Evidence map›Paper›PMID 38225510›Full record

Observational studyBehavior genetics2024

Key Grazing Behaviours of Beef Cattle Identify Specific Genotypes of the Glutamate Metabotropic Receptor 5 Gene (GRM5).

Cristian Anibal Moreno García, Susana Beatríz Perelman, Robyn Dynes, Thomas M R Maxwell, Huitong Zhou, Jonathan Hickford

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in Behavior genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 3 institutions in 2 countries.

Cristian Anibal Moreno GarcíaDepartment of Agricultural Sciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln, Canterbury, New Zealand. Cristian.MorenoGarcia@lincolnuni.ac.nz.ORCID 0000-0002-8169-1119
Susana Beatríz PerelmanDepartamento de Métodos Cuantitativos y Sistemas de Informacíon, Institute for Agricultural Plant Physiology and Ecology IFEVA CONICET, Universidad de Buenos Aires, CABA, Buenos Aires, Argentina.ORCID 0000-0001-6900-6927
Robyn DynesLincoln Research Centre, AgResearch Limited, Lincoln, Canterbury, New Zealand.ORCID 0000-0002-1740-2968
Thomas M R MaxwellDepartment of Agricultural Sciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln, Canterbury, New Zealand.ORCID 0000-0001-9204-1667
Huitong ZhouDepartment of Agricultural Sciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln, Canterbury, New Zealand.ORCID 0000-0001-7620-3160
Jonathan HickfordDepartment of Agricultural Sciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln, Canterbury, New Zealand.ORCID 0000-0001-9313-761X
Lincoln University · NZAgResearch · NZConsejo Nacional de Investigaciones Científicas y Técnicas · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genotype-phenotype associations between the bovine genome and grazing behaviours measured over time and across contexts have been reported in the past decade, with these suggesting the potential for genetic control over grazing personalities in beef cattle. From the large array of metrics used to describe grazing personality behaviours (GP-behaviours), it is still unclear which ones are linked to specific genes. Our prior observational study has reported associations and trends towards associations between genotypes of the glutamate metabotropic receptor 5 gene (GRM5) and four GP-behaviours, yet the unbalanced representation of GRM5 genotypes occurring in observational studies may have limited the ability to detect associations. Here, we applied a subsampling technique to create a genotypically-balanced dataset in a quasi-manipulative experiment with free ranging cows grazing in steep and rugged terrain of New Zealand's South Island. Using quadratic discriminant analysis, two combinations of eleven GP-behaviours (and a total of fifteen behaviours) were selected to build an exploration model and an elevation model, respectively. Both models achieved ∼ 86% accuracy in correctly discriminating cows' GRM5 genotypes with the training dataset, and the exploration model achieved 85% correct genotype prediction of cows from a testing dataset. Our study suggests a potential pleiotropic effect, with GRM5 controlling multiple grazing behaviours, and with implications for the grazing of steep and rugged grasslands. The study highlights the importance of grazing behavioural genetics in cattle and the potential use of GRM5 markers to select individuals with desired grazing personalities and built herds that collectively utilize steep and rugged rangelands sustainably.

Indexed as

Gene Expression RegulationGlutamatesAnimalsCattleFemaleGenotypeHumansGlutamatesAnimal personalityBehavioural geneticsGlobal positioning system tracking (GPS-tracking)Grazing personalitiesQuadratic discriminant analysisSteep and rugged terrain

Identifiers

PMID38225510
PMCPMC10861638
OpenAlexW4390892485

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.