Mapping recombination rate on the autosomal chromosomes based on the persistency of linkage disequilibrium phase among autochthonous beef cattle populations in Spain

Mouresan, Elena Flavia. Universidad de Zaragoza. Departamento de Anatomía, Embriología y Genética Animal. Zaragoza, España.González Rodríguez, Aldemar. Universidad de Zaragoza. Departamento de Anatomía, Embriología y Genética Animal. Zaragoza, España.Cañas Alvarez, Jhon J. Universitat Autònoma de Barcelona. Departament de Ciència Animal i dels Aliments. Barcelona, España.Munilla Leguizamón, Sebastián. Universidad de Zaragoza. Departamento de Anatomía, Embriología y Genética Animal. Zaragoza, España.Altarriba, Juan. Universidad de Zaragoza. Departamento de Anatomía, Embriología y Genética Animal. Zaragoza, España.Díaz, Clara. Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA). Departamento de Mejora Genética Animal. Madrid, España.Baro, Jesus A. Instituto Agroalimentario de Aragón (IA2). Zaragoza, España.Molina, Antonio. Universidad de Valladolid. Departamento de Ciencias Agroforestales. Valladolid, España.12In organisms with sexual reproduction, genetic diversity, and genome evolution are governed by meiotic recombination caused by crossing-over, which is known to vary within the genome. In this study, we propose a simple method to estimate the recombination rate that makes use of the persistency of linkage disequilibrium (LD) phase among closely related populations. The biological material comprised 171 triplets (sire/ dam/offspring) from seven populations of autochthonous beef cattle in Spain (Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta, and Rubia Gallega), which were genotyped for 777,962 SNPs with the BovineHD BeadChip. After standard quality filtering, we reconstructed the haplotype phases in the parental individuals and calculated the LD by the correlation -r- between each pair of markers that had a genetic distance smaller than 1 Mb. Subsequently, these correlations were used to calculate the persistency of LD phase between each pair of populations along the autosomal genome. Therefore, the distribution of the recombination rate along the genome can be inferred since the effect of the number of generations of divergence should be equivalent throughout the genome. In our study, the recombination rate was highest in the largest chromosomes and at the distal portion of the chromosomes. In addition, the persistency of LD phase was highly heterogeneous throughout the genome, with a ratio of 25.4 times between the estimates of the recombination rates from the genomic regions that had the highest (BTA18-7.1 Mb) and the lowest (BTA12- 42.4 Mb) estimates. Finally, an over representation enrichment analysis (ORA) showed differences in the enriched gene ontology (GO) terms between the genes located in the genomic regions with estimates of the recombination rate over (or below) the 95th (or 5th) percentile throughout the autosomal genome

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

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

Detección de regiones genómicas con elevado desequilibrio de ligamiento en poblaciones de vacuno de carne españolas con análisis de BovineHD BeadChip

Mouresan, E. F. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.González Rodríguez, A. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Munilla, Sebastián. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Moreno, C. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Altarriba, J. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Díaz, C. Instituto Nacional de Tecnología Agraria y Alimentaria (INIA). Mejora Genética Animal. Madrid, España.Baro, J. A. Universidad de Valladolid. Departamento de Ciencias Agroforestales. Producción Animal. Valladolid. España.Piedrafita, J. Universitad Autónoma de Barcelona. Ciencia Animal y de los Alimentos. Barcelona, España.Molina, A. Universidad de Córdoba. Departamento de Genética. Córdoba. Spain.Cañas Alvarez, J. J. Universitad Autónoma de Barcelona. Ciencia Animal y de los Alimentos. Barcelona, España.Varona, L. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.59-65El objetivo de este trabajo fue evaluar el patrón de desequilibrio de ligamiento a lo largo del genoma en siete poblaciones españolas autóctonas de vacuno de carne (Asturiana de los Valles, Avileña Negra - Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta y Rubia Gallega). Para ello, se utilizó el BovineHD BeadChip con el que se genotiparon 171 tríos formados por individuo/padre/madre. Después del filtrado, se dispuso de 573.134 SNP. A partir de esta información se definió un parámetro que mide el desequilibrio medio del genoma por regiones de 1Mb en cada una de las poblaciones. Los resultados mostraron que el desequilibrio de ligamiento es muy heterogéneo a lo largo del genoma y que, además, esta heterogeneidad es consistente entre poblaciones. Las causas de esta heterogeneidad pueden ser, o bien estructurales y atribuibles a una menor tasa de mutación y/o recombinación, o bien consecuencia de procesos de selección estabilizadora

Detección de regiones genómicas con elevado desequilibrio de ligamiento en poblaciones de vacuno de carne españolas con análisis de BovineHD BeadChip

Mouresan, E. F. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.González Rodríguez, A. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Munilla, Sebastián. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Moreno, C. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Altarriba, J. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.Díaz, C. Instituto Nacional de Tecnología Agraria y Alimentaria (INIA). Mejora Genética Animal. Madrid, España.Baro, J. A. Universidad de Valladolid. Departamento de Ciencias Agroforestales. Producción Animal. Valladolid. España.Piedrafita, J. Universitad Autónoma de Barcelona. Ciencia Animal y de los Alimentos. Barcelona, España.Molina, A. Universidad de Córdoba. Departamento de Genética. Córdoba. Spain.Cañas Alvarez, J. J. Universitad Autónoma de Barcelona. Ciencia Animal y de los Alimentos. Barcelona, España.Varona, L. Universidad de Zaragoza. Facultad de Veterinaria. Unidad de Mejora Genética. Zaragoza, España.59-65El objetivo de este trabajo fue evaluar el patrón de desequilibrio de ligamiento a lo largo del genoma en siete poblaciones españolas autóctonas de vacuno de carne (Asturiana de los Valles, Avileña Negra - Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta y Rubia Gallega). Para ello, se utilizó el BovineHD BeadChip con el que se genotiparon 171 tríos formados por individuo/padre/madre. Después del filtrado, se dispuso de 573.134 SNP. A partir de esta información se definió un parámetro que mide el desequilibrio medio del genoma por regiones de 1Mb en cada una de las poblaciones. Los resultados mostraron que el desequilibrio de ligamiento es muy heterogéneo a lo largo del genoma y que, además, esta heterogeneidad es consistente entre poblaciones. Las causas de esta heterogeneidad pueden ser, o bien estructurales y atribuibles a una menor tasa de mutación y/o recombinación, o bien consecuencia de procesos de selección estabilizadora

Salud de los trabajadores

Actividad física y su relación con los factores de riesgo cardiovascular de carteros chilenosAnálisis de resultados: riesgos psicosociales en el trabajo Suceso-Istas 21 en Cesfam QuellónAusentismo laboral por enfermedades oftalmológicas, Chile 2009Brote de diarreas por norovirus, posterremoto-tsunami, Constitución, Región del MauleCalidad de vida en profesionales de la salud pública chilenaCaracterización del reposo laboral en personal del SSMN durante el primer semestre de 2010Concentración de nicotina en pelo en trabajadores no fumadores expuestos a humo de tabaco ambientalCondiciones de trabajo y bienestar/malestar docente en profesores de enseñanza media de SantiagoDisfunción auditiva inducida por exposición a xilenoErgonomía aplicada al estudio del síndrome de dolor lumbar en el trabajoEstimación de la frecuencia de factores de riesgo cardiovascular en trabajadores de una empresa mineraExposición a plaguicidas inhibidores de la acetilcolinesterasa en Colombia, 2006-2009Factores de riesgo y daños de salud en conductores de una empresa peruana de transporte terrestre, 2009Las consecuencias de la cultura en salud y seguridad ocupacional en una empresa mineraPercepción de cambios en la práctica médica y estrategias de afrontamientoPercepción de la calidad de vida en la Universidad del BiobíoPesos máximos aceptables para tareas de levantamiento manual de carga en población laboral femeninaRiesgo coronario en trabajadores mineros según la función de Framingham adaptada para la población chilenaTrastornos emocionales y riesgo cardiovascular en trabajadores de la salu

Inferencia bayesiana sobre los parámetros de dispersión genéticos y ambientales en modelos animales con efectos maternos

Los modelos 'modelos animales con efectos maternos' (MAM)son modelos lineales mixtos que se utilizan para ajustar registros de caracteres bajo la influencia de efectos maternos. Uno de los desafíos más importantes en el marco de los MAM es la estimación de los parámetros de dispersión o 'componentes de (co)varianza' (CVC). En esta tesis se introducen desde una perspectiva bayesiana contribuciones teóricas y metodológicas con relación a la estimación de CVC para MAM sujetos a estructuras de covarianza novedosas. En primer lugar, se describe una implementación del análisis bayesiano jerárquico vía el algoritmo del muestreo de Gibbs. Luego, se considera una especificación conjugada diferente para la distribución a priori de la matriz de covarianza genética, basada en la distribución Wishart invertida generalizada, y se presenta una estrategia para determinar los correspondientes hiperparámetros. Esta estrategia fue comparada contra otras especificaciones a priori mediante un estudio de simulación estocástica, y produjo estimaciones precisas de los parámetros genéticos, con menores errores estándares y mejor tasa de convergencia. En segundo lugar, se presenta una formulación alternativa del MAM que incluye un parámetro de correlación ambiental entre pares de observaciones madre-progenie, y se desarrolla un procedimiento de estimación basado en un algoritmo de muestreo por grilla. El procedimiento fue programado y ejecutado exitosamente, y se obtuvo la primera estimación del parámetro de correlación con datos de campo para peso al destete en bovinos de carne. Por último, se considera el problema de la estimación de CVC en una población multirracial, donde en general es necesario especificar una estructura de covarianza heterogénea para los valores de cría. En particular, se demuestra que el modelo basado en la descomposición de la matriz de covarianza genética es equivalente al que deriva de la teoría genética cuantitativa. Además, se extiende el modelo para incluir efectos maternos y se describe la implementación de un análisis bayesiano jerárquico con el objetivo de estimar los CVC. El procedimiento fue implementado con éxito en datos experimentales de peso al destete y se obtuvieron por primera vez estimaciones para el conjunto completo de CVC

Comparing Genomic Prediction Models by Means of Cross Validation

In the two decades of continuous development of genomic selection, a great variety of models have been proposed to make predictions from the information available in dense marker panels. Besides deciding which particular model to use, practitioners also need to make many minor choices for those parameters in the model which are not typically estimated by the data (so called “hyper-parameters”). When the focus is placed on predictions, most of these decisions are made in a direction sought to optimize predictive accuracy. Here we discuss and illustrate using publicly available crop datasets the use of cross validation to make many such decisions. In particular, we emphasize the importance of paired comparisons to achieve high power in the comparison between candidate models, as well as the need to define notions of relevance in the difference between their performances. Regarding the latter, we borrow the idea of equivalence margins from clinical research and introduce new statistical tests. We conclude that most hyper-parameters can be learnt from the data by either minimizing REML or by using weakly-informative priors, with good predictive results. In particular, the default options in a popular software are generally competitive with the optimal values. With regard to the performance assessments themselves, we conclude that the paired k-fold cross validation is a generally applicable and statistically powerful methodology to assess differences in model accuracies. Coupled with the definition of equivalence margins based on expected genetic gain, it becomes a useful tool for breeders

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

Mixed models are commonly used for the estimation of variance components and genetic evaluation of livestock populations. Some evaluation models include two types of additive genetic effects, direct and maternal. Estimates of variance components obtained with models that account for maternal effects have been the subject of a long-standing controversy about strong negative estimates of the covariance between direct and maternal effects. Genomic imprinting is known to be in some cases statistically confounded with maternal effects. In this study, we analysed the consequences of ignoring paternally inherited effects on the partitioning of genetic variance. We showed that the existence of paternal parent-of-origin effects can bias the estimation of variance components when maternal effects are included in the evaluation model. Specifically, we demonstrated that adding a constraint on the genetic parameters of a maternal model resulted in correlations between relatives that were the same as those obtained with a model that fits only paternally inherited effects for most pairs of individuals, as in livestock pedigrees. The main consequence is an upward bias in the estimates of the direct and maternal additive genetic variances and a downward bias in the direct-maternal genetic covariance. This was confirmed by a simulation study that investigated five scenarios, with the trait affected by (1) only additive genetic effects, (2) only paternally inherited effects, (3) additive genetic and paternally inherited effects, (4) direct and maternal additive genetic effects and (5) direct and maternal additive genetic plus paternally inherited effects. For each scenario, the existence of a paternally inherited effect not accounted for by the estimation model resulted in a partitioning of the genetic variance according to the predicted pattern. In addition, a model comparison test confirmed that direct and maternal additive models and paternally inherited models provided an equivalent fit. Ignoring paternally inherited effects in the maternal models for genetic evaluation can lead to a specific pattern of bias in variance component estimates, which may account for the unexpectedly strong negative direct-maternal genetic correlations that are typically reported in the literature. The online version of this article (doi:10.1186/s12711-015-0141-5) contains supplementary material, which is available to authorized users

Breeding value predictive accuracy for scarcely recorded traits in a Eucalyptus grandis breeding population using genomic selection and data on predictor traits

Genomic selection methods are particularly useful for traits that are difcult or expensive to measure. We investigated the impact of using predictor growth traits and/or genomic information to increase the breeding value (BV) predictive accuracies for target scarcely recorded wood quality traits in an open-pollinated Eucalyptus grandis population. The performance of single- and multiple-trait single-step genomic best linear unbiased prediction and conventional pedigree-based models were compared in terms of the predictive accuracies (PA) of estimated BV for the target traits. We also derived the contributions of the BV for candidate trees to better understand our results. The inclusion of predictor traits in both, the training and the validation sets, together with genomic information, improved the PA (up to 17.7%) for pulp yield and cellulose. However, signifcant improvements in PA were not observed when predictor traits were recorded only in the training set or when the impact of genomic information alone was assessed. Changes in the PA were explained by the variations in the maternal contributions, contribution/s from all the predictor/s trait/s, and from genotyped trees. We conclude that there is not a “uni versal” rule regarding the use of genomic information and records on predictor traits. However, assessing the contributions to the BV of validation trees may help to better design how to beneft from predictor traits in forest tree breeding.Fil: Jurcic, Esteban J. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Villalba, Pamela Victoria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Dutour, Joaquín. Forestal Oriental, UPM, Paysandú, UruguayFil: Centurión, Carmelo. Forestal Oriental, UPM, Paysandú, UruguayFil: Munilla, Sebastián. Universidad de Buenos Aires, Facultad de Agronomía, Departamento de Producción Animal, Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

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

Funding: Seventh Framework Programme 289592Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations. Analysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic-pituitary-thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors. We show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits. The online version of this article (doi:10.1186/s12711-016-0258-1) contains supplementary material, which is available to authorized users