Evidence map›Paper›PMID 24675618›Full record

SynthesisPLoS genetics2014

A multi-trait, meta-analysis for detecting pleiotropic polymorphisms for stature, fatness and reproduction in beef cattle.

Sunduimijid Bolormaa, Jennie E Pryce, Antonio Reverter, Yuandan Zhang, William Barendse, Kathryn Kemper, Bruce Tier, Keith Savin, Ben J Hayes, Michael E Goddard

Open access · goldAbstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 164 papers, 20 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
164citing papers in PubMed, 20 pooled it
15.4field-weighted citation impact, top 1% 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

164 citing papers in PubMed, 20 syntheses or guidelines pooled it, 293 citations in OpenAlex.

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  5. Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023
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104 more citing papers are in PubMed but not listed here.

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

10 authors at 3 institutions in 1 country.

Sunduimijid BolormaaVictorian Department of Environment and Primary Industries, Bundoora, Victoria, Australia.
Jennie E PryceVictorian Department of Environment and Primary Industries, Bundoora, Victoria, Australia.
Antonio ReverterCSIRO Animal, Food and Health Sciences, Queensland Bioscience Precinct, St. Lucia, Queensland, Australia.
Yuandan ZhangAnimal Genetics and Breeding Unit, University of New England, Armidale, New South Wales, Australia.
William BarendseCSIRO Animal, Food and Health Sciences, Queensland Bioscience Precinct, St. Lucia, Queensland, Australia.
Kathryn KemperSchool of Land and Environment, University of Melbourne, Parkville, Victoria, Australia.
Bruce TierAnimal Genetics and Breeding Unit, University of New England, Armidale, New South Wales, Australia.
Keith SavinVictorian Department of Environment and Primary Industries, Bundoora, Victoria, Australia.
Ben J HayesVictorian Department of Environment and Primary Industries, Bundoora, Victoria, Australia.
Michael E GoddardVictorian Department of Environment and Primary Industries, Bundoora, Victoria, Australia; School of Land and Environment, University of Melbourne, Parkville, Victoria, Australia.
Commonwealth Scientific and Industrial Research Organisation · AUUniversity of Melbourne · AUUniversity of New England · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t'V-1t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.

Indexed as

Genome-Wide Association StudyAdipose TissueAnimalsCattleGenotypeMeatPhenotypePolymorphism, Single NucleotideQuantitative Trait LociReproduction

Identifiers

PMID24675618
PMCPMC3967938
OpenAlexW2083497058

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.