Artículo

Varona, L., Munilla Leguizamón, S., Mouresan, E. F., González Rodríguez, A., Moreno, C., & Altarriba, J. (2015)"A bayesian model for the analysis of transgenerational epigenetic variation". G3: Genes, Genomes, Genetics,5, (4),p.477-485

Registro:

Documento:
Artículo
Título en inglés:
A bayesian model for the analysis of transgenerational epigenetic variation
Autor/es:
Varona, Luis; Munilla Leguizamón, Sebastián; Mouresan, Elena Flavia; González Rodríguez, Aldemar; Moreno, Carlos; Altarriba, Juan
Año:
2015
Título revista:
G3: Genes, Genomes, Genetics
ISSN:
2160-1836
Volumen:
5
Número:
4
Páginas:
477-485
Temas:
TRANSGENERATIONAL EPIGENETIC VARIATION; SIMULATION; RESEMBLANCE BETWEEN RELATIVES; QUANTITATIVE GENETICS; LINEAR SYSTEM; GENETIC VARIANCE; GENETIC VARIABILITY; GENETIC DATABASE; GENETIC ASSOCIATION; GENETIC ALGORITHM; EPIGENETICS; BOS; BEEF CATTLE; BAYESIAN ANALYSIS; BAYES THEOREM
Idioma:
Inglés
URL al Editor:

Resumen:

Epigenetics has become one of the major areas of biological research. However, the degree of phenotypic variability that is explained by epigenetic processes still remains unclear. From a quantitative genetics perspective, the estimation of variance components is achieved by means of the information provided by the resemblance between relatives. In a previous study, this resemblance was described as a function of the epigenetic variance component and a reset coefficient that indicates the rate of dissipation of epigenetic marks across generations. Given these assumptions, we propose a Bayesian mixed model methodology that allows the estimation of epigenetic variance from a genealogical and phenotypic database. The methodology is based on the development of a T matrix of epigenetic relationships that depends on the reset coefficient. In addition, we present a simple procedure for the calculation of the inverse of this matrix (T-1) and a Gibbs sampler algorithm that obtains posterior estimates of all the unknowns in the model. The new procedure was used with two simulated data sets and with a beef cattle database. In the simulated populations, the results of the analysis provided marginal posterior distributions that included the population parameters in the regions of highest posterior density. In the case of the beef cattle dataset, the posterior estimate of transgenerational epigenetic variability was very low and a model comparison test indicated that a model that did not included it was the most plausible.

Citación:

---------- APA ----------

Varona, L., Munilla Leguizamón, S., Mouresan, E. F., González Rodríguez, A., Moreno, C., & Altarriba, J. (2015). A bayesian model for the analysis of transgenerational epigenetic variation. G3: Genes, Genomes, Genetics,5, (4),p.477-485
10.1534/g3.115.016725

---------- CHICAGO ----------

Varona, Luis, Munilla Leguizamón, Sebastián, Mouresan, Elena Flavia, González Rodríguez, Aldemar, Moreno, Carlos, Altarriba, Juan. 2015. "A bayesian model for the analysis of transgenerational epigenetic variation". G3: Genes, Genomes, Genetics 5, no.4:477-485.
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http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2015varona