title: A Bayesian model for the analysis of transgenerational epigenetic variation.
abstract: 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.
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain Instituto de Biocomputación y Física de los Sistemas Complejos (BIFI), Universidad de Zaragoza, 50018, Zaragoza, Spain lvarona@unizar.es.
authors.forename: Luis
authors.identifier: http://orcid.org/0000-0001-6256-5478
authors.initials: L
authors.lastname: Varona
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain Departamento de Producción Animal, Facultad de Agronomía, Universidad de Buenos Aires, 1417, Ciudad Autónoma de Buenos Aires, Argentina.
authors.forename: Sebastián
authors.initials: S
authors.lastname: Munilla
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain.
authors.forename: Elena Flavia
authors.initials: EF
authors.lastname: Mouresan
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain.
authors.forename: Aldemar
authors.initials: A
authors.lastname: González-Rodríguez
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain Instituto de Biocomputación y Física de los Sistemas Complejos (BIFI), Universidad de Zaragoza, 50018, Zaragoza, Spain.
authors.forename: Carlos
authors.initials: C
authors.lastname: Moreno
authors.affiliation: Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain Instituto de Biocomputación y Física de los Sistemas Complejos (BIFI), Universidad de Zaragoza, 50018, Zaragoza, Spain.
authors.forename: Juan
authors.initials: J
authors.lastname: Altarriba
mesh_terms: D001499:Bayes Theorem; D057890:Epigenomics; D014644:Genetic Variation; D008962:Models, Theoretical; D010641:Phenotype
keywords: Bayesian analysis; epigenetics; genetic variance; resemblance between relatives