The transcriptomic signature of myostatin inhibitory influence on the differentiation of mouse C2C12 myoblasts

Wicik, Zofia; Sadkowski, Tomasz; Jank, Michał; Motyl, T.

doi:10.2478/v10181-011-0095-7

Cited by 15 publications

(14 citation statements)

References 26 publications

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“…ITGB1 codes for a subunit of ubiquitous fibronectin receptors and has a number of suggested functions in different tissues. In skeletal muscle, it has been proposed as a possible target for myostatin in mice myoblast differentiation [30] and is also critical for the development of neuromuscular junctions [31] . TMOD1 encodes for tropomodulin, a protein that regulates tropomyosin and F-actin organization.…”

Section: Resultsmentioning

confidence: 99%

Integrative Data Mining Highlights Candidate Genes for Monogenic Myopathies

Neto¹,

Tassy

Biancalana³

et al. 2014

PLoS ONE

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Inherited myopathies are a heterogeneous group of disabling disorders with still barely understood pathological mechanisms. Around 40% of afflicted patients remain without a molecular diagnosis after exclusion of known genes. The advent of high-throughput sequencing has opened avenues to the discovery of new implicated genes, but a working list of prioritized candidate genes is necessary to deal with the complexity of analyzing large-scale sequencing data. Here we used an integrative data mining strategy to analyze the genetic network linked to myopathies, derive specific signatures for inherited myopathy and related disorders, and identify and rank candidate genes for these groups. Training sets of genes were selected after literature review and used in Manteia, a public web-based data mining system, to extract disease group signatures in the form of enriched descriptor terms, which include functional annotation, human and mouse phenotypes, as well as biological pathways and protein interactions. These specific signatures were then used as an input to mine and rank candidate genes, followed by filtration against skeletal muscle expression and association with known diseases. Signatures and identified candidate genes highlight both potential common pathological mechanisms and allelic disease groups. Recent discoveries of gene associations to diseases, like B3GALNT2, GMPPB and B3GNT1 to congenital muscular dystrophies, were prioritized in the ranked lists, suggesting a posteriori validation of our approach and predictions. We show an example of how the ranked lists can be used to help analyze high-throughput sequencing data to identify candidate genes, and highlight the best candidate genes matching genomic regions linked to myopathies without known causative genes. This strategy can be automatized to generate fresh candidate gene lists, which help cope with database annotation updates as new knowledge is incorporated.

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Section: Resultsmentioning

confidence: 99%

Integrative Data Mining Highlights Candidate Genes for Monogenic Myopathies

Neto¹,

Tassy

Biancalana³

et al. 2014

PLoS ONE

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“…The deletion of myostatin in mice induces dramatic and widespread increase in skeletal muscle mass due to both muscle hypertrophy and hyperplasia [ 32 ], and it also cause double-muscling phenotype of some cattle and sheep breeds [ 57 ]. Wicik et al [ 67 ] showed inhibitory effect of exogenous MSTN on differentiating C 2 C 12 myoblasts.…”

Section: Discussionmentioning

confidence: 99%

Transcriptomic profile adaptations following exposure of equine satellite cells to nutriactive phytochemical gamma-oryzanol

et al. 2016

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BackgroundAdult skeletal muscle myogenesis depends on the activation of satellite cells that have the potential to differentiate into new fibers. Gamma-oryzanol (GO), a commercially available nutriactive phytochemical, has gained global interest on account of its muscle-building and regenerating effects. Here, we investigated GO for its potential influence on myogenesis, using equine satellite cell culture model, since the horse is a unique animal, bred and exercised for competitive sport. To our knowledge, this is the first report where the global gene expression in cultured equine satellite cells has been described.MethodsEquine satellite cells were isolated from semitendinosus muscle and cultured until the second day of differentiation. Differentiating cells were incubated with GO for the next 24 h. Subsequently, total RNA from GO-treated and control cells was isolated, amplified, labeled, and hybridized to two-color Horse Gene Expression Microarray slides. Quantitative PCR was used for the validation of microarray data.ResultsOur results revealed 58 genes with changed expression in GO-treated vs. control cells. Analysis of expression changes suggests that various processes are reinforced by GO in differentiating equine satellite cells, including inhibition of myoblast differentiation, increased proliferation and differentiation, stress response, and increased myogenic lineage commitment.ConclusionsThe present study may confirm putative muscle-enhancing abilities of GO; however, the collective role of GO in skeletal myogenesis remains equivocal. The diversity of these changes is likely due to heterogenous growth rate of cells in primary culture. Genes identified in our study, modulated by the presence of GO, may become potential targets of future research investigating impact of this supplement in skeletal muscle on proteomic and biochemical level.Electronic supplementary materialThe online version of this article (doi:10.1186/s12263-016-0523-5) contains supplementary material, which is available to authorized users.

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“…A large number of high-throughput studies have been performed to explore the functional roles of genes found to have altered expression patterns during skeletal muscle differentiation [ 5 , 24 – 26 ]. Microarray [ 12 , 27 , 28 ] along with RNA-Seq [ 29 ] studies have improved our knowledge of myogenesis by identifying diverse types of target genes encoding myogenic transcription factors or novel myogenic regulatory factors which govern the fusion of myoblasts into myotubes that were otherwise hard to detect with conventional methods. In spite of these improvements, the roles that these genes play in skeletal muscle development as well as the understanding of underlying molecular mechanisms are still poorly understood.…”

Section: Introductionmentioning

confidence: 99%

Network Analysis for the Identification of Differentially Expressed Hub Genes Using Myogenin Knock-down Muscle Satellite Cells

Malik¹,

Lee²,

Jan³

et al. 2015

PLoS ONE

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Muscle, a multinucleate syncytium formed by the fusion of mononuclear myoblasts, arises from quiescent progenitors (satellite cells) via activation of muscle-specific transcription factors (MyoD, Myf5, myogenin: MYOG, and MRF4). Subsequent to a decline in Pax7, induction in the expression of MYOG is a hallmark of myoblasts that have entered the differentiation phase following cell cycle withdrawal. It is evident that MYOG function cannot be compensated by any other myogenic regulatory factors (MRFs). Despite a plethora of information available regarding MYOG, the mechanism by which MYOG regulates muscle cell differentiation has not yet been identified. Using an RNA-Seq approach, analysis of MYOG knock-down muscle satellite cells (MSCs) have shown that genes associated with cell cycle and division, DNA replication, and phosphate metabolism are differentially expressed. By constructing an interaction network of differentially expressed genes (DEGs) using GeneMANIA, cadherin-associated protein (CTNNA2) was identified as the main hub gene in the network with highest node degree. Four functional clusters (modules or communities) were identified in the network and the functional enrichment analysis revealed that genes included in these clusters significantly contribute to skeletal muscle development. To confirm this finding, in vitro studies revealed increased expression of CTNNA2 in MSCs on day 12 compared to day 10. Expression of CTNNA2 was decreased in MYOG knock-down cells. However, knocking down CTNNA2, which leads to increased expression of extracellular matrix (ECM) genes (type I collagen α1 and type I collagen α2) along with myostatin (MSTN), was not found significantly affecting the expression of MYOG in C2C12 cells. We therefore propose that MYOG exerts its regulatory effects by acting upstream of CTNNA2, which in turn regulates the differentiation of C2C12 cells via interaction with ECM genes. Taken together, these findings highlight a new mechanism by which MYOG interacts with CTNNA2 in order to promote myoblast differentiation.

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The transcriptomic signature of myostatin inhibitory influence on the differentiation of mouse C2C12 myoblasts

Cited by 15 publications

References 26 publications

Integrative Data Mining Highlights Candidate Genes for Monogenic Myopathies

Integrative Data Mining Highlights Candidate Genes for Monogenic Myopathies

Transcriptomic profile adaptations following exposure of equine satellite cells to nutriactive phytochemical gamma-oryzanol

Network Analysis for the Identification of Differentially Expressed Hub Genes Using Myogenin Knock-down Muscle Satellite Cells

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