Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle
Abstract Background Growth 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 unde...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | deu |
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BMC
2024-03-01
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| Series: | Genetics Selection Evolution |
| Online Access: | https://doi.org/10.1186/s12711-024-00887-6 |
| _version_ | 1797259593123889152 |
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| author | Marina Martínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Saborío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A. Cleveland Mick Watson Rainer Roehe |
| author_facet | Marina Martínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Saborío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A. Cleveland Mick Watson Rainer Roehe |
| author_sort | Marina Martínez-Álvaro |
| collection | DOAJ |
| description | Abstract Background Growth 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. Results By 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. Conclusions Our 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. |
| first_indexed | 2024-04-24T23:11:53Z |
| format | Article |
| id | doaj.art-b6a533dcd90b440daae8e7a8f09f75ae |
| institution | Directory Open Access Journal |
| issn | 1297-9686 |
| language | deu |
| last_indexed | 2024-04-24T23:11:53Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Genetics Selection Evolution |
| spelling | doaj.art-b6a533dcd90b440daae8e7a8f09f75ae2024-03-17T12:11:40ZdeuBMCGenetics Selection Evolution1297-96862024-03-0156111610.1186/s12711-024-00887-6Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattleMarina Martínez-Álvaro0Jennifer Mattock1Óscar González-Recio2Alejandro Saborío-Montero3Ziqing Weng4Joana Lima5Carol-Anne Duthie6Richard Dewhurst7Matthew A. Cleveland8Mick Watson9Rainer Roehe10Institute of Animal Science and Technology, Universitat Politècnica de ValénciaScotland’s Rural CollegeInstituto Nacional de Investigaciones AgrariasEscuela de Zootecnia y Centro de Investigación en Nutrición Animal, Universidad de Costa RicaGenus plcScotland’s Rural CollegeScotland’s Rural CollegeScotland’s Rural CollegeGenus plcScotland’s Rural CollegeScotland’s Rural CollegeAbstract Background Growth 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. Results By 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. Conclusions Our 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.https://doi.org/10.1186/s12711-024-00887-6 |
| spellingShingle | Marina Martínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Saborío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A. Cleveland Mick Watson Rainer Roehe Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle Genetics Selection Evolution |
| title | Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle |
| title_full | Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle |
| title_fullStr | Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle |
| title_full_unstemmed | Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle |
| title_short | Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle |
| title_sort | including microbiome information in a multi trait genomic evaluation a case study on longitudinal growth performance in beef cattle |
| url | https://doi.org/10.1186/s12711-024-00887-6 |
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