title: Bayesian  inference to study genetic control of resistance to gray leaf spot in maize.
abstract: Gray  leaf spot (GLS) is a major maize disease in Brazil that significantly affects  grain production. We used Bayesian inference to investigate the nature and  magnitude of gene effects related to GLS resistance by evaluation of  contrasting lines and segregating populations. The experiment was arranged in a  randomized block design with three replications and the mean values were  analyzed using a Bayesian shrinkage approach. Additive-dominant and epistatic  effects and their variances were adjusted in an over-parametrized model.  Bayesian shrinkage analysis showed to be an excellent approach to handle complex  models in the study of genetic control in GLS, since this approach allows to  handle overparametrized models (main and epistatic effects) without using  model-selection methods. Genetic control of GLS resistance was predominantly  additive, with insignificant influence of dominance and epistasis effects.
authors.affiliation: Departamento de Biologia, Universidade Federal de Lavras, Lavras, MG, Brasil. marciobalestre@hotmail.com
authors.forename: M
authors.initials: M
authors.lastname: Balestre
authors.forename: R G
authors.initials: RG
authors.lastname: Von Pinho
authors.forename: A H
authors.initials: AH
authors.lastname: Brito
mesh_terms: D001203:Ascomycota / Q000472:pathogenicity; D001499:Bayes Theorem; D060467:Disease Resistance / Q000235:genetics*; D009181:Mycoses / Q000473:pathology; D010935:Plant Diseases / Q000235:genetics*; D018515:Plant Leaves / Q000235:genetics* / Q000382:microbiology; D003313:Zea mays / Q000235:genetics* / Q000382:microbiology