4.7 Article

The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-99028-y

Keywords

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Funding

  1. INIA project [RTA2011-00064-00-00]
  2. European Union's H2020 program [633531]
  3. Spanish project [RTI2018-097610R-I00]
  4. Formacion de Personal Investigador (FPI) pre-doctoral fellowship from INIA
  5. Ramon y Cajal post-doctoral fellowship from the Spanish Ministry of Science and Innovation [RYC2019-027244-I]
  6. [RTA2014-00015-C2-01]

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This study investigated the impact of gut microbiota on rabbit feed efficiency and found that including microbial information in models can improve the prediction of complex phenotypes such as rabbit growth and feed efficiency.
Gut microbiota plays an important role in nutrient absorption and could impact rabbit feed efficiency. This study aims at investigating such impact by evaluating the value added by microbial information for predicting individual growth and cage phenotypes related to feed efficiency. The dataset comprised individual average daily gain and cage-average daily feed intake from 425 meat rabbits, in which cecal microbiota was assessed, and their cage mates. Despite microbiota was not measured in all animals, consideration of pedigree relationships with mixed models allowed the study of cage-average traits. The inclusion of microbial information into certain mixed models increased their predictive ability up to 20% and 46% for cage-average feed efficiency and individual growth traits, respectively. These gains were associated with large microbiability estimates and with reductions in the heritability estimates. However, large microbiabililty estimates were also obtained with certain models but without any improvement in their predictive ability. A large proportion of OTUs seems to be responsible for the prediction improvement in growth and feed efficiency traits, although specific OTUs taxonomically assigned to 5 different phyla have a higher weight. Rabbit growth and feed efficiency are influenced by host cecal microbiota, thus considering microbial information in models improves the prediction of these complex phenotypes.

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