Evidence map›Paper›PMID 42426588›Full record

ArticleGenetics, selection, evolution : GSE2026

Optimisation of selection for methane mitigation by integrating production traits with ruminal microbiome-driven breeding in beef cattle.

Tuan Q Nguyen, Marina Martínez-Álvaro, Joana Lima, Gregor Gorjanc, Matthew A Cleveland, Rainer Roehe

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Tuan Q NguyenScotland's Rural College, Peter Wilson Building, The King's Buildings, West Mains Road, Edinburgh, EH9 3JG, UK. Tuan.Nguyen@sruc.ac.uk.
Marina Martínez-ÁlvaroInstitute of Animal Science and Technology, Universitat Politècnica de Valéncia, 46010, Valencia, Spain.
Joana LimaScotland's Rural College, Peter Wilson Building, The King's Buildings, West Mains Road, Edinburgh, EH9 3JG, UK.
Gregor GorjancThe Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Matthew A ClevelandGenus Plc, DeForest, WI, 53532, USA.
Rainer RoeheScotland's Rural College, Peter Wilson Building, The King's Buildings, West Mains Road, Edinburgh, EH9 3JG, UK. Rainer.Roehe@sruc.ac.uk.ORCID http://orcid.org/0000-0002-4880-3756

Funding

Agriculture and Horticulture Development Board Agriculture and Horticulture Development BoardBiotechnology and Biological Sciences Research Council BB/N01720X/1Biotechnology and Biological Sciences Research Council BB/S006567/1Department for Environment, Food and Rural Affairs, UK Government 10045515Genus 10045515Quality Meat Scotland (QMS) Quality Meat Scotland (QMS)Scottish Government Scottish GovernmentUK Research and Innovation 10045515
6 · The paper itself

Abstract

backgroundBreeding for reduced methane production is challenged by the high cost associated with its continuous measurements on individual animals. To address this, a microbiome-driven breeding methodology was developed and investigated to identify the most informative microbial genes (MGs) related to methane production. The analyses considered different genomic selection scenarios based on data from beef cattle: (i) with and without inclusion of production traits such as daily feed intake, average daily gain (ADG), cold carcass weight (CCW); (ii) different sets of MGs were evaluated - those most informative to predict the host genetics of methane production, with and without restriction of showing favourable genetic correlation with ADG.

resultsMethane production had a high heritability (0.56), and we identified 43 MGs, whose abundances are associated with methane production through functions such as electron transfer and coenzyme A biosynthesis. Selection of 10% of the animals based on microbiome-driven breeding using these 43 MGs revealed a methane mitigation potential of 18% per generation, slightly higher than 17% reduction achieved through direct selection based on methane measurements using respiration chamber. Integrating production traits into the microbiome-driven breeding system enhanced the methane reduction to 23% but also reduced ADG by 14%. To avoid the decline in ADG and CCW, residual methane production was developed on genetic level, which yielded a meaningful 15% reduction in methane production, and a correlated improvement in residual feed intake of 5%. Applying microbiome-driven breeding based only on profiles of MGs favourably correlated with both methane production and ADG resulted in a promising response in methane mitigation of 14%.

conclusionsThe high heritability of methane production supports animal breeding programmes aimed at reducing methane production. However, selection solely for lower methane production resulted in substantial adverse responses in key production traits. Therefore, it is essential to adopt specific selection criteria, such as residual methane production, to reduce its emissions while avoiding negative correlated responses in production traits. Especially, microbiome-driven breeding based on MGs favourably correlated with both reduced methane production and improved ADG, is recommended to directly enhance the efficiency of ruminal microbial metabolism to achieve sustainable beef production by cost-effective breeding.

Indexed as

BreedingGastrointestinal MicrobiomeMethaneMicrobiotaRumenSelection, GeneticAnimalsCattleMethane

Identifiers

PMID42426588
PMCPMC13491708

What Socratic 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 Socratic graph.