Evidence map›Paper›PMID 24643240›Full record

ArticleInternational journal of biological sciences2014

Discovery of candidate genes for muscle traits based on GWAS supported by eQTL-analysis.

Siriluck Ponsuksili, Eduard Murani, Nares Trakooljul, Manfred Schwerin, Klaus Wimmers

Open access · goldAbstract read
In one paragraph

Article in International journal of biological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Siriluck Ponsuksili1. Research Group 'Functional Genome Analyses', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany;
Eduard Murani2. Research Unit 'Molecular Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Nares Trakooljul2. Research Unit 'Molecular Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Manfred Schwerin1. Research Group 'Functional Genome Analyses', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany;
Klaus Wimmers2. Research Unit 'Molecular Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Leibniz Association · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biochemical and biophysical processes that take place in muscle under relaxed and stressed conditions depend on the abundance and activity of gene products of metabolic and structural pathways. In livestock at post-mortem, these muscle properties determine aspects of meat quality and are measurable. The conversion of muscle to meat mimics pathological processes associated with muscle ischemia, injury or damage in humans and it is an economic factor in pork production. Linkage, association, and expression analyses independently contributed to the identification of trait-associated molecular pathways and genes. We aim at providing multiple evidences for the role of specific genes in meat quality by integrating a genome-wide association study (GWAS) for meat quality traits and the detection of eQTL based on trait-correlated expressed genes and trait-associated markers. The GWAS revealed 51 and 200 SNPs significantly associated with meat quality in a crossbred Pietrain×(German Landrace×Large White) (Pi×(GL×LW)) and a purebred German Landrace (GL) population, respectively. Most significant SNPs in Pi×(GL×LW) were located on chromosomes (SSC) 4 and 6. The data of 47,836 eQTLs at a significance level of p<10(-5) were used to scale down the number candidate genes located in these regions. These SNPs on SSC4 showed association with expression levels of ZNF704, IMPA1, and OXSR1; SSC6 SNPs were associated with expression of SIGLEC10 and PIH1D1. Most significant SNPs in GL were located on SSC6 and associated with expression levels of PIH1D1, SIGLEC10, TBCB, LOC100518735, KIF1B, LOC100514845, and two unknown genes. The abundance of transcripts of these genes in muscle, in turn, is significantly correlated with meat quality traits. We identified several genes with evidence for their candidacy for meat quality arising from the integrative approach of a genome-wide association study and eQTL analysis.

Indexed as

Genome-Wide Association StudyMeatMuscle, SkeletalQuantitative Trait LociAnimalsChromosomesPhenotypePolymorphism, Single NucleotideSwineeQTLGWASmicroarraypork quality.SNP chip

Identifiers

PMID24643240
PMCPMC3957088
OpenAlexW2099927646

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.