Revealing host genome-microbiome networks underlying feed efficiency in dairy cows.
Bayesian network
Dry matter intake
Residual feed intake
Rumen microbiome
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
30 10 2024
30 10 2024
Historique:
received:
01
08
2024
accepted:
25
10
2024
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
epublish
Résumé
Ruminants have the ability to digest human-inedible plant materials, due to the symbiotic relationship with the rumen microbiota. Rumen microbes supply short chain fatty acids, amino acids, and vitamins to dairy cows that are used for maintenance, growth, and lactation functions. The main goal of this study was to investigate gene-microbiome networks underlying feed efficiency traits by integrating genotypic, microbial, and phenotypic data from lactating dairy cows. Data consisted of dry matter intake (DMI), net energy secreted in milk, and residual feed intake (RFI) records, SNP genotype, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows. We first assessed marginal associations between genotypes and phenotypic and microbial traits through genomic scans, and then, in regions with multiple significant hits, we assessed gene-microbiome-phenotype networks using causal structural learning algorithms. We found significant regions co-localizing the rumen microbiome and feed efficiency traits. Interestingly, we found three types of network relationships: (1) the cow genome directly affects both rumen microbial abundances and feed efficiency traits; (2) the cow genome (Chr3: 116.5 Mb) indirectly affects RFI, mediated by the abundance of Syntrophococcus, Prevotella, and an unknown genus of Class Bacilli; and (3) the cow genome (Chr7: 52.8 Mb and Chr11: 6.1-6.2 Mb) affects the abundance of Rikenellaceae RC9 gut group mediated by DMI. Our findings shed light on how the host genome acts directly and indirectly on the rumen microbiome and feed efficiency traits and the potential benefits of the inclusion of specific microbes in selection indexes or as correlated traits in breeding programs. Overall, the multistep approach described here, combining whole-genome scans and causal network reconstruction, allows us to reveal the relationship between genome and microbiome underlying dairy cow feed efficiency.
Identifiants
pubmed: 39472728
doi: 10.1038/s41598-024-77782-z
pii: 10.1038/s41598-024-77782-z
doi:
Substances chimiques
RNA, Ribosomal, 16S
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
26060Informations de copyright
© 2024. The Author(s).
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