ArticleScientific reports2024
Revealing host genome-microbiome networks underlying feed efficiency in dairy cows.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Nutrigenomics in precision livestock and poultry farming: Enhancing productivity, welfare, and sustainability through gene-tailored diets.Veterinary and animal science · 2026Review
- Advancing climate-resilient livestock systems: Next-generation emission mitigation strategies and integrated technological innovations.Veterinary and animal science · 2026Review
- Influence of host genetics on the functional composition of the rumen metagenome in beef cattle.Journal of animal science · 2026Article
- Mechanisms and Applications of Gastrointestinal Microbiota-Metabolite Interactions in Ruminants: A Review.Microorganisms · 2025Review
- Quantitative genetics of microbiome-mediated traits.Evolution; international journal of organic evolution · 2025Article
- Dynamic Changes in Rumen Microbial Diversity and Community Composition Within Rumen Fluid in Response to Various Storage Temperatures and Preservation Times.Veterinary sciences · 2025Article
- Ruminant nutrition symposium: novel microbial solutions to optimize production efficiency in beef and dairy systems.Journal of animal science · 2025Review
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Authors and funding
12 authors.
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Abstract
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.
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