Retinto (RR)]. Records (10,255) from 2110 sows were distributed as follows: EE (433 records, 100 sows), ER (2336, 527), ET (942, 177), RE (806, 196), RR (870, 175), RT (2450, 488), TE (193, 36), TR (1993, 359), and TT (232, 68). Average litter size [Total Number Born (TNB)] and number of stillborns (SB) were 8.46 ± 2.27 and 0.25 ± 0.72, respectively. The overdispersion was evident with all models. The model with the best fit included a linear recursive relationship between TNB and the logit of [Formula: see text] of the multiplicative binomial distribution, and it implies that piglet mortality increases with litter size. Estimates of direct effects showed small differences among populations. The analysis of maternal effects indicated that the dams whose mothers were EE had a larger SB, while dams with RR mothers reduced the probability of born dead. The posterior estimates of heterosis suggested a reduction in SB when the sow is crosbred. The multiplicative binomial distribution provides a useful alternative to the binomial distribution when there is overdispersion in the data. Recursive models can be used for modeling non-genetic relationships between traits, even if the phenotypic dependency between traits varies among environments or groups of individuals. Piglet perinatal mortality increased with TNB and is reduced by maternal heterosis.

Transmission ratio distortion (TRD) is defined as the allele transmission deviation from the heterozygous parent to the offspring from the expected Mendelian genotypic frequencies. Although TRD can be a confounding factor in genetic mapping studies, this phenomenon remains mostly unknown in pigs, particularly in traditional breeds (i.e., the Iberian pig). We aimed to describe the maternal TRD prevalence and its genomic distribution in two Iberian varieties. Genotypes from a total of 247 families (dam and offspring) of Entrepelado ( n = 129) and Retinto ( n = 118) Iberian varieties were analyzed. The offspring were sired by both ungenotyped purebred Retinto and Entrepelado Iberian boars, regardless of the dam variety used. After quality control, 16,246 single-nucleotide polymorphisms (SNPs) in the Entrepelado variety and 9744 SNPs in the Retinto variety were analyzed. Maternal TRD was evaluated by a likelihood ratio test under SNP-by-SNP, adapting a previous model solved by Bayesian inference. Results provided 68 maternal TRD loci (TRDLs) in the Entrepelado variety and 24 in the Retinto variety ( q < 0.05), with mostly negative TRD values, increasing the transmission of the minor allele. In addition, both varieties shared ten common TRDLs. No strong evidence of biological effects was found in genes with TRDLs. However, some biological processes could be affected by TRDLs, such as embryogenesis at different levels and lipid metabolism. These findings could provide useful insight into the genetic mechanisms to improve the swine industry, particularly in traditional breeds.

Meat quality has an important genetic component and can be modified by the fatty acid (FA) composition and the amount of fat contained in adipose tissue and muscle. The present study aimed to find genomic regions associated with the FA composition in backfat and muscle (longissimus dorsi) in 439 pigs with three different genetic backgrounds but having the Iberian breed in common. Genome-wide association studies (GWAS) were performed between 38,424 single-nucleotide polymorphisms (SNPs) covering the pig genome and 60 phenotypic traits related to backfat and muscle FA composition. Nine significant associated regions were found in backfat on the Sus scrofa chromosomes (SSC): SSC1, SSC2, SSC4, SSC6, SSC8, SSC10, SSC12, and SSC16. For the intramuscular fat, six significant associated regions were identified on SSC4, SSC13, SSC14, and SSC17. A total of 52 candidate genes were proposed to explain the variation in backfat and muscle FA composition traits. GWAS were also reanalysed including SNPs on five candidate genes (ELOVL6, ELOVL7, FADS2, FASN, and SCD). Regions and molecular markers described in our study may be useful for meat quality selection of commercial pig breeds, although several polymorphisms were breed-specific, and further analysis would be needed to evaluate possible causal mutations.

In binary image segmentation, the choice of the order of the operation sequence may yield to suboptimal results. In this work, we propose to tackle the associated optimization problem via multi-objective approach. Given the original image, in combination with a list of morphological, logical and stacking operations, the goal is to obtain the ideal output at the lowest computational cost. We compared the performance of two Multi-objective Evolutionary Algorithms (MOEAs): the Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). NSGA-II has better results in most cases, but the difference does not reach statistical significance. The results show that the similarity measure and the computational cost are objective functions in conflict, while the number of operations available and type of input images impact on the quality of Pareto set., (© 2020 The Authors.)

The aim of this study was to research the effect of the genetic background (Retinto, Torbiscal, and their reciprocal crosses) on the subcutaneous fatty acids and the sensory characteristics of dry-cured shoulders from Iberian pig, and also to investigate whether there is some interaction between genotype and diet composition when pigs are reared indoors, to obtain information to improve the selection strategies for purebred Iberian pig. The genetic background affected both the fatty acid composition (C17:0, C17:1 n-7, C18:3 n-3 and C20:0 were significantly different) and the sensory characteristics (marbling, lean fibrousness, and flavour intensity and persistence were significantly influenced), which indicates that they should be taken into account in the selection strategies for purebred Iberian pig. In a similar way, the genotype × diet composition interaction also should be taken into account when selecting a genetic line or cross to be fed indoors on a particular diet because of its repercussion on the sensory characteristics., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The Iberian pig is one of the pig breeds that has the highest meat quality. Traditionally, producers have bred one of the available varieties, exclusively, and have not used crosses between them, which has contrasted sharply with other populations of commercial pigs for which crossbreeding has been a standard procedure. The objective of this study was to perform an experiment under full diallel design among three contemporary commercial varieties of Iberian pig and estimate the additive genetic variation and the crossbreeding effects (direct, maternal and heterosis) for prolificacy. The data set comprised 18 193 records for total number born and number born alive from 3800 sows of three varieties of the Iberian breed (Retinto, Torbiscal and Entrepelado) and their reciprocal crosses (Retinto × Torbiscal, Torbiscal × Retinto, Retinto × Entrepelado, Entrepelado × Retinto, Torbiscal × Entrepelado and Entrepelado × Torbiscal), and a pedigree of 4609 individuals. The analysis was based on a multiple population repeatability model, and we developed a model comparison test that indicated the presence of direct line, maternal and heterosis effects. The results indicated the superiorities of the direct line effect of the Retinto and the maternal effect of the Entrepelado populations. All of the potential crosses produced significant heterosis, and additive genetic variation was higher in the Entrepelado than it was in the other two populations. The recommended cross for the highest yield in prolificacy is a Retinto father and an Entrepelado mother to generate a hybrid commercial sow.

Gene Networks (GN), have emerged as an useful tool in recent years for the analysis of different diseases in the field of biomedicine. In particular, GNs have been widely applied for the study and analysis of different types of cancer. In this context, Lung carcinoma is among the most common cancer types and its short life expectancy is partly due to late diagnosis. For this reason, lung cancer biomarkers that can be easily measured are highly demanded in biomedical research. In this work, we present an application of gene co-expression networks in the modelling of lung cancer gene regulatory networks, which ultimately served to the discovery of new biomarkers. For this, a robust GN inference was performed from microarray data concomitantly using three different co-expression measures. Results identified a major cluster of genes involved in SRP-dependent co-translational protein target to membrane, as well as a set of 28 genes that were exclusively found in networks generated from cancer samples. Amongst potential biomarkers, genes N C K A P 1 L and D M D are highlighted due to their implications in a considerable portion of lung and bronchus primary carcinomas. These findings demonstrate the potential of GN reconstruction in the rational prediction of biomarkers.

Individual-specific hidden inbreeding depression load (IDL) can be accounted for in livestock populations by appropriate best linear unbiased prediction approaches. This genetic effect has a recessive pattern and reveals when inherited in terms of identity-by-descent. Nevertheless, IDL inherits as a pure additive genetic background and can be selected using standard breeding values. The main target of this research was to evaluate IDL for litter size in 2 Iberian pig varieties (Entrepelado and Retinto) from a commercial breeding-stock. Analyses were performed on the total number of piglets born (both alive and dead) and used data from 3,200 (8.02 ± 0.04 piglets/litter) Entrepelado and 4,744 Retinto litters (8.40 ± 0.03 piglets/litter). Almost 50% of Entrepelado sows were inbred (1.7% to 25.0%), whereas this percentage reduced to 37.4% in the Retinto variety (0.2% to 25.0%). The analytical model was solved by Bayesian inference and accounted for 2 systematic effects (sow age and breed/variety of the artificial insemination boar), 2 permanent environmental effects (herd-year-season and sow), and 2 genetic effects (IDL and infinitesimal additive). In terms of posterior means (PM), additive genetic and IDL variances were similar in the Entrepelado variety (PM, 0.68 vs. 0.76 piglets2, respectively) and their 95% credibility intervals (95CI) overlapped, although without including zero (0.38 to 0.94 vs. 0.15 to 1.31 piglets2, respectively). The same pattern revealed in the Retinto variety, with IDL variance (PM, 0.41 piglets2; 95CI, 0.07 to 0.88 piglets2) slightly larger than the additive genetic variance (PM, 0.37 piglets2; 95CI, 0.16 to 0.59 piglets2). The relevance of IDL was also checked by a Bayes factor and the deviance information criterion, the model including this effect being clearly favored in both cases. Although the analysis assumed null genetic covariance between IDL and infinitesimal additive effects, a moderate negative correlation (-0.31) was suggested when plotting the PM of breeding values in the Entrepelado variety; a negative genetic trend for IDL was also revealed in this Iberian pig variety (-0.25 piglets for 100% inbred offspring of individuals born in 2014), whereas no trend was detected in Retinto breeding-stock. Those were the first estimates of IDL in a commercial livestock population, they giving evidence of a relevant genetic background with potential consequences on the reproductive performance of Iberian sows., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception. These problems can be caused by variations of the environment or by limitations of the cameras that capture the images. In this work we propose a method that improves the details of infrared images, increasing their entropy, preserving their natural appearance, and enhancing contrast. The proposed method extracts multiple features of brightness and darkness from the infrared image. This is done by means of the multiscale top-hat transform. To improve the infrared image, multiple scales are added to the bright areas and multiple areas of darkness are subtracted. The method was tested with 450 infrared thermal images from a public database. Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.

Background: Intramuscular fat (IMF) content and composition have a strong impact on the nutritional and organoleptic properties of porcine meat. The goal of the current work was to compare the patterns of gene expression and the genetic determinism of IMF traits in the porcine gluteus medius (GM) and longissimus dorsi (LD) muscles., Results: A comparative analysis of the mRNA expression profiles of the pig GM and LD muscles in 16 Duroc pigs with available microarray mRNA expression measurements revealed the existence of 106 differentially expressed probes (fold-change > 1.5 and q-value < 0.05). Amongst the genes displaying the most significant differential expression, several loci belonging to the Hox transcription factor family were either upregulated (HOXA9, HOXA10, HOXB6, HOXB7 and TBX1) or downregulated (ARX) in the GM muscle. Differences in the expression of genes with key roles in carbohydrate and lipid metabolism (e.g. FABP3, ORMDL1 and SLC37A1) were also detected. By performing a GWAS for IMF content and composition traits recorded in the LD and GM muscles of 350 Duroc pigs, we identified the existence of one region on SSC14 (110-114 Mb) displaying significant associations with C18:0, C18:1(n-7), saturated and unsaturated fatty acid contents in both GM and LD muscles. Moreover, we detected several genome-wide significant associations that were not consistently found in both muscles. Further studies should be performed to confirm whether these associations are muscle-specific. Finally, the performance of an eQTL scan for 74 genes, located within GM QTL regions and with available microarray measurements of gene expression, made possible to identify 14 cis-eQTL regulating the expression of 14 loci, and six of them were confirmed by RNA-Seq., Conclusions: We have detected significant differences in the mRNA expression patterns of the porcine LD and GM muscles, evidencing that the transcriptomic profile of the skeletal muscle tissue is affected by anatomical, metabolic and functional factors. A highly significant association with IMF composition on SSC14 was replicated in both muscles, highlighting the existence of a common genetic determinism, but we also observed the existence of a few associations whose magnitude and significance varied between LD and GM muscles.

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.

In the last few years, gene networks have become one of most important tools to model biological processes. Among other utilities, these networks visually show biological relationships between genes. However, due to the large amount of the currently generated genetic data, their size has grown to the point of being unmanageable. To solve this problem, it is possible to use computational approaches, such as heuristics-based methods, to analyze and optimize gene network's structure by pruning irrelevant relationships. In this paper we present a new method, called GeSOp, to optimize large gene network structures. The method is able to perform a considerably prune of the irrelevant relationships comprising the input network. To do so, the method is based on a greedy heuristic to obtain the most relevant subnetwork. The performance of our method was tested by means of two experiments on gene networks obtained from different organisms. The first experiment shows how GeSOp is able not only to carry out a significant reduction in the size of the network, but also to maintain the biological information ratio. In the second experiment, the ability to improve the biological indicators of the network is checked. Hence, the results presented show that GeSOp is a reliable method to optimize and improve the structure of large gene networks.

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0-3 Mb, for body weight, on SSC2, 3-9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC&#95;LD, seven in BC&#95;DU and six in BC&#95;PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.

Meat quality traits have an increasing importance in the pig industry because of their strong impact on consumer acceptance. Herewith, we have combined phenotypic and microarray expression data to map loci with potential effects on five meat quality traits recorded in the longissimus dorsi (LD) and gluteus medius (GM) muscles of 350 Duroc pigs, i.e. pH at 24 hours post-mortem (pH 24 ), electric conductivity (CE) and muscle redness (a*), lightness (L*) and yellowness (b*). We have found significant genome-wide associations for CE of LD on SSC4 (~104 Mb), SSC5 (~15 Mb) and SSC13 (~137 Mb), while several additional regions were significantly associated with meat quality traits at the chromosome-wide level. There was a low positional concordance between the associations found for LD and GM traits, a feature that reflects the existence of differences in the genetic determinism of meat quality phenotypes in these two muscles. The performance of an eQTL search for SNPs mapping to the regions associated with meat quality traits demonstrated that the GM a* SSC3 and pH 24 SSC17 QTL display positional concordance with cis-eQTL regulating the expression of several genes with a potential role on muscle metabolism.

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.

Prolificacy can directly impact porcine profitability, but large genetic variation and low heritability have been found regarding litter size among porcine breeds. To identify key differences in gene expression associated to swine reproductive efficiency, we performed a transcriptome analysis of sows' endometrium from an Iberian x Meishan F2 population at day 30-32 of gestation, classified according to their estimated breeding value (EBV) as high (H, EBV > 0) and low (L, EBV < 0) prolificacy phenotypes. For each sample, mRNA and small RNA libraries were RNA-sequenced, identifying 141 genes and 10 miRNAs differentially expressed between H and L groups. We selected four miRNAs based on their role in reproduction, and five genes displaying the highest differences and a positive mapping into known reproductive QTLs for RT-qPCR validation on the whole extreme population. Significant differences were validated for genes: PTGS2 (p = 0.03; H/L ratio = 3.50), PTHLH (p = 0.03; H/L ratio = 3.69), MMP8 (p = 0.01; H/L ratio =4.41) and SCNN1G (p = 0.04; H/L ratio = 3.42). Although selected miRNAs showed similar expression levels between H and L groups, significant correlation was found between the expression level of ssc-miR-133a (p < 0.01) and ssc-miR-92a (p < 0.01) and validated genes. These results provide a better understanding of the genetic architecture of prolificacy-related traits and embryo implantation failure in pigs.

Background: Linkage maps are essential tools for the study of several topics in genome biology. High density linkage maps for the porcine autosomes have been constructed exploiting the high density data provided by the PorcineSNP60 BeadChip. However, a high density SSCX linkage map has not been reported up to date. The aim of the current study was to build an accurate linkage map of SSCX to provide precise estimates of recombination rates along this chromosome and creating a new tool for QTL fine mapping., Results: A female-specific high density linkage map was built for SSCX using Sscrofa10.2 annotation. The total length of this chromosome was 84.61 cM; although the average recombination rate was 0.60 cM/Mb, both cold and hot recombination regions were identified. A Bayesian probabilistic to genetic groups and revealed that the animals used in the current study for linkage map construction were likely to be carriers of X chromosomes of European origin. Finally, the newly generated linkage map was used to fine-map a QTL at 16 cM for intramuscular fat content (IMF) measured on longissimus dorsi. The sulfatase isozyme S gene constitutes a functional and positional candidate gene underlying the QTL effect., Conclusions: The current study presents for the first time a high density linkage map for SSCX and supports the presence of cold and hot recombination intervals along this chromosome. The large cold recombination region in the central segment of the chromosome is not likely to be due to structural differences between X chromosomes of European and Asian origin. In addition, the newly generated linkage map has allowed us to fine-map a QTL on SSCX for fat deposition.

The adiponectin (ADIPOQ) locus is a positional and functional candidate gene for 2 porcine chromosome 13 (SSC13) QTL influencing cholesterol (CHOL) and low-density lipoprotein (LDL) concentrations in 190-d-old pigs. By sequencing 2.37 kb of the pig ADIPOQ cDNA, we have identified 1 c.*1512G>T 3' untranslated region polymorphism that has been genotyped in a Duroc pig commercial population with records for serum lipid levels at 45 and 190 d of age. Statistical analysis of the data have revealed significant associations between the ADIPOQ genotype and CHOL (P=0.0040) and LDL (P=0.0011) concentrations at 190 d but not at 45 d. In family 3, most of the SSC13 QTL effects on LDL levels at 190 d were explained by the ADIPOQ genotype. We also found an association with triglyceride levels at 45 d (P=0.0060) but not at 190 d. Measurement of allelic mRNA imbalance demonstrated that the G and T alleles are expressed at very similar levels in muscle and fat tissues, indicating that the c.*1512G>T polymorphism does not affect transcript abundance. As a whole, results obtained in the current work as well as previous data gathered in humans and pigs provide evidence that the magnitude of associations between blood lipid phenotypes and candidate loci genotypes may vary depending on the age of the individual, therefore suggesting the existence of dynamic genotype×environment interactions changing on a temporal scale.

An experiment of a 2×2 full diallelic cross between two contemporary Iberian pig strains (Retinto: RR, and Torbiscal: TT) was conducted to estimate the crossbreeding effects for growth and carcass traits. Phenotypic records were obtained under intensive management and consisted of two different data sets. The first set comprised growth traits until weaning and was collected at two different farms (6236 and 1208 records, respectively). Specific data included individual piglet weight at birth and at weaning at 28 days and average daily gain from birth to weaning at 28 days (ADG28) for both RR and TT and their reciprocal crosses. The second set comprised growth data from birth to slaughter (~340 days and ~160 kg) and carcass traits from 349 individuals (randomly) sampled at weaning from the first dataset. Data were analyzed through a Bayesian analysis by using a reparameterization of Dickerson's model that allowed estimation of the posterior distributions of the following crossbreeding effects: average maternal breed effect (gM), average paternal breed effect (gP) and individual heterosis (hI). Results showed that the relative magnitude of crossbreeding effects depends on the trait analyzed. Crosses where Torbiscal strain was used as mother (RT and TT) achieved the greatest performance for all growth traits at weaning, leading to remarkable gM effects. The most outstanding example is the case of ADG28 where the probability of relevance was one. In contrast, TR cross showed the greatest differences from RR cross for all growth at slaughter and carcass traits. These differences were mainly due to hI and gP crossbreeding parameters. In particular, the posterior mean of hI was more noticeable for live weight at slaughter, average daily gain at slaughter and carcass length, while gP was more relevant for hams (kg) and loins (kg) representing from 3% to10% of average performance of traits. Hence, growth traits at weaning did not reveal any notable advantage of the crossbreeding scheme because of the superiority of the Torbiscal strain with respect to its mothering ability and the small hI. However, results from growth and carcass traits at slaughter would support the implementation of a TR crossbred system. It would allow exploitation of both the gP of the Torbiscal strain and the hI between these two Iberian pig strains. Additionally, gP estimates and phenotypic differences between reciprocal crosses might suggest signs of the presence of paternal genetic imprinting in primal cuts traits.

Background: Fatty acids (FA) play a critical role in energy homeostasis and metabolic diseases; in the context of livestock species, their profile also impacts on meat quality for healthy human consumption. Molecular pathways controlling lipid metabolism are highly interconnected and are not fully understood. Elucidating these molecular processes will aid technological development towards improvement of pork meat quality and increased knowledge of FA metabolism, underpinning metabolic diseases in humans., Results: The results from genome-wide association studies (GWAS) across 15 phenotypes were subjected to an Association Weight Matrix (AWM) approach to predict a network of 1,096 genes related to intramuscular FA composition in pigs. To identify the key regulators of FA metabolism, we focused on the minimal set of transcription factors (TF) that the explored the majority of the network topology. Pathway and network analyses pointed towards a trio of TF as key regulators of FA metabolism: NCOA2, FHL2 and EP300. Promoter sequence analyses confirmed that these TF have binding sites for some well-know regulators of lipid and carbohydrate metabolism. For the first time in a non-model species, some of the co-associations observed at the genetic level were validated through co-expression at the transcriptomic level based on real-time PCR of 40 genes in adipose tissue, and a further 55 genes in liver. In particular, liver expression of NCOA2 and EP300 differed between pig breeds (Iberian and Landrace) extreme in terms of fat deposition. Highly clustered co-expression networks in both liver and adipose tissues were observed. EP300 and NCOA2 showed centrality parameters above average in the both networks. Over all genes, co-expression analyses confirmed 28.9% of the AWM predicted gene-gene interactions in liver and 33.0% in adipose tissue. The magnitude of this validation varied across genes, with up to 60.8% of the connections of NCOA2 in adipose tissue being validated via co-expression., Conclusions: Our results recapitulate the known transcriptional regulation of FA metabolism, predict gene interactions that can be experimentally validated, and suggest that genetic variants mapped to EP300, FHL2, and NCOA2 modulate lipid metabolism and control energy homeostasis in pigs.

Previous studies on Iberian × Landrace (IBMAP) pig intercrosses have enabled the identification of several quantitative trait locus (QTL) regions related to growth and fatness traits; however, the genetic variation underlying those QTLs are still unknown. These traits are not only relevant because of their impact on economically important production traits, but also because pig constitutes a widely studied animal model for human obesity and obesity-related diseases. The hypothalamus is the main gland regulating growth, food intake, and fat accumulation. Therefore, the aim of this work was to identify genes and/or gene transcripts involved in the determination of growth and fatness in pig by a comparison of the whole hypothalamic transcriptome (RNA-Seq) in two groups of phenotypically divergent IBMAP pigs. Around 16,000 of the ∼25.010 annotated genes were expressed in these hypothalamic samples, with most of them showing intermediate expression levels. Functional analyses supported the key role of the hypothalamus in the regulation of growth, fat accumulation, and energy expenditure. Moreover, 58,927 potentially new isoforms were detected. More than 250 differentially expressed genes and novel transcript isoforms were identified between the two groups of pigs. Twenty-one DE genes/transcripts that colocalized in previously identified QTL regions and/or whose biological functions are related to the traits of interest were explored in more detail. Additionally, the transcription factors potentially regulating these genes and the subjacent networks and pathways were also analyzed. This study allows us to propose strong candidate genes for growth and fatness based on expression patterns, genomic location, and network interactions.

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., (© 2013 The Authors, Animal Genetics © 2013 Stichting International Foundation for Animal Genetics.)

The leptin (LEP) and its receptor (LEPR) regulate food intake and energy balance through hypothalamic signaling. However, the LEP-LEPR axis seems to be more complex and its expression regulation has not been well described. In pigs, LEP and LEPR genes have been widely studied due to their relevance. Previous studies reported significant effects of SNPs located in both genes on growth and fatness traits. The aim of this study was to determine the expression profiles of LEP and LEPR across hypothalamic, adipose, hepatic and muscle tissues in Iberian x Landrace backcrossed pigs and to analyze the effects of gene variants on transcript abundance. To our knowledge, non porcine LEPR isoforms have been described rather than LEPRb. A short porcine LEPR isoform (LEPRa), that encodes a protein lacking the intracellular residues responsible of signal transduction, has been identified for the first time. The LEPRb isoform was only quantifiable in hypothalamus while LEPRa appeared widely expressed across tissues, but at higher levels in liver, suggesting that both isoforms would develop different roles. The unique LEP transcript showed expression in backfat and muscle. The effects of gene variants on transcript expression revealed interesting results. The LEPRc.1987C>T polymorphism showed opposite effects on LEPRb and LEPRa hypothalamic expression. In addition, one out of the 16 polymorphisms identified in the LEPR promoter region revealed high differential expression in hepatic LEPRa. These results suggest a LEPR isoform-specific regulation at tissue level. Conversely, non-differential expression of LEP conditional on the analyzed polymorphisms could be detected, indicating that its regulation is likely affected by other mechanisms rather than gene sequence variants. The present study has allowed a transcriptional characterization of LEP and LEPR isoforms on a range of tissues. Their expression patterns seem to indicate that both molecules develop peripheral roles apart from their known hypothalamic signal transduction function.

Background: Reproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages., Results: The gene expression stability of ten potential reference genes was studied by three different methods (geNorm, NormFinder and BestKeeper) in ovary and uterus collected at five different physiological time points (heat, and 15, 30, 45 and 60 days of pregnancy). Although final ranking differed, the three algorithms gave very similar results. Thus, the most stable genes across time were TBP and UBC in uterus and TBP and HPRT1 in ovary, while HMBS and ACTB showed the less stable expression in uterus and ovary, respectively. When studied as a systematic effect, the reproductive stage did not significantly affect the expression of the candidate reference genes except at 30d and 60d of pregnancy, when a general drop in expression was observed in ovary., Conclusions: Based in our results, we propose the use of TBP, UBC and SDHA in uterus and TBP, GNB2L1 and HPRT1 in ovary for normalization of longitudinal expression studies using quantitative PCR in sows.

Differential gene expression analyses typically focus on departures across mathematical expectations (i.e. mean) from two or more groups of microarrays, without considering alternative patterns of departure. Nevertheless, recent studies in humans and great apes have suggested that differential gene expression could also be characterized in terms of heterogeneous dispersion patterns. This must be viewed as a very interesting genetic phenomenon clearly linked to the regulation mechanisms of gene transcription. Unfortunately, we completely lack information about the incidence and relevance of dispersion-specific differential gene expression in livestock species, although a specific Bayes factor (BF) for testing this kind of differential gene expression (i.e. within-probe heteroskedasticity) has been recently developed. Within this context, our main objective was to characterize the incidence of dispersion-specific differential gene expression in pigs and, if possible, providing the first evidence of this phenomenon in a livestock species. We evaluated dispersion-specific differential gene expression on ovary, uterus and hypophysis samples from 22 F2 Iberian × Meishan sows, where a total of 15,252 probes were interrogated. For each tissue, heteroskedasticity of probe-specific residual variances was evaluated by three pairwise comparisons involving three physiological stages, that is, heat, 15 days of pregnancy and 45 days of pregnancy. Between 2.9% and 37.4% of the analyzed probes provided statistical evidence of within-tissue across-physiological stages dispersion-specific differential gene expression (BF >1), and between 0.1% and 3.0% of them reported decisive evidence (BF >100). It is important to highlight that <8% of the heteroskedastic probes were also linked to differential gene expression in terms of departures among the probe-specific mathematical expectation of each physiological stage. This discarded the disturbance of scale effects in a high percentage of probes and suggested that probe-specific heteroskedasticity must be viewed as an independent phenomenon within the context of differential gene expression. As a whole, our results report a remarkable incidence of dispersion-specific differential gene expression across the whole genome of the pig, establishing a very interesting starting point for further studies focused on deciphering the genetic mechanisms underlying heteroskedasticity.

Background: The ELOVL fatty acid elongase 6 (ELOVL6), the only elongase related to de novo lipogenesis, catalyzes the rate-limiting step in the elongation cycle by controlling the fatty acid balance in mammals. It is located on pig chromosome 8 (SSC8) in a region where a QTL affecting palmitic, and palmitoleic acid composition was previously detected, using an Iberian x Landrace intercross. The main goal of this work was to fine-map the QTL and to evaluate the ELOVL6 gene as a positional candidate gene affecting the percentages of palmitic and palmitoleic fatty acids in pigs., Methodology and Principal Findings: The combination of a haplotype-based approach and single-marker analysis allowed us to identify the main, associated interval for the QTL, in which the ELOVL6 gene was identified and selected as a positional candidate gene. A polymorphism in the promoter region of ELOVL6, ELOVL6:c.-533C>T, was highly associated with the percentage of palmitic and palmitoleic acids in muscle and backfat. Significant differences in ELOVL6 gene expression were observed in backfat when animals were classified by the ELOVL6:c.-533C>T genotype. Accordingly, animals carrying the allele associated with a decrease in ELOVL6 gene expression presented an increase in C16:0 and C16:1(n-7) fatty acid content and a decrease of elongation activity ratios in muscle and backfat. Furthermore, a SNP genome-wide association study with ELOVL6 relative expression levels in backfat showed the strongest effect on the SSC8 region in which the ELOVL6 gene is located. Finally, different potential genomic regions associated with ELOVL6 gene expression were also identified by GWAS in liver and muscle, suggesting a differential tissue regulation of the ELOVL6 gene., Conclusions and Significance: Our results suggest ELOVL6 as a potential causal gene for the QTL analyzed and, subsequently, for controlling the overall balance of fatty acid composition in pigs.

We performed a whole-genome scan with 110 informative microsatellites in a commercial Duroc population for which growth, fatness, carcass and meat quality phenotypes were available. Importantly, meat quality traits were recorded in two different muscles, that is, gluteus medius (GM) and longissimus thoracis et lumborum (LTL), to find out whether these traits are determined by muscle-specific genetic factors. At the whole-population level, three genome-wide QTL were identified for carcass weight (SSC7, 60 cM), meat redness (SSC13, 84 cM) and yellowness (SSC15, 108 cM). Within-family analyses allowed us to detect genome-wide significant QTL for muscle loin depth between the 3rd and 4th ribs (SSC15, 54 cM), backfat thickness (BFT) in vivo (SSC10, 58 cM), ham weight (SSC9, 69 cM), carcass weight (SSC7, 60 cM; SSC9, 68 cM), BFT on the last rib (SSC11, 48 cM) and GM redness (SSC8, 85 cM; SSC13, 84 cM). Interestingly, there was low positional concordance between meat quality QTL maps obtained for GM and LTL. As a matter of fact, the three genome-wide significant QTL for colour traits (SSC8, SSC13 and SSC15) that we detected in our study were all GM specific. This result suggests that QTL effects might be modulated to a certain extent by genetic and environmental factors linked to muscle function and anatomical location., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

The lipid content and fatty acid (FA) profile have an important impact in human health as well as in the technological transformation and nutritional and organoleptic quality of meat. A genome-wide association study (GWAS) on 144 backcross pigs (25% Iberian × 75% Landrace) was performed for 32 traits associated with intramuscular FA composition and indices of FA metabolism. The GWAS was carried out using Qxpak 5.0 and the genotyping information obtained from the Porcine SNP60K BeadChip (Illumina Inc., San Diego, CA). Signals of significant association considering a false- discovery rate (q-value < 0.05) were observed in 15 of the 32 analyzed traits, and a total of 813 trait-associated SNP (TAS), distributed in 43 chromosomal intervals on almost all autosomes, were annotated. According to the clustering analysis based on functional classification, several of the annotated genes are related to FA composition and lipid metabolism. Some interesting positional concordances among TAS and previously reported QTL for FA compositions and/or other lipid traits were also found. These common genomic regions for different traits suggest pleiotropic effects for FA composition and were found primarily on SSC4, SSC8, and SSC16. These results contribute to our understanding of the complex genetic basis of FA composition and FA metabolism.

Background: The traditional strategy to map QTL is to use linkage analysis employing a limited number of markers. These analyses report wide QTL confidence intervals, making very difficult to identify the gene and polymorphisms underlying the QTL effects. The arrival of genome-wide panels of SNPs makes available thousands of markers increasing the information content and therefore the likelihood of detecting and fine mapping QTL regions. The aims of the current study are to confirm previous QTL regions for growth and body composition traits in different generations of an Iberian x Landrace intercross (IBMAP) and especially identify new ones with narrow confidence intervals by employing the PorcineSNP60 BeadChip in linkage analyses., Results: Three generations (F3, Backcross 1 and Backcross 2) of the IBMAP and their related animals were genotyped with PorcineSNP60 BeadChip. A total of 8,417 SNPs equidistantly distributed across autosomes were selected after filtering by quality, position and frequency to perform the QTL scan. The joint and separate analyses of the different IBMAP generations allowed confirming QTL regions previously identified in chromosomes 4 and 6 as well as new ones mainly for backfat thickness in chromosomes 4, 5, 11, 14 and 17 and shoulder weight in chromosomes 1, 2, 9 and 13; and many other to the chromosome-wide signification level. In addition, most of the detected QTLs displayed narrow confidence intervals, making easier the selection of positional candidate genes., Conclusions: The use of higher density of markers has allowed to confirm results obtained in previous QTL scans carried out with microsatellites. Moreover several new QTL regions have been now identified in regions probably not covered by markers in previous scans, most of these QTLs displayed narrow confidence intervals. Finally, prominent putative biological and positional candidate genes underlying those QTL effects are listed based on recent porcine genome annotation.

Fatty acid composition is a critical aspect of pork because it affects sensorial and technological aspects of meat quality and it is relevant for human health. Previous studies identified significant QTLs in porcine chromosome 12 for fatty acid profile of back fat (BF) and intramuscular fat (IMF). In the present study, 374 SNPs mapped in SSC12 from the 60K Porcine SNP Beadchip were used. We have combined linkage and association analyses with expression data analysis in order to identify regions of SSC12 that could affect fatty acid composition of IMF in longissimus muscle. The QTL scan showed a region around the 60-cM position that significantly affects palmitic fatty acid and two related fatty acid indexes. The Iberian QTL allele increased the palmitic content (+2.6% of mean trait). This QTL does not match any of those reported in the previous study on fatty acid composition of BF, suggesting different genetic control acting at both tissues. The SNP association analyses showed significant associations with linolenic and palmitic acids besides several indexes. Among the polymorphisms that affect palmitic fatty acid and match the QTL region at 60 cM, there were three that mapped in the Phosphatidylcholine transfer protein (PCTP) gene and one in the Acetyl-CoA Carboxylase ∝ gene (ACACA). Interestingly one of the PCTP SNPs also affected significantly unsaturated and double bound indexes and the ratio between polyunsaturated/monounsaturated fatty acids. Differential expression was assessed on longissimus muscle conditional on the genotype of the QTL and on the most significant SNPs, according to the results obtained in the former analyses. Results from the microarray expression analyses, validated by RT-qPCR, showed that PCTP expression levels significantly vary depending on the QTL as well as on the own PCTP genotype. The results obtained with the different approaches point out the PCTP gene as a powerful candidate underlying the QTL for palmitic content.

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.

Background: Reproductive traits, such as prolificacy, are of great interest to the pig industry. Better understanding of their genetic architecture should help to increase the efficiency of pig productivity through the implementation of marker assisted selection (MAS) programmes., Results: The Mucin 4 (MUC4) gene has been evaluated as a candidate gene for a prolificacy QTL described in an Iberian × Meishan (Ib × Me) F2 intercross. For association analyses, two previously described SNPs (DQ124298:g.243A>G and DQ124298:g.344A>G) were genotyped in 347 pigs from the Ib × Me population. QTL for the number of piglets born alive (NBA) and for the total number of piglets born (TNB) were confirmed on SSC13 at positions 44 cM and 51 cM, respectively. The MUC4 gene was successfully located within the confidence intervals of both QTL. Only DQ124298:g.344A>G MUC4 polymorphism was significantly associated with both NBA and TNB (P-value < 0.05) with favourable effects coming from the Meishan origin. MUC4 expression level was determined in F2 sows displaying extreme phenotypes for the number of embryos (NE) at 30-32 days of gestation. Differences in the uterine expression of MUC4 were found between high (NE ≥ 13) and low (NE ≤ 11) prolificacy sows. Overall, MUC4 expression in high prolificacy sows was almost two-fold increased compared with low prolificacy sows., Conclusions: Our data suggest that MUC4 could play an important role in the establishment of an optimal uterine environment that would increase embryonic survival during pig gestation.

Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits., (© 2011 Blackwell Verlag GmbH.)

Teat number is an important trait in sows that should accompany the increase in litter size that has been achieved in the last decades through selection. We have previously identified a genome-wide significant QTL for teat number in porcine chromosome SSC5 by means of an experimental Meishan by Iberian F(2) intercross population. In the present report, we have studied the porcine parathyroid hormone-like hormone (PTHLH) gene, which maps to SSC5, as a candidate gene for this trait, as PTHLH is involved in nipple formation during embryogenesis and nipple development during pregnancy and lactation. We have found that porcine PTHLH gene is transcribed into three mRNA species differing in the 5'UTR region. Two of these variants are reported in pigs here for the first time: one was similar to variant 1 described in humans while the other, which was generated by the retention of two small introns, has not been identified before in any other species. In addition, mRNA expression profile for two of the mRNA variants was assessed in 19 pig tissues. Porcine PTHLH showed a widespread expression as it was present in all tested tissues and relative expression of each variant was tissue dependent. Finally, we have performed an association study between a non-synonymous mutation in the coding region of this gene and sow teat number. The PTHLH polymorphism was segregating in our Meishan by Iberian F(2) population at intermediate allelic frequencies. We compared here six different statistical models to choose the one with a better fit and a lower degree of complexity. However, despite the potential negative effect of the PTHLH mutation in the signal peptide of this protein, we did not detect any association between the PTHLH genotype and the sow teat number phenotype, concluding that the causal mutation of the observed QTL is very likely not related to this gene., (© 2011 Blackwell Verlag GmbH.)

Intramuscular fat (IMF) storage is a biological process with a strong impact on nutritional and technological properties of meat and also with relevant consequences on human health. The genetic architecture of IMF content and composition phenotypes has been thoroughly studied in pigs through the identification of QTL and the estimation of genetic parameters. A question that has not been elucidated yet is if the genetic determinants of IMF-related phenotypes are muscle specific or, conversely, have broad effects on the whole skeletal muscle compartment. We have addressed this question by generating lipid QTL maps for 2 muscles with a high commercial value, gluteus medius (GM) and longissimus thoracis et lumborum (LTL), in a Duroc commercial population (n = 350). Our data support a lack of concordance between the GM and LTL QTL maps, suggesting that the effects of polymorphisms influencing IMF, cholesterol, and fatty acid contents are modulated to some extent by complex spatial factors related to muscle location, metabolism, and function. These results have important implications on the implementation of genomic selection schemes aimed to improve the lipid profile of swine meat.

A considerable number of fatness QTL have been identified in growing pigs, but there is a lack of knowledge about the genetic architecture of this trait in gilts and sows. We have performed a genome scan, in 255 Iberian × Meishan F(2) sows, for backfat thickness (BF) at 150 (BF(150) ) and 210 (BF(210)) days of age, 30 days after conception (BF(30)) and 7-10 days before farrowing (BF(bf)). We have found one BF150 QTL in SSC6 (120 cM) that was highly significant (P < 0.001) at the chromosome-wide level and suggestive at the genome-wide level (P < 0.1). Ten additional chromosome-wide significant QTL were found for sow BF(150) (SSC1, SSC13), BF(210) (SSC6, SSC8, SSC15), BF(30) (SSC5, SSC6) and BF(bf) (SSC1, SSC6, SSC13). The location of several of the BF QTL varied depending on the growing and reproductive status of the sow, suggesting that part of these genetic effects may have a temporal pattern of phenotypic expression., (© 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.)

The aim of the present study was to identify polymorphisms and to analyze endometrial gene expression of the porcine SSC13 ITIH cluster that could explain differences in prolificacy of 255 F(2) sows derived from an Iberian (Ib)×Meishan (Me) intercross in which QTL for the number of piglets born alive (NBA) and total number of piglets born (TNB) were previously detected on this chromosome. Sequencing of ITIH-1, -3, and -4 mRNAs was done and several polymorphisms segregating within the Ib×Me population were found in all three genes. Significant associations with NBA were found for two SNPs from ITIH-1, four from ITIH-3, and four SNPs from ITIH-4 (p<0.05). Haplotypes for the significant SNPs were calculated by segregation analysis and a marker assisted association test indicated that the alleles coming from the Meishan breed had a favorable effect on NBA for all three genes. Interestingly, some of the significant SNPs were located within the von Willebrand domain of the ITIH proteins, the binding site of molecules essential for the synthesis of the extracellular matrix during cumulus expansion. Gene expression analyses also revealed differences in the expression level of the ITIH-3 gene regarding the prolificacy performance (high or low) and the uterus sample (apical or basal)., (Copyright © 2011 Elsevier B.V. All rights reserved.)