Evidence map›Paper›PMID 32000665›Full record

SynthesisGenetics, selection, evolution : GSE2020

Genomic regions associated with muscularity in beef cattle differ in five contrasting cattle breeds.

Jennifer L Doyle, Donagh P Berry, Roel F Veerkamp, Tara R Carthy, Ross D Evans, Siobhán W Walsh, Deirdre C Purfield

Abstract readMeta-Analysis
In one paragraph

Synthesis in Genetics, selection, evolution : GSE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023
    Pooled it
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  6. Animals : an open access journal from MDPI · 2025
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  19. Genome-Wide Association Study forPathogens (Basel, Switzerland) · 2022
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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

7 authors.

Jennifer L DoyleTeagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland.
Donagh P BerryTeagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland. donagh.berry@teagasc.ie.ORCID http://orcid.org/0000-0003-4349-1447
Roel F VeerkampAnimal Breeding and Genomics Centre, Wageningen University and Research Centre, Livestock Research, Wageningen, The Netherlands.
Tara R CarthyTeagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland.
Ross D EvansIrish Cattle Breeding Federation, Bandon, Co. Cork, Ireland.
Siobhán W WalshDepartment of Science, Waterford Institute of Technology, Cork Road, Waterford, Co. Waterford, Ireland.
Deirdre C PurfieldTeagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland.

Funding

Science Foundation Ireland 16/RC/3835Science Foundation Ireland SF 14/IA/2576
6 · The paper itself

Abstract

backgroundLinear type traits, which reflect the muscular characteristics of an animal, could provide insight into how, in some cases, morphologically very different animals can yield the same carcass weight. Such variability may contribute to differences in the overall value of the carcass since primal cuts vary greatly in price; such variability may also hinder successful genome-based association studies. Therefore, the objective of our study was to identify genomic regions that are associated with five muscularity linear type traits and to determine if these significant regions are common across five different breeds. Analyses were carried out using linear mixed models on imputed whole-genome sequence data in each of the five breeds, separately. Then, the results of the within-breed analyses were used to conduct an across-breed meta-analysis per trait.

resultsWe identified many quantitative trait loci (QTL) that are located across the whole genome and associated with each trait in each breed. The only commonality among the breeds and traits was a large-effect pleiotropic QTL on BTA2 that contained the MSTN gene, which was associated with all traits in the Charolais and Limousin breeds. Other plausible candidate genes were identified for muscularity traits including PDE1A, PPP1R1C and multiple collagen and HOXD genes. In addition, associated (gene ontology) GO terms and KEGG pathways tended to differ between breeds and between traits especially in the numerically smaller populations of Angus, Hereford, and Simmental breeds. Most of the SNPs that were associated with any of the traits were intergenic or intronic SNPs located within regulatory regions of the genome.

conclusionsThe commonality between the Charolais and Limousin breeds indicates that the genetic architecture of the muscularity traits may be similar in these breeds due to their similar origins. Conversely, there were vast differences in the QTL associated with muscularity in Angus, Hereford, and Simmental. Knowledge of these differences in genetic architecture between breeds is useful to develop accurate genomic prediction equations that can operate effectively across breeds. Overall, the associated QTL differed according to trait, which suggests that breeding for a morphologically different (e.g. longer and wider versus shorter and smaller) more efficient animal may become possible in the future.

Indexed as

AnimalsBreedingCattleFemaleGenomicsLinear ModelsMaleMuscle, SkeletalPolymorphism, Single NucleotideQuantitative Trait LociRed MeatWhole Genome Sequencing

Identifiers

PMID32000665
PMCPMC6993462

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.