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A large database linking the rumen bacterial composition and milk traits in Lacaune sheep
Ruminants are able to produce food for human consumption from plants, thanks to rumen bacteria. Bacteria are able to transform feed to microbial proteins and to biohydrogenate unsaturated fatty acids, contributing directly to fine milk composition. The database consists of daily records of milk yiel...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825406/ https://www.ncbi.nlm.nih.gov/pubmed/36611050 http://dx.doi.org/10.1038/s41597-022-01912-3 |
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author | Martinez Boggio, Guillermo Marie-Etancelin, Christel Menras, Jean-Marie Tomas, Regis Chemit, Marie-Luce Gabinaud, Béatrice Pascal, Géraldine Meynadier, Annabelle |
author_facet | Martinez Boggio, Guillermo Marie-Etancelin, Christel Menras, Jean-Marie Tomas, Regis Chemit, Marie-Luce Gabinaud, Béatrice Pascal, Géraldine Meynadier, Annabelle |
author_sort | Martinez Boggio, Guillermo |
collection | PubMed |
description | Ruminants are able to produce food for human consumption from plants, thanks to rumen bacteria. Bacteria are able to transform feed to microbial proteins and to biohydrogenate unsaturated fatty acids, contributing directly to fine milk composition. The database consists of daily records of milk yield, somatic cell score and 17 milk components such as fatty acids and proteins from 795 Lacaune dairy ewes. Ruminal samples were extracted from ewes using a gastric tube and sequenced to determine the bacterial composition by metabarcoding 16S rRNA gene on a next-generation sequencing platform. From bioinformatics analysis, 9,536,442 sequences were retained and re-grouped into 2,059 affiliated OTUs, represented by 751 to 168,617 sequences. Overall, 2,059 OTUs from 795 samples were attributed to 11 phyla. The most representative phyla were Bacteroidota (50.6%) and Firmicutes (43.6%), and the most abundant families were Prevotellaceae (37.9%), Lachnospiraceae (18.1%), Ruminococcaceae (8.97%). Both shared datasets will be useful for researchers to study the link between rumen bacteria and milk traits and to propose solutions to improve animal production and health. |
format | Online Article Text |
id | pubmed-9825406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98254062023-01-09 A large database linking the rumen bacterial composition and milk traits in Lacaune sheep Martinez Boggio, Guillermo Marie-Etancelin, Christel Menras, Jean-Marie Tomas, Regis Chemit, Marie-Luce Gabinaud, Béatrice Pascal, Géraldine Meynadier, Annabelle Sci Data Data Descriptor Ruminants are able to produce food for human consumption from plants, thanks to rumen bacteria. Bacteria are able to transform feed to microbial proteins and to biohydrogenate unsaturated fatty acids, contributing directly to fine milk composition. The database consists of daily records of milk yield, somatic cell score and 17 milk components such as fatty acids and proteins from 795 Lacaune dairy ewes. Ruminal samples were extracted from ewes using a gastric tube and sequenced to determine the bacterial composition by metabarcoding 16S rRNA gene on a next-generation sequencing platform. From bioinformatics analysis, 9,536,442 sequences were retained and re-grouped into 2,059 affiliated OTUs, represented by 751 to 168,617 sequences. Overall, 2,059 OTUs from 795 samples were attributed to 11 phyla. The most representative phyla were Bacteroidota (50.6%) and Firmicutes (43.6%), and the most abundant families were Prevotellaceae (37.9%), Lachnospiraceae (18.1%), Ruminococcaceae (8.97%). Both shared datasets will be useful for researchers to study the link between rumen bacteria and milk traits and to propose solutions to improve animal production and health. Nature Publishing Group UK 2023-01-07 /pmc/articles/PMC9825406/ /pubmed/36611050 http://dx.doi.org/10.1038/s41597-022-01912-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Martinez Boggio, Guillermo Marie-Etancelin, Christel Menras, Jean-Marie Tomas, Regis Chemit, Marie-Luce Gabinaud, Béatrice Pascal, Géraldine Meynadier, Annabelle A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title | A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title_full | A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title_fullStr | A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title_full_unstemmed | A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title_short | A large database linking the rumen bacterial composition and milk traits in Lacaune sheep |
title_sort | large database linking the rumen bacterial composition and milk traits in lacaune sheep |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825406/ https://www.ncbi.nlm.nih.gov/pubmed/36611050 http://dx.doi.org/10.1038/s41597-022-01912-3 |
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