Bayesian estimation in maternally ancestral animal models for weaning weight of beef cattle

The Bayesian approach was implemented for fitting several maternally ancestral models for weaning weight data of Angus calves. The goal was to evaluate to what extent genetic evaluation models with additive grand maternal effects (G), or with an ancestrally structured covariance matrix for maternal environmental effects (E), or with a sire × year interaction (ISY), or combinations thereof (GE, GSY, ESY, GESY), redistribute the additive variability and reduce the negative magnitude of the additive correlation between direct and maternal effects (rAoAm), when compared with the regular maternal animal model (I). All animals with records had known dams and maternal granddams. The sampling scheme induced low autocorrelations among all variables and tended to converge quickly. The signs of the estimates of rAoAm were consistently negative for all models fitted. The magnitudes of the estimates of rAoAm from models E, G, GE, ESY, and GESY were almost one-third of those from models I and ISY. Inclusion of the sire × year interaction had some effect in reducing the negative magnitude of rAoAm, but also reduced the size of the estimates of direct (ho 2) and maternal ( hm 2) heritabilities. In comparison, models E or G reduced the negative magnitude of rAoAm by 0.50 units and produced more favorable estimates of ho 2 and hm 2 than models I and ISY. The estimate of ho 2 from G was similar to the one from I; however, the estimated hm 2 was 0.04 units greater, whereas the estimate of rAoAm was much less negative (−0.21 vs. −0.71) than the respective estimates from I. The environmental correlation between the weaning weights of dams and their daughters (λ) was estimated to be −0.28 ± 0.03 in E and ESY, and −0.21 ± 0.03 in GE and GESY. Inclusion of the sire × year interaction effect by itself did not have much of an impact in the reduction of the estimated magnitude of rAoAm. Rank correlations among EBV for direct effects were larger than 0.94 and did not show any appreciable difference among models, whereas the rank correlation among maternal breeding values displayed differences in the ranking between I and the other models. Models E and ESY recovered the largest amount of total additive variability with maternal effects.Fil: Suárez, M. J.. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentin

Bayesian estimation of (co) variance components in Argentinian Brangus for carcass traits using the FCG algorithm

Se emplearon los datos de 2273 toritos y vaquillonas Brangus para estimar las heredabilidades (h2 ) y las correlaciones aditivas y ambientales de caracteres de calidad de carne medidos por ultrasonido. Los registros provenían del programa de evaluación genética de la Asociación Argentina de Brangus. Los caracteres medidos fueron el área del ojo del bife (AOB), el marmoreado (MB), la grasa dorsal (GD) y la grasa de cadera (GC). La edad media de los animales al momento de la medición fue 641 días en machos y 685 días en hembras. Los parámetros genéticos y ambientales fueron estimados mediante un algoritmo bayesiano conjugado. Los valores estimados de h2 fueron 0,22, 0,16, 0,12 y 0,21, para AOB, GD, CC y MB, respectivamente. En términos generales, las estimaciones de las correlaciones genéticas y ambientales se encontraron cercanas a la cifra media de la literatura. Si bien los valores estimados de h2 fueron inferiores al promedio de la investigación realizada en vacunos para carne, la variabilidad encontrada es suficiente como para que la respuesta a la selección por estos caracteres – empleando predicciones de los valores de cría calculadas con los parámetros estimados - sea moderadamente efectiva.Data on 2273 Brangus young bulls and heifers were used to estimate heritabilities (h2 ) and genetics and environmental correlations for ultrasound carcass measures. Records were from the genetic evaluation program of Asociación Argentina de Brangus. Traits measured were rib-eye area (AOB), marbling (MB), back-fat thickness (GD), and hip-fat thickness (GC). Average ages of measure were 641 days in males and 685 in females. The genetic and environmental dispersion parameters were estimated by a conjugate Bayesian algorithm (FCG). Estimates of h2 were 0,22, 0,16, 0,12, and 0,21, for AOB, GD, CC, and MB, respectively. In general, estimates of genetic and environmental correlations were close to the average published values. Even tough estimates of h2 were below the average of published estimates for beef cattle, the additive genetic variation found in the current study would lead to a moderate response to selection – using predictions of breeding value that are calculated with the estimate parameters.Fil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Birchmeier, A. N.. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentin

Genotype imputation accuracy in a F2 pig population using high density and low density SNP panels

Background: F2 resource populations have been used extensively to map QTL segregating between pig breeds. A limitation associated with the use of these resource populations for fine mapping of QTL is the reduced number of founding individuals and recombinations of founding haplotypes occurring in the population. These limitations, however, become advantageous when attempting to impute unobserved genotypes using within family segregation information. A trade-off would be to re-type F2 populations using high density SNP panels for founding individuals and low density panels (tagSNP) in F2 individuals followed by imputation. Subsequently a combined meta-analysis of several populations would provide adequate power and resolution for QTL mapping, and could be achieved at relatively low cost. Such a strategy allows the wealth of phenotypic information that has previously been obtained on experimental resource populations to be further mined for QTL identification. In this study we used experimental and simulated high density genotypes (HD-60K) from an F2 cross to estimate imputation accuracy under several genotyping scenarios. Results: Selection of tagSNP using physical distance or linkage disequilibrium information produced similar imputation accuracies. In particular, tagSNP sets averaging 1 SNP every 2.1 Mb (1,200 SNP genome-wide) yielded imputation accuracies (IA) close to 0.97. If instead of using custom panels, the commercially available 9K chip is used in the F2, IA reaches 0.99. In order to attain such high imputation accuracy the F0 and F1 generations should be genotyped at high density. Alternatively, when only the F0 is genotyped at HD, while F1 and F2 are genotyped with a 9K panel, IA drops to 0.90. Conclusions: Combining 60K and 9K panels with imputation in F2 populations is an appealing strategy to re-genotype existing populations at a fraction of the cost.Fil: Gualdron Duarte, Jose Luis. Michigan State University; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bates, Ronald O.. Michigan State University; Estados UnidosFil: Ernst, Catherine W.. Michigan State University; Estados UnidosFil: Raney, Nancy E.. Michigan State University; Estados UnidosFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Steibel, Juan P.. Michigan State University; Estados Unido

Eficiencia de la capacitancia y altura de canopeo comprimido (con disco) para estimar biomasa forrajera

p.213-219En pasturas de ciclo OIP de la Pcia. de Buenos Aires, entre marzo y setiembre se evaluó la hipótesis de que en relación al método directo (referencia) un sistema integrado por capacitancia y altura de canopeo comprimida por un disco, produciría mejores estimaciones de biomasa forrajera (BF) que por separado. Las estimaciones se evaluaron por regresión en doble muestreo. Los valores de referencia e indirectos, provenientes de muestras aleatorias y sujetas a error, se analizaron mediante un modelo de variables con error (EIV). Las regresiones simples entre referencia y capacitancia o disco, resultaron significativas (P igual 0,004) con coeficientes de determinación (r2) menores a 3 por ciento. La regresión múltiple Y(BF, kg MS ha`1) igual a 694,0 + 0,38 (capacitancia) - 2,4 X2 (disco) resultó significativa (P igual a 0,042) con un r2 igual a 21 por ciento. El modelo de EIV generó la ecuación Y (BF, kg MS. h a 1) igual a 303,98 + 0,753 X (capacitancia), (DE igual a 494,9 kg MS. h a 1, CV igual a 29,3 por ciento) para utilizarla de marzo a septiembre. La utilización conjunta de capacitancia y altura con disco mejoró las estimaciones de BF comparada con cada estimador individual, pero no en magnitud apreciable

Efecto de la varianza genética aditiva generacional sobre las componentes de la respuesta a la selección en una población con generaciones superpuestas

p.221-230El objetivo de esta investigación fue comparar la respuesta a la selección usando el Modelo Animal-BLUP con grupos genéticos, utilizando la variancia genética aditiva de cada generación (s²A(C), con aquel que utiliza la variancia aditiva en la población base (s²a), mediante simulación estocastica de una población animal con generaciones superpuestas. A diferencia de otros estudios, el modelo de generación de datos incluyó efectos fijos como el sexo (variable clasificatoria) y la edad del animal a la medición del carácter (covariable), con el objeto de asemejarse a los modelos de evaluación en poblaciones reales. Los resultados corresponden a 20 años de selección, tomando el promedio de 100 réplicas. La h² original en la población fue 0,4. La pérdida de información consistió en omitir al azar relaciones de parentesco, afín de incorporar los grupos al modelo de evaluación animal. El 25 por ciento de los animales poseían ambos padres desconocidos, 25 por ciento poseían la madre desconocida, 25 por ciento el padre y el 25 por ciento restante poseían ambos padres conocidos. En las condiciones simuladas no se observaron diferencias significativas (pmayor a 0,05), en las variables estudiadas: respuesta a la selección, variancia aditiva, exactitud, intensidad de selección, consanguinidad e intervalo generacional, para los casos de información completa e incompleta con la inclusión de grupos, según se consideró las s²a ó la s²a(g

Gene expression specificity of the mussel antifungal mytimycin (MytM)

We previously reported the nucleotide sequences and diversity of mytimycin (MytM) from the Mediterranean mussel, Mytilus galloprovincialis. Using real-time PCR (q-PCR), we observed that the MytM gene was mainly expressed in circulating hemocytes and to a less extent in the mantle. In vivo challenge with bacteria or with the yeast, Candida albicans, did not increase the expression as measured by q-PCR in hemocytes. By contrast, injection of the filamentous fungus, Fusarium oxysporum, induced a sudden and strong increase of expression at 9h p.i. (stimulation index of 25.7 +- 2.1). Optimum stimulating dose was 104 spores of F. oxysporum per mussel. In the same samples, AMP mytilin and myticin showed no stimulation. Consequently, we hypothesized the existence of 2 different signal transduction pathways, one activated by bacteria and yeast, the other triggered by filamentous fungi. A second challenge performed with F. oxysporum 24 h after the first challenge induced an increase of MytM gene expression (stimulation index of 3.5 +- 1.7). However, this second increase was significantly lower than the first, suggesting less efficient response rather than significant protection

Frailty Index and incident mortality, hospitalization and institutionalization in Alzheimer's disease: data from the ICTUS study.

BACKGROUND: The identification of an objective evaluation of frailty capable of predicting adverse outcomes in Alzheimer's disease is increasingly discussed. The purpose of this study was to investigate whether the Frailty Index (FI) predicts hospitalization, institutionalization, and mortality in Alzheimer's disease patients. METHODS: A prospective multicenter cohort study (follow-up = 2 years) that included 1,191 participants with Alzheimer's disease was carried out. The outcomes of interest were incident hospitalization, institutionalization, and mortality. The FI was calculated as the ratio of actual to thirty potential deficits, that is, deficits presented by the participant divided by 30. Severity of dementia was assessed using the Clinical Dementia Rating score. Cox proportional hazard models were performed. RESULTS: Mean age of the study sample was 76.2 (SD = 7.6) years. A quadratic relationship of the FI with age was reported at baseline (R 2 = .045, p < .001). The FI showed a statistically significant association with mortality (age- and gender-adjusted hazard ratio [HR] = 1.019, 95% confidence interval [CI] = 1.002-1.037, p = .031) and hospitalization (age- and gender-adjusted HR = 1.017, 95% CI = 1.006-1.029, p = .004) and a borderline significance with institutionalization. When the Clinical Dementia Rating score was simultaneously included in the age- and gender-adjusted models, the FI confirmed its predictive capacity for hospitalization (HR = 1.019, 95% CI = 1.006-1.032, p = .004), whereas the Clinical Dementia Rating score was the strongest predictor for mortality (HR = 1.922, 95% CI = 1.256-2.941, p = .003) and institutionalization (HR = 1.955, 95%CI = 1.427-2.679, p < .001). CONCLUSIONS: The FI is a robust predictor of adverse outcomes even after the stage of the underlying dementia is considered. Future work should evaluate the clinical implementation of the FI in the assessment of demented individuals in order to improve the personalization of care

Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations

Background: Currently, association studies are analysed using statistical mixed models, with marker effects estimated by a linear transformation of genomic breeding values. The variances of marker effects are needed when performing the tests of association. However, approaches used to estimate the parameters rely on a prior variance or on a constant estimate of the additive variance. Alternatively, we propose a standardized test of association using the variance of each marker effect, which generally differ among each other. Random breeding values from a mixed model including fixed effects and a genomic covariance matrix are linearly transformed to estimate the marker effects. Results: The standardized test was neither conservative nor liberal with respect to type I error rate (false-positives), compared to a similar test using Predictor Error Variance, a method that was too conservative. Furthermore, genomic predictions are solved efficiently by the procedure, and the p-values are virtually identical to those calculated from tests for one marker effect at a time. Moreover, the standardized test reduces computing time and memory requirements. The following steps are used to locate genome segments displaying strong association. The marker with the highest − log(p-value) in each chromosome is selected, and the segment is expanded one Mb upstream and one Mb downstream of the marker. A genomic matrix is calculated using the information from those markers only, which is used as the variance-covariance of the segment effects in a model that also includes fixed effects and random genomic breeding values. The likelihood ratio is then calculated to test for the effect in every chromosome against a reduced model with fixed effects and genomic breeding values. In a case study with pigs, a significant segment from chromosome 6 explained 11% of total genetic variance. Conclusions: The standardized test of marker effects using their own variance helps in detecting specific genomic regions involved in the additive variance, and in reducing false positives. Moreover, genome scanning of candidate segments can be used in meta-analyses of genome-wide association studies, as it enables the detection of specific genome regions that affect an economically relevant trait when using multiple populations.Fil: Gualdron Duarte, Jose Luis. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bates, Ronald O.. Michigan State University; Estados UnidosFil: Ernst, Catherine W.. Michigan State University; Estados UnidosFil: Raney, Nancy E.. Michigan State University; Estados UnidosFil: Steibel, Juan P.. Michigan State University; Estados Unido

Prediction of breeding values with additive animal models for crosses from 2 populations

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