Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows
Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries)
Zingaretti, Laura M. (Centre de Recerca en Agrigenòmica)
Popova, Milka (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France))
Estellé, Jordi (Université Paris-Saclay. Institut National de la Recherche Agronomique. Génétique Animale et Biologie Intégrative (France))
Bernard, Aurelien (Université Clermont Auvergne. Institut National de la Recherche Agronomique. VetAgro Sup (France))
Pons, Nicolas (Institut National de la Recherche Agronomique. Metagenopolis Unit (France))
Bellot, Pau (Centre de Recerca en Agrigenòmica)
Mach Casellas, Núria (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France))
Rau, Andrea (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France))
Roume, Hugo (Institut National de la Recherche Agronomique. Metagenopolis Unit (France))
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Faverdin, Philippe (Institut National de la Recherche Agronomique (França))
Edouard, Nadège (Institut National de la Recherche Agronomique (França))
Ehrlich, Dusko (Institut National de la Recherche Agronomique. Metagenopolis Unit (France))
Morgavi, Diego P. (Université Clermont Auvergne. Institut National de la Recherche Agronomique (France))
Renand, Gilles (Université Paris-Saclay. Institut National de la Recherche Agronomique. AgroParisTech (France))

Data:	2020
Resum:	Mitigation of greenhouse gas emissions is relevant for reducing the environmental impact of ruminant production. In this study, the rumen microbiome from Holstein cows was characterized through a combination of 16S rRNA gene and shotgun metagenomic sequencing. Methane production (CH4) and dry matter intake (DMI) were individually measured over 4-6 weeks to calculate the CH4 yield (CH4y = CH4/DMI) per cow. We implemented a combination of clustering, multivariate and mixed model analyses to identify a set of operational taxonomic unit (OTU) jointly associated with CH4y and the structure of ruminal microbial communities. Three ruminotype clusters (R1, R2 and R3) were identified, and R2 was associated with higher CH4y. The taxonomic composition on R2 had lower abundance of Succinivibrionaceae and Methanosphaera, and higher abundance of Ruminococcaceae, Christensenellaceae and Lachnospiraceae. Metagenomic data confirmed the lower abundance of Succinivibrionaceae and Methanosphaera in R2 and identified genera (Fibrobacter and unclassified Bacteroidales) not highlighted by metataxonomic analysis. In addition, the functional metagenomic analysis revealed that samples classified in cluster R2 were overrepresented by genes coding for KEGG modules associated with methanogenesis, including a significant relative abundance of the methyl-coenzyme M reductase enzyme. Based on the cluster assignment, we applied a sparse partial leastsquares discriminant analysis at the taxonomic and functional levels. In addition, we implemented a sPLS regression model using the phenotypic variation of CH4y. By combining these two approaches, we identified 86 discriminant bacterial OTUs, notably including families linked to CH4 emission such as Succinivibrionaceae, Ruminococcaceae, Christensenellaceae, Lachnospiraceae and Rikenellaceae. These selected OTUs explained 24% of the CH4y phenotypic variance, whereas the host genome contribution was ~14%. In summary, we identified rumen microbial biomarkers associated with the methane production of dairy cows; these biomarkers could be used for targeted methane-reduction selection programmes in the dairy cattle industry provided they are heritable.
Ajuts:	European Commission 665919 Ministerio de Economía y Competitividad SEV-2015-0533
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Metagenomics ; Metataxonomics ; Methane emission ; Microbial biomarker
Publicat a:	Journal of Animal Breeding and Genetics, Vol. 137, Issue 1 (January 2020) , p. 49-59, ISSN 1439-0388

DOI: 10.1111/jbg.12427
PMID: 31418488

11 p, 594.5 KB

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