Evidence map›Paper›PMID 25875247›Full record

ArticlePloS one2015

Identification of common regulators of genes in co-expression networks affecting muscle and meat properties.

Siriluck Ponsuksili, Puntita Siengdee, Yang Du, Nares Trakooljul, Eduard Murani, Manfred Schwerin, Klaus Wimmers

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 28 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

7 authors at 1 institution in 1 country.

Siriluck PonsuksiliInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Puntita SiengdeeInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Yang DuInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Nares TrakooljulInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Eduard MuraniInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Manfred SchwerinInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Klaus WimmersInstitute for 'Genome Biology', Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany.
Research Institute for Farm Animal Biology (FBN) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the genetic contributions behind skeletal muscle composition and metabolism is of great interest in medicine and agriculture. Attempts to dissect these complex traits combine genome-wide genotyping, expression data analyses and network analyses. Weighted gene co-expression network analysis (WGCNA) groups genes into modules based on patterns of co-expression, which can be linked to phenotypes by correlation analysis of trait values and the module eigengenes, i.e. the first principal component of a given module. Network hub genes and regulators of the genes in the modules are likely to play an important role in the emergence of respective traits. In order to detect common regulators of genes in modules showing association with meat quality traits, we identified eQTL for each of these genes, including the highly connected hub genes. Additionally, the module eigengene values were used for association analyses in order to derive a joint eQTL for the respective module. Thereby major sites of orchestrated regulation of genes within trait-associated modules were detected as hotspots of eQTL of many genes of a module and of its eigengene. These sites harbor likely common regulators of genes in the modules. We exemplarily showed the consistent impact of candidate common regulators on the expression of members of respective modules by RNAi knockdown experiments. In fact, Cxcr7 was identified and validated as a regulator of genes in a module, which is involved in the function of defense response in muscle cells. Zfp36l2 was confirmed as a regulator of genes of a module related to cell death or apoptosis pathways. The integration of eQTL in module networks enabled to interpret the differentially-regulated genes from a systems perspective. By integrating genome-wide genomic and transcriptomic data, employing co-expression and eQTL analyses, the study revealed likely regulators that are involved in the fine-tuning and synchronization of genes with trait-associated expression.

Indexed as

Gene Regulatory NetworksAnimalsCell LineGenomeGenotypeMeatMiceMuscle, SkeletalPolymorphism, Single NucleotideQuantitative Trait LociReceptors, CXCRRNA InterferenceRNA, Small InterferingTristetraprolinCmkor1 protein, mouseReceptors, CXCRRNA, Small InterferingTristetraprolinZfp36 protein, mouse

Identifiers

PMID25875247
PMCPMC4397042
OpenAlexW1977206101

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LicenceCC BY
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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 OpenQuestion graph.