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A Coruña, Spain

Gonzalez-Recio O.,INIA | Forni S.,Genus plc
Genetics Selection Evolution | Year: 2011

Background: Genomic selection has gained much attention and the main goal is to increase the predictive accuracy and the genetic gain in livestock using dense marker information. Most methods dealing with the large p (number of covariates) small n (number of observations) problem have dealt only with continuous traits, but there are many important traits in livestock that are recorded in a discrete fashion (e.g. pregnancy outcome, disease resistance). It is necessary to evaluate alternatives to analyze discrete traits in a genome-wide prediction context. Methods. This study shows two threshold versions of Bayesian regressions (Bayes A and Bayesian LASSO) and two machine learning algorithms (boosting and random forest) to analyze discrete traits in a genome-wide prediction context. These methods were evaluated using simulated and field data to predict yet-to-be observed records. Performances were compared based on the models' predictive ability. Results: The simulation showed that machine learning had some advantages over Bayesian regressions when a small number of QTL regulated the trait under pure additivity. However, differences were small and disappeared with a large number of QTL. Bayesian threshold LASSO and boosting achieved the highest accuracies, whereas Random Forest presented the highest classification performance. Random Forest was the most consistent method in detecting resistant and susceptible animals, phi correlation was up to 81% greater than Bayesian regressions. Random Forest outperformed other methods in correctly classifying resistant and susceptible animals in the two pure swine lines evaluated. Boosting and Bayes A were more accurate with crossbred data. Conclusions: The results of this study suggest that the best method for genome-wide prediction may depend on the genetic basis of the population analyzed. All methods were less accurate at correctly classifying intermediate animals than extreme animals. Among the different alternatives proposed to analyze discrete traits, machine-learning showed some advantages over Bayesian regressions. Boosting with a pseudo Huber loss function showed high accuracy, whereas Random Forest produced more consistent results and an interesting predictive ability. Nonetheless, the best method may be case-dependent and a initial evaluation of different methods is recommended to deal with a particular problem. © 2011 González-Recio and Forni; licensee BioMed Central Ltd.

BACKGROUND: The aim of this work was to study the effects on litter size of variants of the porcine genes RBP4, ESR1 and IGF2, currently used in genetic tests for different purposes. Moreover, we investigated a possible effect of the interaction between RBP4-MspI and ESR1-PvuII polymorphisms. The IGF2-intron3-G3072A polymorphism is actually used to select lean growth, but other possible effects of this polymorphism on reproductive traits need to be evaluated. METHODS: Detection of polymorphisms in the genomic and cDNA sequences of RBP4 gene was carried out. RBP4-MspI and IGF2-intron3-G3072A were genotyped in a hyperprolific Chinese-European line (Tai-Zumu) and three new RBP4 polymorphisms were genotyped in different pig breeds. A bivariate animal model was implemented in association analyses considering the number of piglets born alive at early (NBA12) and later parities (NBA3+ ) as different traits. A joint analysis of RBP4-MspI and ESR1-PvuII was performed to test their possible interaction. In the IGF2 analysis, paternal or maternal imprinting effects were also considered. RESULTS: Four different RBP4 haplotypes were detected (TGAC, GGAG, GAAG and GATG) in different pig breeds and wild boars. A significant interaction effect between RBP4-MspI and ESR1-PvuII polymorphisms of 0.61 +/- 0.29 piglets was detected on NBA3+. The IGF2 analysis revealed a significant increase on NBA3+ of 0.74 +/- 0.37 piglets for the paternally inherited allele A. CONCLUSIONS: All the analyzed pig and wild boar populations shared one of the four detected RBP4 haplotypes. This suggests an ancestral origin of the quoted haplotype. The joint use of RBP4-MspI and ESR1-PvuII polymorphisms could be implemented to select for higher prolificacy in the Tai-Zumu line. In this population, the paternal allele IGF2-intron3-3072A increased litter size from the third parity. The non-additive effects on litter size reported here should be tested before implementation in other pig breeding schemes.

Rodriguez Martin J.A.,INIA | Ramos-Miras J.J.,University of Almeria | Boluda R.,University of Valencia | Gil C.,University of Almeria
Geoderma | Year: 2013

This study characterises and compares Cr, Ni, Pb, Cu, Zn and Cd (HMs) contents and the main edaphic parameters in arable soils (AS) from western areas of the Andalusian Autonomous Community (SE Spain) with greenhouse soils (GS) from the province of Almería, one of the most productive agricultural systems in Europe. We explored 199 GS and 142 AS, representing local and regional scales of variation in this important Mediterranean area. The hazardousness of HMs was particularly relevant in GS where agricultural practices, which centre on maximising production, end up with products that finally enter the human food chain directly. Despite their similar edaphic characteristics, the main differences between AS and GS were nutrients and HM contents such as P, K, Cd, Pb and Zn, suggesting the widespread use of agrochemicals in greenhouse farming. Cd concentration in GS tripled that in AS. Here, we conclude that despite anthropogenic HM input, the association patterns of these elements were similar on the two spatial variability scales. Cd, Pb and Zn contents, and partly those of Cu, were related with agricultural practices. On the short spatial scale, grouping these HMs gave very high contents in GS. The associations found with Cr and Ni suggest a lithogenic influence combined with a paedogenic effect on spatial maps; this natural origin input becomes more marked on the long spatial scale represented by AS, where the main Cr and Ni contents were found in the vicinity of Mountain areas not influenced by human activities. © 2013 Elsevier B.V.

Santiago-Moreno J.,INIA
Society of Reproduction and Fertility supplement | Year: 2010

Despite apparent progress in reproductive technology as applied to wild ruminants, the success achieved in terms of the number of offspring that become healthy adults has remained low. Difficulties often arise through a lack of knowledge regarding appropriate cryopreservation techniques, and indeed through a lack of detailed information on the reproductive physiology of the species in question. The Spanish ibex (Capra pyrenaica) is a wild caprid found exclusively in the mountains of Iberia; only two of the original four subspecies still exist. Great efforts need to be made to preserve this species. The endocrine and environmental mechanisms that control its seasonal reproduction need to be properly understood, reproductive technologies (particularly the cryopreservation of gametes) optimised, and genetic resource banks developed. The experience obtained with the Spanish ibex may be useful in ex situ conservation strategies designed to preserve other threatened Mediterranean wild ruminants.

High-resolution gas chromatography/mass spectrometry (HRGC/MS) is the standard method for analysing dioxin, furan and polybrominated retardants in hazardous waste. Determination of dioxin-like compounds using in vitro bioassays such as ethoxyresorufin-O-deethylase (EROD) is an important tool to evaluate their Ah receptor-mediated toxic effects, because it detects all arylhydrocarbon receptor ligands in a variety of sample matrices. In the present work, we compared RTG-2 cell line EROD bioassay with HRGC/MS for assessing waste samples (liquid and solid) contaminated with polychlorinated dibenzo-p-dioxins and dibenzofurans, polychlorinated biphenyls (dioxin-like PCBs) and other xenobiotics. For liquid samples, HRGC/MS-toxic equivalent (HRGC/MS-TEQ) values ranged from 273.26 to 5.84 ng TEQ l(-1) and correlated well (correlation coefficient 0.99) with values obtained by EROD-TEQ, which ranged from 128 to 2.5 ng TEQ l(-1). For solid samples, HRGC/MS-TEQ values ranged from 3.44 to 0.49 ng TEQ g(-1) and correlated less well than liquid samples (correlation coefficient 0.64) with values obtained by EROD-TEQ ranging from 2.27 to 0.93 ng TEQ g(-1). The overestimation of RTG-2 EROD-TEQ (1.2 +/- 0.92 of values established by HRGC/MS) and the absence of false-negative results may limit analytical costs by eliminating the need for follow-up GC/MS analysis on the negative samples. We suggest that RTG-2 EROD bioassay is an inexpensive means for preliminary dioxin and furan positive screenings of waste samples. (c) 2010 John Wiley & Sons, Ltd.

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