Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle - Genetics Selection Evolution Access content directly
Journal Articles Genetics Selection Evolution Year : 2024

Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

Marina Martínez-Álvaro
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Jennifer Mattock
  • Function : Author
Óscar González-Recio
  • Function : Author
Alejandro Saborío-Montero
  • Function : Author
Ziqing Weng
  • Function : Author
Joana Lima
  • Function : Author
Carol-Anne Duthie
  • Function : Author
Richard Dewhurst
  • Function : Author
Matthew A. Cleveland
  • Function : Author
Mick Watson
  • Function : Author
Rainer Roehe
  • Function : Correspondent author
  • PersonId : 969776

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Abstract

AbstractBackgroundGrowth rate is an important component of feed conversion efficiency in cattle and varies across the different stages of the finishing period. The metabolic effect of the rumen microbiome is essential for cattle growth, and investigating the genomic and microbial factors that underlie this temporal variation can help maximize feed conversion efficiency at each growth stage.ResultsBy analysing longitudinal body weights during the finishing period and genomic and metagenomic data from 359 beef cattle, our study demonstrates that the influence of the host genome on the functional rumen microbiome contributes to the temporal variation in average daily gain (ADG) in different months (ADG1, ADG2, ADG3, ADG4). Five hundred and thirty-three additive log-ratio transformed microbial genes (alr-MG) had non-zero genomic correlations (rg) with at least one ADG-trait (ranging from |0.21| to |0.42|). Only a few alr-MG correlated with more than one ADG-trait, which suggests that a differential host-microbiome determinism underlies ADG at different stages. These alr-MG were involved in ribosomal biosynthesis, energy processes, sulphur and aminoacid metabolism and transport, or lipopolysaccharide signalling, among others. We selected two alternative subsets of 32 alr-MG that had a non-uniform or a uniform rg sign with all the ADG-traits, regardless of the rg magnitude, and used them to develop a microbiome-driven breeding strategy based on alr-MG only, or combined with ADG-traits, which was aimed at shaping the rumen microbiome towards increased ADG at all finishing stages. Combining alr-MG information with ADG records increased prediction accuracy of genomic estimated breeding values (GEBV) by 11 to 22% relative to the direct breeding strategy (using ADG-traits only), whereas using microbiome information, only, achieved lower accuracies (from 7 to 41%). Predicted selection responses varied consistently with accuracies. Restricting alr-MG based on their rg sign (uniform subset) did not yield a gain in the predicted response compared to the non-uniform subset, which is explained by the absence of alr-MG showing non-zero rg at least with more than one of the ADG-traits.ConclusionsOur work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.
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Origin : Publication funded by an institution
Origin : Publication funded by an institution
Origin : Publication funded by an institution
Origin : Publication funded by an institution

Dates and versions

hal-04508405 , version 1 (18-03-2024)

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Marina Martínez-Álvaro, Jennifer Mattock, Óscar González-Recio, Alejandro Saborío-Montero, Ziqing Weng, et al.. Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle. Genetics Selection Evolution, 2024, 56 (1), pp.19. ⟨10.1186/s12711-024-00887-6⟩. ⟨hal-04508405⟩
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