Glycogenome expression dynamics during mouse C2C12 myoblast differentiation suggests a sequential reorganization of membrane glycoconjugates
© Janot et al; licensee BioMed Central Ltd. 2009
Received: 26 March 2009
Accepted: 20 October 2009
Published: 20 October 2009
Several global transcriptomic and proteomic approaches have been applied in order to obtain new molecular insights on skeletal myogenesis, but none has generated any specific data on glycogenome expression, and thus on the role of glycan structures in this process, despite the involvement of glycoconjugates in various biological events including differentiation and development. In the present study, a quantitative real-time RT-PCR technology was used to profile the dynamic expression of 375 glycogenes during the differentiation of C2C12 myoblasts into myotubes.
Of the 276 genes expressed, 95 exhibited altered mRNA expression when C2C12 cells differentiated and 37 displayed more than 4-fold up- or down-regulations. Principal Component Analysis and Hierarchical Component Analysis of the expression dynamics identified three groups of coordinately and sequentially regulated genes. The first group included 12 down-regulated genes, the second group four genes with an expression peak at 24 h of differentiation, and the last 21 up-regulated genes. These genes mainly encode cell adhesion molecules and key enzymes involved in the biosynthesis of glycosaminoglycans and glycolipids (neolactoseries, lactoseries and ganglioseries), providing a clearer indication of how the plasma membrane and extracellular matrix may be modified prior to cell fusion. In particular, an increase in the quantity of ganglioside GM3 at the cell surface of myoblasts is suggestive of its potential role during the initial steps of myogenic differentiation.
For the first time, these results provide a broad description of the expression dynamics of glycogenes during C2C12 differentiation. Among the 37 highly deregulated glycogenes, 29 had never been associated with myogenesis. Their biological functions suggest new roles for glycans in skeletal myogenesis.
Myogenesis is a complex process which leads muscle progenitor cells to proliferate and then differentiate into myotubes. This process is strongly controlled by the spatio-temporal expression of myogenic regulatory factors (MRFs) - MyoD, Myf5, myogenin and Mrf4 (or Myf6) [1, 2] - and by several transcription factors of the myocyte enhancer factor-2 (MEF2) family . Their expression defines different stages in the myogenic process: myoblast proliferation, cell-cycle withdrawal, cell fusion to form myotubes, and the maturation of myotubes into myofibers. MRFs are members of the bHLH (basic Helix-Loop-Helix) protein family . They cooperate with MEF2 transcription factors to mediate the transcription of muscle-specific genes . bHLH proteins also form heterodimers with E proteins [6, 7], enabling binding to the E-box consensus DNA sequence  and the transcription of specific skeletal muscle genes, such as the myosin heavy chain gene .
As well as myogenic factors, myogenesis involves other molecular actors such as embryonic fibroblast growth factor (eFGF), cadherins, members of the cadherin-associated immunoglobulin superfamily such as CDO (CAM (Cell Adhesion Molecule)-related/down-regulated by oncogenes), BOC (b rother o f C DO) , neogenin  and p38 MAP kinase . These are the classic molecules involved in cell interactions and signaling. In order to monitor the expression of these actors, several studies have exploited the development of high-throughput gene expression profiling using microarrays and proteomic approaches. Recent microarray studies on C2C12 cells, mouse myoblasts that can differentiate into myotubes, have afforded a broad molecular description of myogenesis and identified sets of genes that display transcriptional variations in expression between proliferating and differentiating cells [13–16]. These studies identified some genes, as Zfp-51 and Ptger4, which were not previously associated with skeletal myogenic differentiation. Some proteomics studies on developing myotubes have partially confirmed and completed these microarray-based studies by providing evidence for the involvement of transcription regulators, signaling factors, phospho-proteins and adhesion molecules, as well as novel non-characterized proteins (Riken clones and unnamed proteins) in skeletal muscle development and contractility [17, 18].
The plasma membrane and extracellular matrix (ECM) of myoblasts, like those of other eukaryotic cells, are rich in glycoproteins and glycolipids. Despite all the data generated by transcriptomic and proteomic studies, little information is available on the role of glycoconjugates in myogenesis. The principal reason for this lies in the weak expression of glycogenes which is hardly detectable using pan-genomic microarrays. Nevertheless, some proteoglycans of the ECM, e.g. syndecans, have been shown to play different roles in myogenesis [19, 20]. Inhibition of their synthesis halts myoblast proliferation and fusion independently of the expression of the myogenic bHLH factor. In the same way, blocking N-glycan synthesis impairs myoblast fusion  and the in vivo invalidation of Mgat1, a gene involved in the synthesis of complex N-glycans, generates mouse embryo death in utero . Conversely, NCAM1 O-glycosylation promotes myoblast fusion [23, 24]. Glycolipids also play key roles in cell differentiation [25, 26]. They appear to be involved in muscle development, since their membrane levels are altered during G7 and G8 myoblast fusion, with an increase in gangliosides and neutral glycolipid synthesis . In other myogenic cell lines, changes have been observed in the activities of the glycosyltransferases that contribute to glycolipid synthesis .
In order to clarify the potential roles of glycosylation in myogenesis, quantitative real-time RT-PCR was used to analyze the expression of 375 glycogenes (that account for more than 60% of the glycogenome) in differentiating mouse C2C12 cells. Seventy-four percent of the genes (276 genes) were expressed during C2C12 cell differentiation: 181 of them were invariant while 37 displayed up- or down-regulations of more than 4-fold. These genes were clustered in three main groups. The first cluster contained genes with gradually decreasing quantities of transcripts. In the second set of genes, transcript levels reached a maximum at 24-48 h of differentiation and then decreased, while those in the third cluster increased throughout differentiation. The functions controlled by the clustered genes, as a function of their group, highlighted how the myoblast cell membrane and ECM could be modified for cell fusion during C2C12 differentiation. For the first time, this study provides a general framework for glycogene expression during the onset of in vitro myogenesis.
Results and Discussion
The combined use of cell lines and microarrays offers a major opportunity to study gene expression patterns and/or dynamics during different physiological and pathological processes. However, the substantial findings generated by the use of pangenomic microarrays have generally been difficult to interpret in terms of the gene regulation controlling biological functions. In this study, we chose to explore the expression dynamics of just one part of the mouse genome, called the 'glycogenome', in the context of myogenesis. For this purpose, we first of all standardized the experimental conditions for the differentiation of C2C12 (a mouse myogenic cell line), and analyzed the expression of myogenic markers by quantitative real-time RT-PCR. The expression of 375 glycogenes was then monitored in differentiating C2C12 cells using quantitative real-time RT-PCR with TLDA (TaqMan Low Density Array, see Methods section). Highly deregulated genes were next clustered as a function of their expression profiles. Their functions were analyzed and used to suggest new roles for glycoconjugates in myogenic differentiation.
The expression of MRF and marker genes is consistent with C2C12 cell differentiation
MyoD, Myf5 and myogenin genes were expressed throughout C2C12 differentiation (Figure 1B). MyoD mRNA levels only changed slightly, regardless of the time elapsing after the start of differentiation. Beyond t = 48 h, the expression of Myf5 decreased more than two-fold and remained down-regulated, while the myogenin gene was up-regulated (~100-fold). For Mrf4, transcripts were only detected at t = 192 h. Therefore, the expression profiles of myogenic regulatory factors during C2C12 differentiation were in agreement with their expression patterns (top diagram inset in Figure 1B) described in the literature [15, 16, 32, 33].
Expression of the muscle transcription factors Mef2a and Mef2d increased as from 6 h of differentiation to reach 60-fold for Mef2a and 3.4-fold for Mef2d at the end of the experiment (Figure 1C). Their expression was in line with their myogenic activator roles . Interestingly, the increase in Hes6 expression started at t = 6 h of differentiation and reached 6.5-fold after 72 h. As demonstrated elsewhere , this last result argued in favor of Hes6 involvement at the onset of C2C12 differentiation and more generally of the myogenic process. Unlike the Hes and Mef genes, Csrp3 expression was first detected at t = 18 h of differentiation and increased to reach a peak at t = 120 h (Figure 1C). The expression profile of Csrp3, encoding the LIM protein, correlated with its activator function of C2C12 differentiation. Indeed, it has been showed that LIM protein is not necessary for myoblast proliferation but plays a key role in upcoming myogenic differentiation . Thus, the transcriptional expression profiles of both myogenic marker genes and MRFs genes attested to the accurate time course of C2C12 differentiation.
Most glycogenes are expressed during the onset of C2C12 differentiation
Data summary of Mus musculus glycogene expression during C2C12 differentiation.
Number of known genes1
Number of analyzed genes2
Number of expressed genes3
Genes with 2× up- or down-regulation4
Genes with 4× up- or down-regulation4
Three-quarters of the genes analyzed were expressed (Table 1): 276 genes displayed significant quantities of transcripts (Ct ≤ 33) during at least one point of the differentiation time course. Among the 375 glycogenes of this study, 202 genes were also analyzed in Tomczak et al. study . The microarray and TLDA approaches gave similar results for 91 genes, 43 were expressed and 48 unexpressed. For the remaining common genes (111), only TLDA revealed significant expression levels. This could be explained by the methodologies employed, insofar as microarray techniques are less precise and sensitive than quantitative real-time RT-PCR .
Among the genes expressed, 34% had a minimum 2-fold modification of their expression for at least one kinetic time, and 10% displayed a variation of at least 4-fold (Table 1). The significant number of glycogenes thus regulated underlined the critical function of glycosylation in this differentiation process. Lectin genes appeared to be regulated preferentially, because only 57% of them were expressed, compared to 73% or more for the other gene families. Within each glycogene family, it is interesting to note that no correlation was observed between the number of genes analyzed and the number of those regulated. Indeed, glycosyltransferase genes accounted for about 40% of analyzed genes and only 11% of them displayed an mRNA variation of more than 4-fold. At the same time, ~50% of lectin and sulfotransferase genes, representing ~27% and ~6% of analyzed genes respectively, were significantly modified in terms of their expression. In addition, no glycogene sub-family, such as fucosyltransferases or sialyltransferases, was preferentially repressed or expressed.
Genes displaying more than 4-fold variation (37 genes) were distributed into four groups according to their glyco-family (Table 1). The first group included lectin and sulfotransferase genes (26% of them with significant mRNA variations), the second contained glycosyltransferase and sugar carrier genes (11-16% deregulated), the third included glycosidase genes (only 4% of genes deregulated), and the final group comprised translocase and sugar metabolism genes in which no gene displayed a variation in mRNA expression. Thus, a large proportion of the modifications to glycogene expression that occurred during C2C12 differentiation mainly seemed to affect proteins giving rise to the glycans or lectins required for cell contacts. These results are consistent with the cellular events involved in myotube formation, i.e. cell interactions and fusions.
Among the genes analyzed, 99 were poorly or not expressed. Their corresponding mRNA were not detected (Ct = 40) or not significantly quantified (Ct>33). These genes encoded proteins involved in physiological processes unrelated to myogenesis. For example, Has3 encodes a hyaluronan synthase which is active in hyaluronan/hyaluronic acid synthesis and known to be involved in the inflammatory response , and Icam2 encodes a lectin which mediates adhesive interactions during the immune response.
Nearly half of analyzed glycogenes could be cell homeostasis genes
Among the 276 genes expressed, 181 were invariantly transcribed (Table 1). These constitutively expressed genes could be divided into three sets, according to their functions. The first set corresponded to genes involved in cell homeostasis, the second to genes involved in myogenic cell homeostasis and the third to myogenic genes that could probably undergo a late modification to their expression. In this respect, most of the genes encoding proteins involved in N-glycan precursor synthesis and present on our mouse glycogenome TLDA were homeostasis cell genes and were constitutively expressed. Alg2, Alg3, Alg9, Alg12 (mannosyltransferase genes) and Alg6 (a glucosyltransferase gene), which are responsible for N-glycan precursor synthesis, were expressed without any significant variations. This was also the case for Dpia3 (or Erp57), an ER chaperone-encoding gene involved in disulfide bond formation . The second set of genes, although constitutively expressed during the first 72 h of differentiation, could have crucial functions at all stages of myogenesis. The myogenic factor MyoD, or the sialidase gene Neu3 are representative of this group . Finally, the expression of the third set of genes may be modified after 72 h of differentiation and be required for later stages of myogenesis. For example, the expression of Pomt1, encoding an O-mannosyltransferase which is known to glycosylate the muscle membrane protein α-dystroglycan linking cytoskeleton actin to ECM components, could be tardily up-regulated .
Glycogenes with significant mRNA variations are sequentially expressed
Gene clustering was performed using the Euclidean distances calculated with their coordinates on the first plan of PCA. This clearly highlighted three groups (Figure 2B). The first contained 12 genes, the second four and the third 21. The myogenic marker Myf5 was classified in cluster 2, MyoD and myogenin in cluster 3 (data not shown); Mrf4 was not clustered since it was not expressed during the first 72 h of differentiation. mRNA levels in the cluster 1 displayed a general tendency to decrease that was more pronounced towards the end of the time course (Figure 2C). Cluster 2 included genes with a peak mRNA expression at 24 h of differentiation. Genes in cluster 3 had expression profiles opposite to those of cluster 1 because these expressions increased and became more important at the end of the time course (Figure 2C).
With regards the sequential expression of ≥ 4-fold variant glycogenes and the function of encoded proteins, the early differentiation of C2C12 cells seemed mainly to require: (i) the specific expression of molecules involved in cell signaling and a modification to ECM composition, (ii) the expression of CAMs, and (iii) qualitative and/or quantitative modifications to plasma membrane glycoconjugates.
Cell signaling and GAGs sulfation contribute to the initiation of myogenesis
The functions assured by some down-regulated genes in cluster 1 suggested an involvement of cell signaling in myogenic differentiation. The commitment of C2C12 cells to the myogenic or adipogenic lineage is controlled by specific transcription factors. Myogenesis is regulated by MRFs , while adipogenesis is controlled by PPAR-γ and the C/EBP families of transcription factors [39, 40]. The Olr1 gene encodes a lectin which is activated by PPAR-γ signaling . The down-regulation of Olr1 is consistent with the commitment of C2C12 to myogenic differentiation. Lfng is an enzyme that elongates O-fucose on some EGF-like domains of the Notch receptor. It belongs to the Fringe family  and acts as a modulator of the Notch signaling pathway . It also influences cell fate during embryonic development . Given the involvement of Notch in the myogenic process , Lfng down-regulation in differentiating C2C12 cells argues for the involvement of Lfng in myogenic differentiation. Interestingly, among the up-regulated genes in cluster 3, Lgals12 encoded the galectin-12 which is required for adipogenic signaling and adipocyte differentiation . This gene is indeed weakly expressed at early stages, but its important transcriptional induction beyond 48 h of differentiation suggests, for the first time, its later implication in myogenesis.
Deregulated glycogenes during the onset of C2C12 differentiation.
mRNA Relative Quantity according to differentiation time
CAMs, glycosphingolipids and glycoproteins of the C2C12 plasma membrane appeared to be reshaped for cell fusion
Myoblast fusion into myotubes requires cell interactions. Ten highly regulated glycogenes are involved in cell adhesion (Figure 3). Among the genes in cluster 1, four encoded lectins (Itga3, Itgb7, Siglecg and Selp) and one a sulfotransferase (Chst10). These five genes have been described in different developmental processes. For example, Itgα3 associated with Itgβ1 have been shown to mediate the migration of endothelial cells and angiogenesis . In the present case, the down-regulation of Itgα3 may have been linked to the arrest of myoblast migration and proliferation. In addition, five lectin genes encoding for three integrins (Itgα4, Itgα7 and Itgβ1bp2), one galectin (Lgals7) and Ncam1, belonged to up-regulated genes (Cluster 3). Most of them have important functions in myogenesis: NCAM1 in myoblast fusion [23, 24], melusin (encoded by Itgb1bp2) in the maturation and/or organization of muscle cells , and Itgα7 (with Itgβ1) in myogenesis [51, 52]. Up-regulation of these CAM-encoding genes, combined with the down-regulation of the four genes in cluster 1 mentioned above, also suggests a potential switch of CAM during myogenic differentiation.
GM3 ganglioside levels increase in differentiating C2C12 cells
Little is known about the importance of glycosylation in myogenesis because of the poor representativeness of glycogenes, i.e. ~2% of the genome, and because the weak expression of most of them is not revealed by microarrays. In order to determine how glycosylation could be involved in this process, we used a quantitative real-time RT-PCR technology to analyze the expression of 375 glycogenes representing more than 60% of the mouse glycogenome, during the onset of differentiation of the myogenic C2C12 cell line. The glycogenome includes genes encoding for proteins involved in the transport, synthesis and/or recognition of monosaccharide precursors, glycans and glycoconjugates. This study presents for the first time a focused transcriptomic analysis of the glycogenome during myogenic differentiation.
C2C12 mouse myoblasts (strain C3H, American Type Culture Collection (ATCC), Manassas, VA, USA) were cultured in DMEM (Dubelco's modified Eagle's medium, Eurobio, Courtaboeuf, France) supplemented with 10% fetal calf serum (Eurobio), 2 mM L-glutamine, 50 units/mL penicillin and 50 μg/mL streptomycin. Cells were grown to 80% confluence and were differentiated into myotubes with DMEM supplemented with 2% horse serum. After 48 h of differentiation, the medium was changed every day. For each kinetic point analyzed, cells were rinsed briefly with PBS and harvested following trypsinization (1× PBS, 1 mM EDTA, 0.05% (w/v) trypsin).
RNA extraction and cDNA synthesis
Total RNA from each sample was obtained by anion exchange chromatography (RNeasy mini Kit, Qiagen Inc., Hilden, Germany). The integrity and quantity of total RNA were measured using a micro fluidic-based platform (Agilent 2100 Bioanalyser, Agilent Technologies Inc., Santa Clara, CA, USA). The High Capacity cDNA Archive Kit (Applied Biosystems, Foster City, CA, USA) was used to convert 5 or 10 μg of total RNA into single-stranded cDNA.
Design of the glycogenome TaqMan Low Density Array (TLDA)
A micro-fluidic card dedicated to quantitative real-time RT-PCR analyses of part of the mouse genome, the 'glycogenome', was designed. The glycogenes thus analyzed encode proteins involved in glycan synthesis or glycan recognition. They were selected from GenBank, CAZY and MGI databases [59–61]. They include glycosidases, glycosyltransferases, sugar carriers and sugar metabolism proteins, translocases, sulfotransferases and lectins. These genes control glycosylation functions which likely regulate myogenesis. When this work started, ~600 corresponding murine genes were listed (Table 1). The TLDA technology used is based on quantitative real-time RT-PCR with TaqMan probes validated by the manufacturer. Among the 600 genes listed, only 389 validated probes were available for gene expression studies https://products.Appliedbiosystems.com/ab/en/US/adirect/ab. The technology operates on 384 well plates and allows a simultaneous analysis of 375 candidate glycogenes, 9 wells being dedicated to 6 reference genes. Consequently, among the 389 genes, for which validated probes were available, some sulfotransferase genes were not selected in order to preferentially analyze all available genes involved in glycan biosynthesis and not in glycan modification. Thus, for genes encoding sulfotransferases, only 22 probes of the 36 listed were considered (Table 1), reducing to 375 the number of glycogenes analyzed using TLDA, that is ~60% of the mouse genes known to be related to glycosylation.
Quantitative real-time RT-PCR
The quantity of each mRNA was determined by quantitative real-time RT-PCR on an ABI Prism 7900 Sequence Detector System using TaqMan probe-based chemistry (Applied Biosystems). 6-carboxyfluorescein (FAM) was used as a reporter. The amplification reactions for each gene were performed with 2 ng cDNA for 96-well plates (analysis of myogenic markers) and with 3 ng cDNA for TaqMan Low Density Arrays (TLDA) (analysis of glycogenes). This relative quantification was reliant on the use of several reference genes: 18S RNA, G6pdx, Gapdh, Tcea, Tbp.
Gene mRNA expression data were collected and analyzed using SDS 2.2.2 software (Applied Biosystems). The comparative ΔΔCt method was used to quantify the relative abundance of mRNA. This method uses a calibrator sample to enable a comparison of gene expression levels in different samples. During this study, we used time t = 0 h of differentiation as the calibrator sample. The values obtained indicated the changes in expression in the sample of interest by comparison with the calibrator sample after normalization to 18S RNA. Relative quantities were regarded as significant for genes whose Ct (Threshold Cycle) was lower than 33. Genes that were not expressed were given a Ct value of 40 by default.
Relative levels of mRNA in the 37 selected genes were log-transformed and analyzed using Principal Component Analysis (PCA) and hierarchical cluster analysis (HCA) with PAST version 1.78 [62, 63] in order to reveal trends in their expression. This mathematical procedure reduces the number of possibly correlated variables (seven dimensions corresponding to the different differentiation times) to a smaller number. Thus, most of the data are projected in a 2D-space defined by the two principal components PC1 and PC2, which are synthetic axes expressing the percentage of data variance. Indeed, PCA extracts the direction where the cloud of values is extended, constituting the first component or principal component (PC1). The next direction (PC2) is orthogonal to the first one. The cloud of points reflects the level of expression of each gene as a function of its position relative to the vectors. Vectors indicate the orientation of variation and correspond to most representative expression profiles. Samples belonging to a same pattern are therefore expected to be grouped in a similar area. The coordinates of each gene on the ordination plan were used to calculate Euclidean distances between all pair-wise combinations. The unweighted pair-group average was taken as an agglomeration method to construct the Hierarchical Component Analysis.
C2C12 cells were grown on glass cover-slips. After removing the medium, the cells were washed twice with PBS and fixed for 15 min in 4% paraformaldehyde. After two washes of 5 min each in 1× PBS, the cells were further incubated for 1 h with a blocking solution (1× PBS with 10% fetal bovine serum (Eurobio)), and labeled with an anti-GM3 primary antibody (Seikagaku Corporation, Japan) diluted 1/100 in blocking solution for 1 h at room temperature. A control was performed using cells incubated with a mouse isotypic IgM (Santa Cruz, CA, USA) at the same concentration as the anti-GM3 primary antibody. The cells were rinsed in 1× PBS, incubated for 1 h with an FITC-conjugated secondary antibody (Sigma-Aldrich, Saint Quentin Fallavier, France) and then washed 3 times for 5 min with 1× PBS. The cover-slips were washed in PBS and mounted on glass slides. The cells were then observed under an Olympus epifluorescence microscope.
Cell Adhesion Molecule
Hierarchical Cluster Analysis
protein containing a cystein-rich domain described in Lin-11, Il-1 and Mec-3 proteins
Myogenic Regulatory Factor
Neural cell adhesion molecule
Principal Component Analysis
Peroxysome Proliferator-Activated Receptor.
This work was supported by the Limousin Regional Council, and the French Ministry of Research and Technology doctoral fellowships of M. Janot and A. Audfray.
- Buckingham M, Bajard L, Chang T, Daubas P, Hadchouel J, Meilhac S, Montarras D, Rocancourt D, Relaix F: The formation of skeletal muscle: from somite to limb. J Anat. 2003, 202: 59-68. 10.1046/j.1469-7580.2003.00139.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Tapscott SJ: The circuitry of a master switch: Myod and the regulation of skeletal muscle gene transcription. Development. 2005, 132: 2685-2695. 10.1242/dev.01874.View ArticlePubMedGoogle Scholar
- Naya FJ, Olson E: MEF2: a transcriptional target for signaling pathways controlling skeletal muscle growth and differentiation. Curr Opin Cell Biol. 1999, 11: 683-688. 10.1016/S0955-0674(99)00036-8.View ArticlePubMedGoogle Scholar
- Rudnicki MA, Jaenisch R: The MyoD family of transcription factors and skeletal myogenesis. Bioessays. 1995, 17: 203-209. 10.1002/bies.950170306.View ArticlePubMedGoogle Scholar
- Black BL, Olson EN: Transcriptional control of muscle development by myocyte enhancer factor-2 (MEF2) proteins. Annu Rev Cell Dev Biol. 1998, 14: 167-196. 10.1146/annurev.cellbio.14.1.167.View ArticlePubMedGoogle Scholar
- Murre C, McCaw PS, Vaessin H, Caudy M, Jan LY, Jan YN, Cabrera CV, Buskin JN, Hauschka SD, Lassar AB, et al: Interactions between heterologous helix-loop-helix proteins generate complexes that bind specifically to a common DNA sequence. Cell. 1989, 58: 537-544. 10.1016/0092-8674(89)90434-0.View ArticlePubMedGoogle Scholar
- Lassar AB, Davis RL, Wright WE, Kadesch T, Murre C, Voronova A, Baltimore D, Weintraub H: Functional activity of myogenic HLH proteins requires hetero-oligomerization with E12/E47-like proteins in vivo. Cell. 1991, 66: 305-315. 10.1016/0092-8674(91)90620-E.View ArticlePubMedGoogle Scholar
- Blackwell TK, Weintraub H: Differences and similarities in DNA-binding preferences of MyoD and E2A protein complexes revealed by binding site selection. Science. 1990, 250: 1104-1110. 10.1126/science.2174572.View ArticlePubMedGoogle Scholar
- Meissner JD, Umeda PK, Chang KC, Gros G, Scheibe RJ: Activation of the beta myosin heavy chain promoter by MEF-2D, MyoD, p300, and the calcineurin/NFATc1 pathway. J Cell Physiol. 2007, 211: 138-148. 10.1002/jcp.20916.View ArticlePubMedGoogle Scholar
- Kang JS, Mulieri PJ, Hu Y, Taliana1 L, Krauss RS: BOC, an Ig superfamily member, associates with CDO to positively regulate myogenic differentiation. The EMBO Journal. 2002, 21: 114-124. 10.1093/emboj/21.1.114.PubMed CentralView ArticlePubMedGoogle Scholar
- Kang JS, Yi MJ, Zhang W, Feinleib JL, Cole F, Krauss RS: Netrins and neogenin promote myotube formation. J Cell Biol. 2004, 167: 493-504. 10.1083/jcb.200405039.PubMed CentralView ArticlePubMedGoogle Scholar
- Cuenda A, Cohen P: Stress-activated protein kinase-2/p38 and a rapamycin-sensitive pathway are required for C2C12 myogenesis. J Biol Chem. 1999, 274: 4341-4346. 10.1074/jbc.274.7.4341.View ArticlePubMedGoogle Scholar
- Moran JL, Li Y, Hill AA, Mounts WM, Miller CP: Gene expression changes during mouse skeletal myoblast differentiation revealed by transcriptional profiling. Physiol Genomics. 2002, 10: 103-111.View ArticlePubMedGoogle Scholar
- Shen X, Collier JM, Hlaing M, Zhang L, Delshad EH, Bristow J, Bernstein HS: Genome-wide examination of myoblast cell cycle withdrawal during differentiation. Dev Dyn. 2003, 226: 128-138. 10.1002/dvdy.10200.View ArticlePubMedGoogle Scholar
- Delgado I, Huang X, Jones S, Zhang L, Hatcher R, Gao B, Zhang P: Dynamic gene expression during the onset of myoblast differentiation in vitro. Genomics. 2003, 82: 109-121. 10.1016/S0888-7543(03)00104-6.View ArticlePubMedGoogle Scholar
- Tomczak KK, Marinescu VD, Ramoni MF, Sanoudou D, Montanaro F, Han M, Kunkel LM, Kohane IS, Beggs AH: Expression profiling and identification of novel genes involved in myogenic differentiation. FASEB J. 2004, 18: 403-405.PubMedGoogle Scholar
- Puente LG, Carrière JF, Kelly JF, Megeney LA: Comparative analysis of phosphoprotein-enriched myocyte proteomes reveals widespread alterations during differentiation. FEBS Lett. 2004, 574: 138-144. 10.1016/j.febslet.2004.08.019.View ArticlePubMedGoogle Scholar
- Kislinger T, Gramolini AO, Pan Y, Rahman K, MacLennan DH, Emili A: Proteome dynamics during C2C12 myoblast differentiation. Mol Cell Proteomics. 2005, 4: 887-901. 10.1074/mcp.M400182-MCP200.View ArticlePubMedGoogle Scholar
- Osses N, Brandan E: ECM is required for skeletal muscle differentiation independently of muscle regulatory factor expression. Am J Physiol Cell Physiol. 2002, 282: C383-394.View ArticlePubMedGoogle Scholar
- Cornelison DD, Wilcox-Adelman SA, Goetinck PF, Rauvala H, Rapraeger AC, Olwin BB: Essential and separable roles for Syndecan-3 and Syndecan-4 in skeletal muscle development and regeneration. Genes Dev. 2004, 18: 2231-2236. 10.1101/gad.1214204.PubMed CentralView ArticlePubMedGoogle Scholar
- Olden K, Law J, Hunter VA, Romain R, Parent JB: Inhibition of fusion of embryonic muscle cells in culture by tunicamycin is prevented by leupeptin. J Cell Biol. 1981, 88: 199-204. 10.1083/jcb.88.1.199.View ArticlePubMedGoogle Scholar
- Metzler M, Gertz A, Sarkar M, Schachter H, Schrader JW, Marth JD: Complex asparagine-linked oligosaccharides are required for morphogenic events during post-implantation development. EMBO J. 1994, 13: 2056-2065.PubMed CentralPubMedGoogle Scholar
- Fazeli S, Wells DJ, Hobbs C, Walsh FS: Altered secondary myogenesis in transgenic animals expressing the neural cell adhesion molecule under the control of a skeletal muscle alpha-actin promoter. J Cell Biol. 1996, 135: 241-251. 10.1083/jcb.135.1.241.View ArticlePubMedGoogle Scholar
- Suzuki M, Angata K, Nakayama J, Fukuda M: Polysialic acid and mucin type O-glycans on the neural cell adhesion molecule differentially regulate myoblast fusion. J Biol Chem. 2003, 278: 49459-49468. 10.1074/jbc.M308316200.View ArticlePubMedGoogle Scholar
- Fukumoto S, Iwamoto T, Sakai E, Yuasa K, Fukumoto E, Yamada A, Hasegawa T, Nonaka K, Kato Y: Current topics in pharmacological research on bone metabolism: osteoclast differentiation regulated by glycosphingolipids. J Pharmacol Sci. 2006, 100: 195-200. 10.1254/jphs.FMJ05004X3.View ArticlePubMedGoogle Scholar
- Yanagisawa M, Yu RK: The expression and functions of glycoconjugates in neural stem cells. Glycobiology. 2007, 17: 57R-74R. 10.1093/glycob/cwm018.View ArticlePubMedGoogle Scholar
- Leskawa KC, Hogan EL: Regulation of glycolipid synthesis during differentiation of clonal murine muscle cells. Mol Cell Biochem. 1990, 96: 163-173. 10.1007/BF00420908.View ArticlePubMedGoogle Scholar
- Cambron LD, Leskawa KC: Glycosphingolipids during skeletal muscle cell differentiation: comparison of normal and fusion-defective myoblasts. Mol Cell Biochem. 1994, 130: 173-185. 10.1007/BF01457398.View ArticlePubMedGoogle Scholar
- Ornatsky OI, McDermott JC: MEF2 protein expression, DNA binding specificity and complex composition, and transcriptional activity in muscle and non-muscle cells. J Biol Chem. 1996, 271: 24927-24933. 10.1074/jbc.271.40.24927.View ArticlePubMedGoogle Scholar
- Kong Y, Flick MJ, Kudla AJ, Konieczny SF: Muscle LIM protein promotes myogenesis by enhancing the activity of MyoD. Mol Cell Biol. 1997, 17: 4750-4760.PubMed CentralView ArticlePubMedGoogle Scholar
- Cossins J, Vernon AE, Zhang Y, Philpott A, Jones PH: Hes6 regulates myogenic differentiation. Development. 2002, 129: 2195-2207.PubMedGoogle Scholar
- Shimokawa T, Kato M, Ezaki O, Hashimoto S: Transcriptional regulation of muscle-specific genes during myoblast differentiation. Biochem Biophys Res Commun. 1998, 246: 287-292. 10.1006/bbrc.1998.8600.View ArticlePubMedGoogle Scholar
- Dedieu S, Mazeres G, Cottin P, Brustis JJ: Involvement of myogenic regulator factors during fusion in the cell line C2C12. Int J Dev Biol. 2002, 46: 235-241.PubMedGoogle Scholar
- Provenzano M, Mocellin S: Complementary techniques: validation of gene expression data by quantitative real time PCR. Adv Exp Med Biol. 2007, 593: 66-73. full_text.View ArticlePubMedGoogle Scholar
- Bai KJ, Spicer AP, Mascarenhas MM, Yu L, Ochoa CD, Garg HG, Quinn DA: The role of hyaluronan synthase 3 in ventilator-induced lung injury. Am J Respir Crit Care Med. 2005, 172: 92-98. 10.1164/rccm.200405-652OC.PubMed CentralView ArticlePubMedGoogle Scholar
- Farmery MR, Allen S, Allen AJ, Bulleid NJ: The role of ERp57 in disulfide bond formation during the assembly of major histocompatibility complex class I in a synchronized semipermeabilized cell translation system. J Biol Chem. 2000, 275: 14933-14938. 10.1074/jbc.275.20.14933.View ArticlePubMedGoogle Scholar
- Anastasia L, Papini N, Colazzo F, Palazzolo G, Tringali C, Dileo L, Piccoli M, Conforti E, Sitzia C, Monti E, Sampaolesi M, Tettamanti G, Venerando B: NEU3 sialidase strictly modulates GM3 levels in skeletal myoblasts C2C12 thus favoring their differentiation and protecting them from apoptosis. J Biol Chem. 2008, 283: 36265-36271. 10.1074/jbc.M805755200.PubMed CentralView ArticlePubMedGoogle Scholar
- Prados B, Peña A, Cotarelo RP, Valero MC, Cruces J: Expression of the murine Pomt1 gene in both the developing brain and adult muscle tissues and its relationship with clinical aspects of Walker-Warburg syndrome. Am J Pathol. 2007, 170: 1659-1668. 10.2353/ajpath.2007.061264.PubMed CentralView ArticlePubMedGoogle Scholar
- Brun RP, Kim JB, Hu E, Altiok S, Spiegelman BM: Adipocyte differentiation: a transcriptional regulatory cascade. Curr Opin Cell Biol. 1996, 8: 826-832. 10.1016/S0955-0674(96)80084-6.View ArticlePubMedGoogle Scholar
- Gregoire FM, Smas CM, Sul HS: Understanding adipocyte differentiation. Physiol Rev. 1998, 78: 783-809.PubMedGoogle Scholar
- Chui PC, Guan HP, Lehrke M, Lazar MA: PPARgamma regulates adipocyte cholesterol metabolism via oxidized LDL receptor 1. J Clin Invest. 2005, 115: 2244-2256. 10.1172/JCI24130.PubMed CentralView ArticlePubMedGoogle Scholar
- Moran JL, Johnston SH, Rauskolb C, Bhalerao J, Bowcock AM, Vogt TF: Genomic structure, mapping, and expression analysis of the mammalian Lunatic, Manic, and Radical fringe genes. Mamm Genome. 1999, 10: 535-541. 10.1007/s003359901039.View ArticlePubMedGoogle Scholar
- Haines N, Irvine KD: Glycosylation regulates Notch signalling. Nat Rev Mol Cell Biol. 2003, 4: 786-797.View ArticlePubMedGoogle Scholar
- Johnston SH, Rauskolb C, Wilson R, Prabhakaran B, Irvine KD, Vogt TF: A family of mammalian Fringe genes implicated in boundary determination and the Notch pathway. Development. 1997, 124: 2245-2254.PubMedGoogle Scholar
- Buas MF, Kabak S, Kadesch T: Inhibition of myogenesis by Notch: evidence for multiplepathways. J Cell Physiol. 2009, 218: 84-93. 10.1002/jcp.21571.PubMed CentralView ArticlePubMedGoogle Scholar
- Yang RY, Hsu DK, Yu L, Chen HY, Liu FT: Galectin-12 is required for adipogenic signaling and adipocyte differentiation. J Biol Chem. 2004, 279: 29761-29766. 10.1074/jbc.M401303200.View ArticlePubMedGoogle Scholar
- Handel TM, Johnson Z, Crown SE, Lau EK, Proudfoot AE: Regulation of protein function by glycosaminoglycans--as exemplified by chemokines. Annu Rev Biochem. 2005, 74: 385-410. 10.1146/annurev.biochem.72.121801.161747.View ArticlePubMedGoogle Scholar
- Funderburgh JL, Mitschler RR, Funderburgh ML, Roth MR, Chapes SK, Conrad GW: Macrophage receptors for lumican. A corneal keratan sulfate proteoglycan. Invest Ophthalmol Vis Sci. 1997, 38: 1159-1167.PubMedGoogle Scholar
- Fukushi J, Makagiansar IT, Stallcup WB: NG2 proteoglycan promotes endothelial cell motility and angiogenesis via engagement of galectin-3 and alpha3beta1 integrin. Mol Biol Cell. 2004, 15: 3580-3590. 10.1091/mbc.E04-03-0236.PubMed CentralView ArticlePubMedGoogle Scholar
- Brancaccio M, Guazzone S, Menini N, Sibona E, Hirsch E, De Andrea M, Rocchi M, Altruda F, Tarone G, Silengo L: Melusin is a new muscle-specific interactor for beta(1) integrin cytoplasmic domain. J Biol Chem. 1999, 274: 29282-29288. 10.1074/jbc.274.41.29282.View ArticlePubMedGoogle Scholar
- Schöber S, Mielenz D: The Role of Extracellular and Cytoplasmic Splice Domains of [alpha]7-Integrin in Cell Adhesion and Migration on Laminins. Experimental Cell Research. 2000, 255: 303-313. 10.1006/excr.2000.4806.View ArticlePubMedGoogle Scholar
- Blanco-Bose WE, Blau HM: Laminin-induced change in conformation of preexisting alpha7beta1 integrin signals secondary myofiber formation. Dev Biol. 2001, 233: 148-160. 10.1006/dbio.2001.0177.View ArticlePubMedGoogle Scholar
- Stuart CA, Yin D, Howell ME, Dykes RJ, Laffan JJ, Ferrando AA: Hexose transporter mRNAs for GLUT4, GLUT5, and GLUT12 predominate in human muscle. Am J Physiol Endocrinol Metab. 2006, 291: E1067-E1073. 10.1152/ajpendo.00250.2006.View ArticlePubMedGoogle Scholar
- Im SS, Kwon SK, Kim TH, Kim HI, Ahn YH: Regulation of glucose transporter type 4 isoform gene expression in muscle and adipocytes. IUBMB Life. 2007, 59: 134-145. 10.1080/15216540701313788.View ArticlePubMedGoogle Scholar
- Hajduch E, Litherland GJ, Turban S, Brot-Laroche E, Hundal HS: Insulin regulates the expression of the GLUT5 transporter in L6 skeletal muscle cells. FEBS Lett. 2003, 549: 77-82. 10.1016/S0014-5793(03)00773-7.View ArticlePubMedGoogle Scholar
- Lisinski I, Schürmann A, Joost HG, Cushman SW, Al-Hasani H: Targeting of GLUT6 (formerly GLUT9) and GLUT8 in rat adipose cells. Biochem J. 2001, 358: 517-522. 10.1042/0264-6021:3580517.PubMed CentralView ArticlePubMedGoogle Scholar
- Clemmensen I: Interaction of tetranectin with sulphated polysaccharides and trypan blue. Scand J Clin Lab Invest. 1989, 49: 719-725. 10.3109/00365518909091550.View ArticlePubMedGoogle Scholar
- Hayashi Y, Okino N, Kakuta Y, Shikanai T, Tani M, Narimatsu H, Ito M: Klotho-related protein is a novel cytosolic neutral beta-glycosylceramidase. J Biol Chem. 2007, 282: 30889-30900. 10.1074/jbc.M700832200.View ArticlePubMedGoogle Scholar
- GenBank. [http://www.ncbi.nlm.nih.gov/Genbank/]
- The CAZy database. [http://www.cazy.org/]
- The Mouse Genome Informatics. [http://www.informatics.jax.org]
- Hammer O, Harper DAT, Ryan PD: PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica. 2001, 4: 9-Google Scholar
- The Paleontological Statistics Software Package for Education and Data Analysis. [http://folk.uio.no/ohammer/past/download.html]
- The Kegg Pathway Database. [http://www.genome.ad.jp/kegg/pathway.html]
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.