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Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study

dc.creatorSaborío Montero, Alejandro
dc.creatorGutiérrez Rivas, Mónica
dc.creatorGarcía Rodríguez, Aser
dc.creatorAtxaerandio Galdos, Raquel
dc.creatorGoiri Zamora, Idoia
dc.creatorLópez de Maturana, Evangelina
dc.creatorJiménez Montero, José Antonio
dc.creatorAlenda Jiménez, Rafael
dc.creatorGonzález Recio, Oscar
dc.date.accessioned2023-02-23T14:17:45Z
dc.date.available2023-02-23T14:17:45Z
dc.date.issued2019-09-18
dc.description.abstractThe advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host–metagenome–phenotype relationship. A non‐recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH4) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north‐west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian® NG infrared gas monitor from Edinburgh Sensors during cow's visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH4. Heritability of CH4 was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH4 ranged from −0.76 to 0.65 in the non‐recursive bivariate model and from −0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen's whole metagenome recursively regulates methane emissions in dairy cows and that both CH4 and the microbiota compositions are partially controlled by the host genotype.es
dc.description.procedenceUCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de Zootecniaes
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA)es
dc.description.sponsorshipNational plan of research, development and innovation 2013‐2020, Grant/ Award Number: RTA2015‐0022‐CO3 (METALGEN)es
dc.identifier.citationhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jbg.12444
dc.identifier.doihttps://doi.org/10.1111/jbg.12444
dc.identifier.issn1439-0388
dc.identifier.urihttps://hdl.handle.net/10669/88223
dc.language.isoeng
dc.rightsacceso abierto
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceJournal of Animal Breeding and Genetics 00: 2019es
dc.subjectGenetic correlationes
dc.subjectHeritabilityes
dc.subjectMetagenomees
dc.subjectGREENHOUSE GAS EMISSIONSes
dc.subjectRecursive modeles
dc.subjectSTRUCTURAL EQUATION MODELes
dc.subjectCATTLE FARMINGes
dc.subjectDAIRY INDUSTRYes
dc.titleStructural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of studyes
dc.typeartículo originales

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