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Background: There is a growing interest in uncovering the factors that shape microbiome composition due to its association with complex phenotypic traits in livestock. Host genetic variation is increasingly recognized as a major factor influencing the microbiome. The Iberian pig breed, known for its high-quality meat products, includes various strains with recognized genetic and phenotypic variability. However, despite the microbiome's known impact on pigs' productive phenotypes such as meat quality traits, comparative analyses of gut microbial composition across Iberian pig strains are lacking. This study aims to explore the gut microbiota of two Iberian pig strains, Entrepelado (n = 74) and Retinto (n = 63), and their reciprocal crosses (n = 100), using machine learning (ML) models to identify key microbial taxa relevant for distinguishing their genetic backgrounds, which holds potential application in the pig industry. Nine ML algorithms, including tree-based, kernel-based, probabilistic, and linear algorithms, were used. Results: Beta diversity analysis on 16 S rRNA microbiome data revealed compositional divergence among genetic, age and batch groups. ML models exploring maternal, paternal and heterosis effects showed varying levels of classification performance, with the paternal effect scenario being the best, achieving a mean Area Under the ROC curve (AUROC) of 0.74 using the Catboost (CB) algorithm. However, the most genetically distant animals, the purebreds, were more easily discriminated using the ML models. The classification of the two Iberian strains reached the highest mean AUROC of 0.83 using Support Vector Machine (SVM) model. The most relevant genera in this classification performance were Acetitomaculum, Butyricicoccus and Limosilactobacillus. All of which exhibited a relevant differential abundance between purebred animals using a Bayesian linear model. Conclusions: The study confirms variations in gut microbiota among Iberian pig strains and their crosses, influenced by genetic and non-genetic factors. ML models, particularly CB and RF, as well as SVM in certain scenarios, combined with a feature selection process, effectively classified genetic groups based on microbiome data and identified key microbial taxa. These taxa were linked to short-chain fatty acids production and lipid metabolism, suggesting microbial composition differences may contribute to variations in fat-related traits among Iberian genetic groups. [ABSTRACT FROM AUTHOR]

Background: The magnitude of inbreeding depression depends on the recessive burden of the individual, which can be traced back to the hidden (recessive) inbreeding load among ancestors. However, these ancestors carry different alleles at potentially deleterious loci and therefore there is individual variability of this inbreeding load. Estimation of the additive genetic value for inbreeding load is possible using a decomposition of inbreeding in partial inbreeding components due to ancestors. Both the magnitude of variation in partial inbreeding components and the additive genetic variance of inbreeding loads are largely unknown. Our study had three objectives. First, based on substitution effect under non-random matings, we showed analytically that inbreeding load of an ancestor can be expressed as an additive genetic effect. Second, we analysed the structure of individual inbreeding by examining the contributions of specific ancestors/founders using the concept of partial inbreeding coefficients in three French dairy sheep populations (Basco-Béarnaise, Manech Tête Noire and Manech Tête Rousse). Third, we included these coefficients in a mixed model as random regression covariates, to predict genetic variance and breeding values of the inbreeding load for milk yield in the same breeds. Results: Pedigrees included 190,276, 166,028 and 633,655 animals of Basco-Béarnaise, Manech Tête Noire and Manech Tête Rousse, respectively, born between 1985 and 2021. A fraction of 99.1% of the partial inbreeding coefficients were lower than 0.01 in all breeds, meaning that in practice inbreeding occurs in pedigree loops that span several generations backwards. Less than 5% ancestors generate inbreeding, because mating is essentially between unrelated individuals. Inbreeding load estimations involved 658,731, 541,180 and 2,168,454 records of yearly milk yield from 178,123, 151,863 and 596,586 females in Basco-Béarnaise, Manech Tête Noire and Manech Tête Rousse, respectively. Adding the inbreeding load effect to the model improved the fitting (values of the statistic Likelihood Ratio Test between 132 and 383) for milk yield in the three breeds. The inbreeding load variances were equal to 11,804 and 9435 L squared of milk yield for a fully inbred (100%) descendant in Manech Tête Noire and Manech Tête Rousse. In Basco-Béarnaise, the estimate of the inbreeding load variance (11,804) was not significantly different from zero. The correlations between (direct effect) additive genetic and inbreeding load effects were − 0.09, − 0.08 and − 0.12 in Basco-Béarnaise, Manech Tête Noire and Manech Tête Rousse. Conclusions: The decomposition of inbreeding in partial coefficients in these populations shows that inbreeding is mostly due to several small contributions of ancestors (lower than 0.001) going back several generations (5 to 7 generations), which is according to the policy of avoiding close matings. There is variation of inbreeding load among animals, although its magnitude does not seem enough to warrant selection based on this criterion. [ABSTRACT FROM AUTHOR]

Thirlwall Model shows evidence in Latin American countries, as well as for the Peruvian economy, with an economic growth rate of balance of payments equilibrium, which is explained by causal variables that present a long-term cointegration relationship. These variables are exports with little added value, imports that reinforce technological dependence, external income, relative prices or the real exchange rate, the institutions, and the volatility of exports. Investment policies are prescribed in innovative, physical, financial, natural, and social human capital that tend to reduce the restriction of foreign exchange, technological dependence and the international market. Therefore, endogenous, dynamic, sustained, inclusive economic growth is generated, low in carbon as a means for sustainable human development, within the framework of a new growth and development strategy that involves balancing the participation of the market, state and civil society. [ABSTRACT FROM AUTHOR]

This study analyses and explains food imports from Peru: 1980-2021. The econometric method uses Autoregressive Distributed Lagged (ARDL) models. The result of the stationarity property of I (0) and I(1) of the variables suggests the use of the ARDL model. The Granger causality result shows that variables explain food imports. The bound test cointegration showed a long-run cointegration to exist between foot imports and income, the real exchange rate, relative prices, price of fertilizers, and institution. The short-run analysis shows positive effects of relative prices and the real exchange rate towards food imports. And in the long-run analysis, we have found a positive relationship between food imports and economic growth. Also, there is a negative relationship between food imports and the growth of the real exchange rate, the price of fertilizers, and the opening of the Free Trade Agreement. Policies for self-sufficiency are recommended through investment policies in human capital for research in fertilizers and alternative organic manures; in financial capital for access to credit for small producers; in social capital, with support for sectors with lower productivity in rural areas to reduce dependence on the international market and the growing demand for food imports that puts food security at risk. [ABSTRACT FROM AUTHOR]

Crossbreeding plays a pivotal role within pig breeding programmes, aiming to maximize heterosis and improve reproductive traits in crossbred maternal lines. Nevertheless, there is evidence indicating that the performance of reciprocal crosses between two genetic lines might exhibit variability. These variations in performance can be attributed to differences in the correlations between gametic effects, acting as either sire or dam, within purebred and crossbred populations. To address this issue, we propose a multivariate gametic model that incorporates up to four correlated gametic effects for each parental population. The model is employed on a data set comprising litter size data (total number of piglets born—TNB‐ and number of piglets born alive—NBA‐) derived from a reciprocal cross involving two Iberian pig populations: Entrepelado and Retinto. The data set comprises 6933 records from 1564 purebred Entrepelado (EE) sows, 4995 records from 1015 Entrepelado × Retinto (ER) crosses, 2977 records from 756 Retinto × Entrepelado (RE) crosses and 7497 records from 1577 purebred Retinto (RR) sows. The data set is further supplemented by a pedigree encompassing 6007 individual‐sire‐dam entries. The statistical model also included the order of parity (with six levels), the breed of the service sire (five levels) and the herd‐year‐season effects (141 levels). Additionally, the model integrates random dominant and permanent environmental sow effects. The analysis employed a Bayesian approach, and the results revealed all the posterior estimates of the gametic correlations to be positive. The range of the posterior mean estimates of the correlations varied across different gametic effects and traits, with a range between 0.04 (gametic correlation between the paternal effects for purebred and the maternal for crossbred in Retinto) and 0.53 (gametic correlation between the paternal effects for purebred and the paternal for crossbred in Entrepelado). Furthermore, the posterior mean variance estimates of the maternal gametic effects were consistently surpassed those for paternal effects within all four populations. The results suggest the possible influence of imprinting effects on the genetic control of litter size, and underscore the importance of incorporating crossbred data into the breeding value predictions for purebred individuals. [ABSTRACT FROM AUTHOR]

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It is generally assumed that parents make a genetically equal contribution to their offspring, but this assumption might not always hold. This is because the expression of a gene can be blocked by methylation during gametogenesis, and the degree of methylation can depend on the origin of the parental gene (imprinting) or by preferential management associated with genetic merit. The first consequences of this for quantitative genetics is that the mean phenotypes of reciprocal heterozygotes need no longer be the same, as would be expected according to Mendelian heritage. We analysed three mare reproductive traits (reproductive efficiency, age at first foaling and foaling number) and three morphological traits (height at withers, thoracic circumference, and scapula‐ischial length) in the Pura Raza Española (PRE) horse population, which possesses a deep and reliable pedigree, making it a perfect breed for analysing the quantitative effect of parent‐of‐origin. The number of animals analysed ranged from 44,038 to 144,191, all of them with both parents known. The model comparison between a model without parent‐of‐origin effects and three different models with parent‐of‐origin effects revealed that both maternal and paternal gametic effects influence all the analysed traits. The maternal gametic effect had a higher influence on most traits, accounting for between 3% and 11% of the total phenotypic variance, while the paternal gametic effect accounted for a higher proportion of variance in one trait, age at first foaling (4%). As expected, the Pearson's correlations between additive breeding values of models that consider parent‐of‐origin and that do not consider parent‐of‐origin were very high; however, the percentage of coincident animals slightly decreases when comparing animals with the highest estimated breeding values. Ultimately, this work demonstrates that parent‐of‐origin effects exist in horse gene transmission from a quantitative point of view. Additionally, including an estimate of the parent‐of‐origin effect within the PRE horse breeding program could be a great tool for a better parent's selection and that could be of interest for breeders, as this value will determine whether the animals acquire genetic categories and are much more highly valued. [ABSTRACT FROM AUTHOR]

Background and purpose: The aim of this study was to describe the frequency and distribution of SOD1 mutations in Spain, and to explore factors contributing to their phenotype and prognosis. Methods: Seventeen centres shared data on amyotrophic lateral sclerosis (ALS) patients carrying pathogenic or likely pathogenic SOD1 variants. Multivariable models were used to explore prognostic modifiers. Results: In 144 patients (from 88 families), 29 mutations (26 missense, 2 deletion/insertion and 1 frameshift) were found in all five exons of SOD1, including seven novel mutations. A total of 2.6% of ALS patients (including 17.7% familial and 1.3% sporadic) were estimated to carry SOD1 mutations. The frequency of this mutation varied considerably among regions, due to founder events. The most frequent mutation was p.Gly38Arg (n = 58), followed by p.Glu22Gly (n = 11), p.Asn140His (n = 10), and the novel p.Leu120Val (n = 10). Most mutations were characterized by a protracted course, and some of them by atypical phenotypes. Older age of onset was independently associated with faster disease progression (exp[Estimate] = 1.03 [0.01, 0.05], p = 0.001) and poorer survival (hazard ratio 1.05 [1.01, 1.08], p = 0.007), regardless of the underlying mutation. Female sex was independently associated with faster disease progression (exp[Estimate] = 2.1 [1.23, 3.65], p = 0.012) in patients carrying the p.Gly38Arg mutation, resulting in shorter survival compared with male carriers (236 vs. 301 months). Conclusions: These data may help to evaluate the efficacy of SOD1 targeted treatments, and to expand the number of patients that might benefit from these treatments. [ABSTRACT FROM AUTHOR]