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dc.contributor.authorDelgado, Beatriz
dc.contributor.authorBach, Alex
dc.contributor.authorGuasch, Isabel
dc.contributor.authorGonzález, Carmen
dc.contributor.authorElcoso, Guillermo
dc.contributor.authorPryce, Jennie E.
dc.contributor.authorGonzalez-Recio, Oscar
dc.contributor.otherProducció Animalca
dc.date.accessioned2019-10-15T14:23:25Z
dc.date.available2019-10-15T14:23:25Z
dc.date.issued2019-01-09
dc.identifier.citationDelgado, Beatriz, Alex Bach, Isabel Guasch, Carmen González, Guillermo Elcoso, Jennie E. Pryce, and Oscar Gonzalez-Recio. 2019. "Whole Rumen Metagenome Sequencing Allows Classifying And Predicting Feed Efficiency And Intake Levels In Cattle". Scientific Reports 9 (1). Springer Nature. doi:10.1038/s41598-018-36673-w.ca
dc.identifier.issn2045-2322ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/499
dc.description.abstractThe current research was carried out to determine the associations between the rumen microbiota and traits related with feed efficiency in a Holstein cattle population (n = 30) using whole metagenome sequencing. Improving feed efficiency (FE) is important for a more sustainable livestock production. The variability for the efficiency of feed utilization in ruminants is partially controlled by the gastrointestinal microbiota. Modulating the microbiota composition can promote a more sustainable and efficient livestock. This study revealed that most efficient cows had larger relative abundance of Bacteroidetes (P = 0.041) and Prevotella (P = 0.003), while lower, but non-significant (P = 0.119), relative abundance of Firmicutes. Methanobacteria (P = 0.004) and Methanobrevibacter (P = 0.003) were also less abundant in the high-efficiency cows. A de novo metagenome assembly was carried out using de Bruijn graphs in MEGAHIT resulting in 496,375 contigs. An agnostic pre-selection of microbial contigs allowed high classification accuracy for FE and intake levels using hierarchical classification. These microbial contigs were also able to predict FE and intake levels with accuracy of 0.19 and 0.39, respectively, in an independent population (n = 31). Nonetheless, a larger potential accuracy up to 0.69 was foreseen in this study for datasets that allowed a larger statistical power. Enrichment analyses showed that genes within these contigs were mainly involved in fatty acids and cellulose degradation pathways. The findings indicated that there are differences between the microbiota compositions of high and low-efficiency animals both at the taxonomical and gene levels. These differences are even more evident in terms of intake levels. Some of these differences remain even between populations under different diets and environments, and can provide information on the feed utilization performance without information on the individual intake level.ca
dc.format.extent13ca
dc.language.isoengca
dc.publisherNature Researchca
dc.relation.ispartofScientific Reportsca
dc.rightsAttribution 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleWhole rumen metagenome sequencing allows classifying and predicting feed efficiency and intake levels in cattleca
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.projectIDMINECO/Programa Estatal de promoción del talento y su empleabilidad en I+D+I/PRX17-00044/ES/ /ca
dc.subject.udc575ca
dc.subject.udc59ca
dc.subject.udc619ca
dc.subject.udc636ca
dc.identifier.doihttps://doi.org/10.1038/s41598-018-36673-wca
dc.contributor.groupProducció de Remugantsca


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