Evidence map›Paper›PMID 25887672›Full record

ArticleBMC genomics2015

Transcriptome analysis of cattle muscle identifies potential markers for skeletal muscle growth rate and major cell types.

Bing Guo, Paul L Greenwood, Linda M Cafe, Guanghong Zhou, Wangang Zhang, Brian P Dalrymple

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. 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
2.9field-weighted citation impact, top 9% 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.

  1. Pooled it
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  6. Relationships Among Growth, Carcass Characteristics, andAnimals : an open access journal from MDPI · 2024
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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 3 institutions in 2 countries.

Bing GuoKey Laboratory of Meat Processing and Quality Control, Synergetic Innovation Centre of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing, 210095, P. R. China. guobingflying@gmail.com.
Paul L GreenwoodCSIRO Agriculture Flagship, Armidale, NSW, 2350, Australia. Paul.Greenwood@csiro.au.
Linda M CafeNSW Department of Primary Industries, University of New England, Armidale, NSW, 2351, Australia. Linda.Cafe@dpi.nsw.gov.au.
Guanghong ZhouKey Laboratory of Meat Processing and Quality Control, Synergetic Innovation Centre of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing, 210095, P. R. China. ghzhou@njau.edu.cn.
Wangang ZhangKey Laboratory of Meat Processing and Quality Control, Synergetic Innovation Centre of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing, 210095, P. R. China. wangang.zhang@yahoo.com.
Brian P DalrympleCSIRO Agriculture Flagship, St. Lucia, QLD, 4067, Australia. Brian.Dalrymple@csiro.au.
Nanjing Agricultural University · CNCommonwealth Scientific and Industrial Research Organisation · AUUniversity of New England · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to identify markers for muscle growth rate and the different cellular contributors to cattle muscle and to link the muscle growth rate markers to specific cell types.

resultsThe expression of two groups of genes in the longissimus muscle (LM) of 48 Brahman steers of similar age, significantly enriched for "cell cycle" and "ECM (extracellular matrix) organization" Gene Ontology (GO) terms was correlated with average daily gain/kg liveweight (ADG/kg) of the animals. However, expression of the same genes was only partly related to growth rate across a time course of postnatal LM development in two cattle genotypes, Piedmontese x Hereford (high muscling) and Wagyu x Hereford (high marbling). The deposition of intramuscular fat (IMF) altered the relationship between the expression of these genes and growth rate. K-means clustering across the development time course with a large set of genes (5,596) with similar expression profiles to the ECM genes was undertaken. The locations in the clusters of published markers of different cell types in muscle were identified and used to link clusters of genes to the cell type most likely to be expressing them. Overall correspondence between published cell type expression of markers and predicted major cell types of expression in cattle LM was high. However, some exceptions were identified: expression of SOX8 previously attributed to muscle satellite cells was correlated with angiogenesis. Analysis of the clusters and cell types suggested that the "cell cycle" and "ECM" signals were from the fibro/adipogenic lineage. Significant contributions to these signals from the muscle satellite cells, angiogenic cells and adipocytes themselves were not as strongly supported. Based on the clusters and cell type markers, sets of five genes predicted to be representative of fibro/adipogenic precursors (FAPs) and endothelial cells, and/or ECM remodelling and angiogenesis were identified.

conclusionsGene sets and gene markers for the analysis of many of the major processes/cell populations contributing to muscle composition and growth have been proposed, enabling a consistent interpretation of gene expression datasets from cattle LM. The same gene sets are likely to be applicable in other cattle muscles and in other species.

Indexed as

Gene Expression ProfilingTranscriptomeAdipogenesisAnimalsBiomarkersCattleCell CycleCluster AnalysisComputational BiologyExtracellular MatrixGene ExpressionGene Expression RegulationModels, BiologicalMolecular Sequence AnnotationMuscle, SkeletalQuantitative Trait, HeritableBiomarkers

Identifiers

PMID25887672
PMCPMC4364331
OpenAlexW2010524507

What OpenQuestion holds

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LicenceCC BY
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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.