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dc.contributor.authorVelasco-Galilea, María
dc.contributor.authorPiles, Miriam
dc.contributor.authorRamayo-Caldas, Yuliaxis
dc.contributor.authorVarona, Luis
dc.contributor.authorSánchez, Juan Pablo
dc.contributor.otherProducció Animalca
dc.date.accessioned2022-08-01T07:43:38Z
dc.date.available2022-08-01T07:43:38Z
dc.date.issued2022-06-27
dc.identifier.citationVelasco-Galilea, María, Miriam Piles, Yuliaxis Ramayo-Caldas, Luis Varona, and Juan Pablo Sánchez. 2022. "Use Of Bayes Factors To Evaluate The Effects Of Host Genetics, Litter And Cage On The Rabbit Cecal Microbiota". Genetics Selection Evolution 54 (1). doi:10.1186/s12711-022-00738-2.ca
dc.identifier.issn0999-193Xca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/1826
dc.description.abstractBackground The rabbit cecum hosts and interacts with a complex microbial ecosystem that contributes to the variation of traits of economic interest. Although the influence of host genetics on microbial diversity and specific microbial taxa has been studied in several species (e.g., humans, pigs, or cattle), it has not been investigated in rabbits. Using a Bayes factor approach, the aim of this study was to dissect the effects of host genetics, litter and cage on 984 microbial traits that are representative of the rabbit microbiota. Results Analysis of 16S rDNA sequences of cecal microbiota from 425 rabbits resulted in the relative abundances of 29 genera, 951 operational taxonomic units (OTU), and four microbial alpha-diversity indices. Each of these microbial traits was adjusted with mixed linear and zero-inflated Poisson (ZIP) models, which all included additive genetic, litter and cage effects, and body weight at weaning and batch as systematic factors. The marginal posterior distributions of the model parameters were estimated using MCMC Bayesian procedures. The deviance information criterion (DIC) was used for model comparison regarding the statistical distribution of the data (normal or ZIP), and the Bayes factor was computed as a measure of the strength of evidence in favor of the host genetics, litter, and cage effects on microbial traits. According to DIC, all microbial traits were better adjusted with the linear model except for the OTU present in less than 10% of the animals, and for 25 of the 43 OTU with a frequency between 10 and 25%. On a global scale, the Bayes factor revealed substantial evidence in favor of the genetic control of the number of observed OTU and Shannon indices. At the taxon-specific level, significant proportions of the OTU and relative abundances of genera were influenced by additive genetic, litter, and cage effects. Several members of the genera Bacteroides and Parabacteroides were strongly influenced by the host genetics and nursing environment, whereas the family S24-7 and the genus Ruminococcus were strongly influenced by cage effects. Conclusions This study demonstrates that host genetics shapes the overall rabbit cecal microbial diversity and that a significant proportion of the taxa is influenced either by host genetics or environmental factors, such as litter and/or cage.ca
dc.format.extent15ca
dc.language.isoengca
dc.publisherBMCca
dc.relation.ispartofGenetics Selection Evolutionca
dc.rightsAttribution 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleUse of Bayes factors to evaluate the effects of host genetics, litter and cage on the rabbit cecal microbiotaca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.relation.projectIDINIA/Programa Nacional de Proyectos de Investigación Fundamental/RTA2011-00064-00-00/ES/Mejora genética de la eficacia alimentaria en especies prolíficas/ca
dc.relation.projectIDEC/H2020/633531/EU/Adapting the feed, the animal and the feeding techniques to improve the efficiency and sustainability of monogastric livestock production systems/Feed-a-Geneca
dc.relation.projectIDMICIU/Programa Estatal de I+D+I orientada a los retos de la sociedad/RTI2018-097610-R-I00ES/MEJORA DE LA EFECTIVIDAD Y LA VIABILIDAD DE LOS PROGRAMAS DE SELECCION GENETICA PARA AUMENTAR LA EFICIENCIA ALIMENTARIA DE ESPECIES PROLIFICA/ca
dc.relation.projectIDINIA/Programa Estatal de I+D+I orientada a los retos de la sociedad/RTA2014-00015-C02-01/ES/Mejora de la eficiencia alimentaria en cerdos y conejos. Determinismo genético y estrategias de selección/ca
dc.relation.projectIDMICIU-FEDER/Programa Estatal de promoción del talento y su empleabilidad en I+D+I/RYC2019-027244-I/ES/ /ca
dc.relation.projectIDMICIU/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I/CEX2019-000902-S/ES/ /ca
dc.relation.projectIDMICIU/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/PID2019-108829RB-I00/ES/La belleza de lo profundo: Aplicaciones del deep learning a la predicción genómica/ca
dc.subject.udc636ca
dc.identifier.doihttps://doi.org/10.1186/s12711-022-00738-2ca
dc.contributor.groupGenètica i Millora Animalca


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Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/
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