ArticlePloS one2013
Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed.
- Reliable enteric methane prediction from the cattle (Bos taurus) rumen microbiome.Communications biology · 2026Article
- Short communication: oral microbiome as a potential proxy for methane emissions in grazing tropical composite beef cattle.Journal of animal science · 2026Article
- Impact of reducing metagenomic sequencing depth on phenotypic prediction accuracy of feed intake and average daily gain in beef cattle.Journal of animal science · 2026Article
- Article
- Prediction accuracy for feed intake and body weight gain using host genomic and rumen metagenomic data in beef cattle.Genetics, selection, evolution : GSE · 2025Article
- Metagenomic Analysis Revealed Significant Changes in the Beef Cattle Rectum Microbiome Under Fescue Toxicosis.Biology · 2025Article
- Improving genomic prediction accuracy for methane emission and feed efficiency in sheep: integrating rumen microbial PCA with host genomic variation using neural network GBLUP (NN-GBLUP).Genetics, selection, evolution : GSE · 2025Article
- Rumen metagenome profiles are heritable and rank the New Zealand national sheep flock for enteric methane emissions.Genetics, selection, evolution : GSE · 2025Article
- Investigating the establishment of the rumen and oral bacterial communities in beef cattle and assessing the applicability of using the oral bacterial community composition as a proxy for rumen bacterial community structure in cattle.Frontiers in microbiology · 2025Article
- Genomic and Gut Microbiome Evaluations of Growth and Feed Efficiency Traits in Broilers.Animals : an open access journal from MDPI · 2024Article
- Rumen microbiome and fat deposition in sheep: insights from a bidirectional mendelian randomization study.NPJ biofilms and microbiomes · 2024Article
- Parameter Estimation of Host Genomic and Gut Microbiota Contribution to Growth and Feed Efficiency Traits in Meat Rabbits.Microorganisms · 2024Article
- An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows.Animal microbiome · 2024Article
- Article
- Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.Genetics, selection, evolution : GSE · 2023Article
- On the holobiont 'predictome' of immunocompetence in pigs.Genetics, selection, evolution : GSE · 2023Article
- Article
- Estimation of Complex-Trait Prediction Accuracy from the Different Holo-Omics Interaction Models.Genes · 2022Article
- Exploring methods to summarize gut microbiota composition for microbiability estimation and phenotypic prediction in swine.Journal of animal science · 2022Article
- Dynamic changes in fecal bacterial microbiota of dairy cattle across the production line.BMC microbiology · 2022Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle.
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