Evidence map›Paper›PMID 26968377›Full record

ArticleBMC genomics2016

Detailed phenotyping identifies genes with pleiotropic effects on body composition.

Sunduimijid Bolormaa, Ben J Hayes, Julius H J van der Werf, David Pethick, Michael E Goddard, Hans D Daetwyler

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

39 citing papers in PubMed, 94 citations in OpenAlex.

  1. Genome-wide association study of mature cow size traits in American Angus cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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  8. Association Analyses between Single Nucleotide Polymorphisms inAnimals : an open access journal from MDPI · 2023
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  11. Animals : an open access journal from MDPI · 2023
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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

6 authors at 4 institutions in 1 country.

Sunduimijid BolormaaAgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, 3083, Australia. bolormaa.sunduimijid@ecodev.vic.gov.au.
Ben J HayesAgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, 3083, Australia.
Julius H J van der WerfCooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.
David PethickCooperative Research Centre for Sheep Industry Innovation, Armidale, NSW, 2351, Australia.
Michael E GoddardAgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, 3083, Australia.
Hans D DaetwylerAgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, 3083, Australia.
AgriBio · AUMurdoch University · AUPoultry CRC · AUUniversity of New England · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic variation in both the composition and distribution of fat and muscle in the body is important to human health as well as the healthiness and value of meat from cattle and sheep. Here we use detailed phenotyping and a multi-trait approach to identify genes explaining variation in body composition traits.

resultsA multi-trait genome wide association analysis of 56 carcass composition traits measured on 10,613 sheep with imputed and real genotypes on 510,174 SNPs was performed. We clustered 71 significant SNPs into five groups based on their pleiotropic effects across the 56 traits. Among these 71 significant SNPs, one group of 11 SNPs affected the fatty acid profile of the muscle and were close to 8 genes involved in fatty acid or triglyceride synthesis. Another group of 23 SNPs had an effect on mature size, based on their pattern of effects across traits, but the genes near this group of SNPs did not share any obvious function. Many of the likely candidate genes near SNPs with significant pleiotropic effects on the 56 traits are involved in intra-cellular signalling pathways. Among the significant SNPs were some with a convincing candidate gene due to the function of the gene (e.g. glycogen synthase affecting glycogen concentration) or because the same gene was associated with similar traits in other species.

conclusionsUsing a multi-trait analysis increased the power to detect associations between SNP and body composition traits compared with the single trait analyses. Detailed phenotypic information helped to identify a convincing candidate in some cases as did information from other species.

Indexed as

PhenotypeAnimalsBody CompositionCattleCluster AnalysisFatty AcidsGenetic Association StudiesGenetic PleiotropyGenotypeHumansMeatModels, GeneticMuscle, SkeletalPolymorphism, Single NucleotideSheepFatty AcidsBody compositionGenesGWASHumanMeta-analysisMulti-traitPleiotropySheep

Identifiers

PMID26968377
PMCPMC4788919
OpenAlexW2292985992

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.