ArticleGenetics, selection, evolution : GSE2023
Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.
Article in Genetics, selection, evolution : GSE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 12 citations in OpenAlex.
- Methane emissions in beef cattle: A review of measurements and mitigation strategies.Veterinary and animal science · 2026Review
- Microbiome Engineering in Dairy Cattle: A Critical Review of Strategies for Disease Resistance, Productivity, and Sustainable Farming.Veterinary sciences · 2026Review
- 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
- Influence of host genetics on the functional composition of the rumen metagenome in beef cattle.Journal of animal science · 2026Article
- The hologenome concept and its implications for animal breeding in the multi-omics Era.Genetics and molecular biology · 2026Article
- Prediction accuracy for feed intake and body weight gain using host genomic and rumen metagenomic data in beef cattle.Genetics, selection, evolution : GSE · 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
- Combining genomics and semen microbiome increases the accuracy of predicting bull prolificacy.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors at 4 institutions in 4 countries.
Funding
Abstract
backgroundRumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits.
resultsIncorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance.
conclusionsThis paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.