Use of a reduced set of single nucleotide polymorphisms for genetic evaluation of resistance to Salmonella carrier state in laying hens

Chantier qualité GA; Salmonella propagation by apparently healthy chickens could be decreased by the selection and use of chicken lines that are more resistant to carrier state. Using a reduced set of markers, this study investigates, for the first time to the authors' knowledge, the feasibility of a genomic selection approach for resistance to carrier state in hen lines. In this study, commercial laying hen lines were divergently selected for resistance to Salmonella carrier state at 2 different ages: young chicks and adults at the peak of lay. A total of 600 birds were typed with 831 informative SNP markers and artificially infected with Salmonella Enteritidis. Phenotypes were collected 28 d (389 young animals) or 38 d (208 adults) after infection. Two types of variance component analyses, including SNP data or not, were performed and compared. The set of SNP used was efficient in capturing a large part of the genetic variation. Average accuracies from mixed model equations did not change between analyses, showing that using SNP data does not increase information in this data set. These results confirm that genomic selection for Salmonella carrier state resistance in laying hens is promising. Nevertheless, a denser SNP coverage of the genome on a greater number of animals is still needed to assess its feasibility and efficiency

High-power density electric motors for regional aircraft propulsion.

This Master's thesis project aims, firstly, to evaluate the current state of the art in aeronautical propulsion technology using electric machines. Once the state of the art has been studied, a tool for the design and calculation of electric motors with superconducting windings is developed in order to present a pre-design that meets the established objectives. The analysis carried out on the state of the art will provide information on the design guidelines that have been taken in recent years, as well as the different projects and studies that are planned for the medium-term future. Thanks to this framework, geometric and performance requirements of the motor are defined together with the objectives to be met. In order to achieve this goal, a superconducting motor design module is implemented in Matlab and FEMM, which helps to develop the selected motor efficiently, rapidly and accurately. The IPED electric machine design tool is described, and the different stages in the calculation of the motor are explained in detail. Finally, the conclusions drawn from the different chapters are summarised, which will serve as a guideline for the continuation of the HIVOMOT project, in which this Master's thesis is framed.El presente proyecto de fin de Máster trata, en primer lugar, de realizar una evaluación sobre el estado actual de la tecnología de la propulsión aeronáutica mediante máquinas eléctricas. Una vez estudiado el estado del arte, se desarrolla una herramienta de diseño y cálculo de motores eléctricos con devanados superconductores con el fin de presentar un prediseño que cumpla con los objetivos establecidos. El análisis realizado sobre el estado de la tecnología permitirá conocer las líneas de diseño que se han tomado en los últimos años, así como los diferentes proyectos y estudios que están previstos en un futuro a medio plazo. Gracias a este marco de trabajo se definen unos requerimientos geométricos y de prestaciones del motor junto con unos objetivos a cumplir. Para poder alcanzar esta meta se implementa un módulo de diseño de motores superconductores en Matlab y FEMM que ayuda a desarrollar el motor seleccionado de forma eficaz, rápida y precisa. Se describe la herramienta de diseño de máquinas eléctricas IPED, y se explica de forma detallada las diferentes etapas en el cálculo del motor. Por último, se resumen las conclusiones extrapoladas en los diferentes capítulos y que servirán como pauta de cara a la continuación del proyecto HIVOMOT, en el que se encuentra enmarcado este proyecto de Fin de Máster

Revisión crítica de la estimulación subtalámica en la enfermedad de Parkinson

The authors critically review subthalamic nucleus (STN) stimulation for Parkinson's disease (PD) at long follow-up (3-5 years). Subthalamic stimulation induce a significant improvement during the "off" medication in the assessment motor score UPDRS (Unified Parkinson Disease Rating Scale) 3-5 years after surgery. Results show that the benefits obtained in tremor, rigidity, bradykinesia, dyskinesias induced by medication and levodopa reduction are significantly maintained during long term. The improvement in other clinical signs as gait and postural stability at long follow-up are not maintained comparing with the benefits obtained one year after surgery. A high percentage of patients show a cognitive disturbance during the follow-up period that may be correlated with the disease progression. The conclusion is that bilateral STN stimulation is an effective treatment for PD patients at long term but it should be considered earlier in the course of P

Genome-wide association study for feed efficiency in collective cage-raised rabbits under full and restricted feeding

Feed efficiency (FE) is one of the most economically and environmentally relevant traits in the animal production sector. The objective of this study was to gain knowledge about the genetic control of FE in rabbits. To this end, GWASs were conducted for individual growth under two feeding regimes (full feeding and restricted) and FE traits collected from cage groups, using 114 604 autosome SNPs segregating in 438 rabbits. Two different models were implemented: (1) an animal model with a linear regression on each SNP allele for growth trait; and (2) a two‐trait animal model, jointly fitting the performance trait and each SNP allele content, for FE traits. This last modeling strategy is a new tool applied to GWAS and allows information to be considered from non‐genotyped individuals whose contribution is relevant in the group average traits. A total of 189 SNPs in 17 chromosomal regions were declared to be significantly associated with any of the five analyzed traits at a chromosome‐wide level. In 12 of these regions, 20 candidate genes were proposed to explain the variation of the analyzed traits, including genes such as FTO, NDUFAF6 and CEBPA previously associated with growth and FE traits in monogastric species. Candidate genes associated with behavioral patterns were also identified. Overall, our results can be considered as the foundation for future functional research to unravel the actual causal mutations regulating growth and FE in rabbits.info:eu-repo/semantics/publishedVersio

International genomic evaluation methods for dairy cattle

<p>Abstract</p> <p>Background</p> <p>Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Higher reliabilities from larger genotype files promote cooperation across country borders. Genomic information can be exchanged across countries using simple conversion equations, by modifying multi-trait across-country evaluation (MACE) to account for correlated residuals originating from the use of foreign evaluations, or by multi-trait analysis of genotypes for countries that use the same reference animals.</p> <p>Methods</p> <p>Traditional MACE assumes independent residuals because each daughter is measured in only one country. Genomic MACE could account for residual correlations using daughter equivalents from genomic data as a fraction of the total in each country and proportions of bulls shared. MACE methods developed to combine separate within-country genomic evaluations were compared to direct, multi-country analysis of combined genotypes using simulated genomic and phenotypic data for 8,193 bulls in nine countries.</p> <p>Results</p> <p>Reliabilities for young bulls were much higher for across-country than within-country genomic evaluations as measured by squared correlations of estimated with true breeding values. Gains in reliability from genomic MACE were similar to those of multi-trait evaluation of genotypes but required less computation. Sharing of reference genotypes among countries created large residual correlations, especially for young bulls, that are accounted for in genomic MACE.</p> <p>Conclusions</p> <p>International genomic evaluations can be computed either by modifying MACE to account for residual correlations across countries or by multi-trait evaluation of combined genotype files. The gains in reliability justify the increased computation but require more cooperation than in previous breeding programs.</p

Simulating a base population in honey bee for molecular genetic studies

<p>Abstract</p> <p>Background</p> <p>Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (<it>Varroa destructor</it>) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee.</p> <p>Results</p> <p>Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ² statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r² values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r² value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency.</p> <p>Conclusion</p> <p>We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at <url>http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html</url></p

Genetic prediction of complex traits: integrating infinitesimal and marked genetic effects

Genetic prediction for complex traits is usually based on models including individual (infinitesimal) or marker effects. Here, we concentrate on models including both the individual and the marker effects. In particular, we develop a ''Mendelian segregation'' model combining infinitesimal effects for base individuals and realized Mendelian sampling in descendants described by the available DNA data. The model is illustrated with an example and the analyses of a public simulated data file. Further, the potential contribution of such models is assessed by simulation. Accuracy, measured as the correlation between true (simulated) and predicted genetic values, was similar for all models compared under different genetic backgrounds. As expected, the segregation model is worthwhile when markers capture a low fraction of total genetic variance. (Résumé d'auteur

Deregressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs

<p>Abstract</p> <p>Background</p> <p>Genomic selection can be implemented by a multi-step procedure, which requires a response variable and a statistical method. For pure-bred pigs, it was hypothesised that deregressed estimated breeding values (EBV) with the parent average removed as the response variable generate higher reliabilities of genomic breeding values than EBV, and that the normal, thick-tailed and mixture-distribution models yield similar reliabilities.</p> <p>Methods</p> <p>Reliabilities of genomic breeding values were estimated with EBV and deregressed EBV as response variables and under the three statistical methods, genomic BLUP, Bayesian Lasso and MIXTURE. The methods were examined by splitting data into a reference data set of 1375 genotyped animals that were performance tested before October 2008, and 536 genotyped validation animals that were performance tested after October 2008. The traits examined were daily gain and feed conversion ratio.</p> <p>Results</p> <p>Using deregressed EBV as the response variable yielded 18 to 39% higher reliabilities of the genomic breeding values than using EBV as the response variable. For daily gain, the increase in reliability due to deregression was significant and approximately 35%, whereas for feed conversion ratio it ranged between 18 and 39% and was significant only when MIXTURE was used. Genomic BLUP, Bayesian Lasso and MIXTURE had similar reliabilities.</p> <p>Conclusions</p> <p>Deregressed EBV is the preferred response variable, whereas the choice of statistical method is less critical for pure-bred pigs. The increase of 18 to 39% in reliability is worthwhile, since the reliabilities of the genomic breeding values directly affect the returns from genomic selection.</p