Evidence map›Paper›PMID 37723422›Full record

ArticleBMC genomics2023

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host.

Melanie K Hess, Hannah E Hodgkinson, Andrew S Hess, Larissa Zetouni, Juliana C C Budel, Hannah Henry, Alistair Donaldson, Timothy P Bilton, Tracey C van Stijn, Michelle R Kirk and 12 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Phenotyping fatty acids and theVeterinary and animal science · 2026
    Article
  2. Heritability of theFrontiers in plant science · 2026
    Article
  3. Article
  4. Article
  5. Characterization of the Ruminal Microbiome of Water BuffaloesAnimals : an open access journal from MDPI · 2023
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 3 institutions in 5 countries.

Melanie K HessAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand. melanie.k.hess@gmail.com.
Hannah E HodgkinsonAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Andrew S HessAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Larissa ZetouniAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Juliana C C BudelAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Hannah HenryAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Alistair DonaldsonNSW Department of Primary Industries, University of New England, Armidale, 2351, Australia.
Timothy P BiltonAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Tracey C van StijnAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Michelle R KirkAgResearch Ltd., Grasslands Research Centre, Private Bag 11,008, Palmerston North, 4410, New Zealand.
Ken G DoddsAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Rudiger BrauningAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Alan F McCullochAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Sharon M HickeyAgResearch Ltd., Ruakura Research Centre, Private Bag 3115, Hamilton, 3214, New Zealand.
Patricia L JohnsonAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Arjan JonkerAgResearch Ltd., Grasslands Research Centre, Private Bag 11,008, Palmerston North, 4410, New Zealand.
Nickolas MortonTe Pūnaha Matatini, University of Auckland, Auckland, 1010, New Zealand.
Shaun HendyTe Pūnaha Matatini, University of Auckland, Auckland, 1010, New Zealand.
V Hutton OddyNSW Department of Primary Industries, University of New England, Armidale, 2351, Australia.
Peter H JanssenAgResearch Ltd., Grasslands Research Centre, Private Bag 11,008, Palmerston North, 4410, New Zealand.
John C McEwanAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
Suzanne J RoweAgResearch Ltd., Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
AgResearch · NZUniversity of Auckland · NZUniversity of New England · AU

Funding

AgResearch Curiosity FundLivestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gasses SOW14-AGR-GPLER-SP5-SRMeat and Livestock Australia and the Australian Commonwealth Government 119400343Ministry of Business, Innovation and Employment C10X1306New Zealand Agricultural Greenhouse Gas Research Centre Breeding low emitting ruminants MET5.1
6 · The paper itself

Abstract

backgroundProducing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible.

resultsMetagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets.

conclusionsVariation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Indexed as

MetagenomeMicrobiotaAnimalsLivestockMethaneRumenSheepMethaneGeneticsGenotyping-by-sequencingMetagenomeReference basedReference freeRestriction enzyme reduced representation sequencingRumen microbiome

Identifiers

PMID37723422
PMCPMC10506323
OpenAlexW4386839650

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.