Estimación de varianza epigenética transgeneracional
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L. Varona [1] ; S. Munilla [1] ; E.F. Mouresan [1] ; A. Gonzalez Rodriguez [1] ; C. Moreno [1] ; J. Altarriba [1]
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[1] Universidad de Zaragoza
Universidad de Zaragoza
Zaragoza, España
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- Localización: XVI Jornadas sobre Producción Animal: 19 y 20 de mayo de 2015, Zaragoza / Javier Álvarez Rodríguez (aut.), Begoña Panea Doblado (aut.), Jorge Hugo Calvo Lacosta (aut.), Mireia Blanco Alibés (aut.), José Alfonso Abecia Martínez (aut.), Daniel Villalba Mata (aut.), María Ángeles Latorre Górriz (aut.), Vol. 2, 2015, ISBN 978-84-606-7969-1, págs. 495-497
- Idioma: español
- Títulos paralelos:
- Epigenetic variance component estimation
- Enlaces
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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 a beef cattle database. 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.
