HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Data Supplement All Versions of this Article: 10/2/103    most recent 00011.2002v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (18) Citing Articles via Google Scholar Google Scholar Articles by Moran, J. L. Articles by Miller, C. P. Search for Related Content PubMed PubMed Citation Articles by Moran, J. L. Articles by Miller, C. P.

Gene expression changes during mouse skeletal myoblast differentiation revealed by transcriptional profiling

Department of Genomics, Wyeth Research, Cambridge, Massachusetts 02140

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Studies described here utilize high-density oligonucleotide arrays to characterize changes in global mRNA expression patterns during proliferation, cell cycle withdrawal, and terminal differentiation in mouse C2C12 myoblasts. Statistical analyses revealed 629 sequences differentially regulated between proliferating and differentiating myoblasts. These genes were clustered using self-organizing maps to identify sets of coregulated genes and were assigned to functional categories that were analyzed for distribution across expression clusters. Clusters were identified with statistically significant enrichment of functional categories including muscle contraction, cell adhesion, extracellular matrix function, cellular metabolism, mitochondrial transport, DNA replication, cell cycle control, mRNA transcription, and unexpectedly, immune regulation. In addition, functional category enrichment data can be used to predict gene function for numerous differentially regulated expressed sequence tags. The results provide new insight into how genes involved in these cellular processes may play a role in skeletal muscle growth and differentiation.

C2C12 cells; oligonucleotide array; functional category enrichment

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
SKELETAL MUSCLE DIFFERENTIATION is a highly ordered process requiring myocyte proliferation, expression of muscle-specific regulatory factors, cell cycle withdrawal, and the synthesis of muscle contractile proteins, resulting in the fusion of mononucleated myoblasts into terminally differentiated multinucleated myotubes (1). Myocyte differentiation is regulated by four myogenic regulatory factors (MRFs): MyoD, Myf5, myogenin, and MRF4 (Myf6) (28, 39). These muscle-specific basic helix-loop-helix (bHLH) transcription factors cooperate with the MEF2 family of MADS box transcription factors to activate transcription of muscle structural genes through E-box and MEF2 promoter sites, respectively (5). Negative regulators of muscle gene transcription include the Id dominant-negative HLH proteins, which sequester bHLH proteins into complexes incapable of binding DNA, and the bHLH protein twist (reviewed in Ref. 2).

The myogenic program consists of two temporally separated processes: myoblast proliferation and differentiation. Proliferating mononucleate myoblasts expressing MyoD and Myf5 are committed to the muscle lineage and will continue to proliferate in the presence of mitogens under high-serum conditions in vitro. Upon serum deprivation, myoblasts activate transcription of myogenin and undergo irreversible cell cycle arrest following transcription of the cyclin-dependent kinase (Cdk) inhibitor, p21, and dephosphorylation of pRb (1, 40). Skeletal muscle differentiation then proceeds through the induction of muscle-specific gene expression and fusion of myoblasts into myotubes (1, 13, 14, 29, 41).

Here, we have used high-density oligonucleotide arrays to investigate transcriptional changes occurring during myoblast proliferation and differentiation in C2C12 cells, a well-characterized in vitro model of mouse skeletal muscle cell differentiation (1, 6). DNA microarray technology enables highly parallel analysis of mRNA expression patterns. The use of DNA microarrays to identify genes involved in skeletal muscle function and pathology has been limited to studies of mouse and monkey muscle aging and the effects of caloric restriction, as well as alveolar rhabdomyosarcomas (19, 20, 22, 42). We have identified sets of genes whose transcripts are differentially regulated between proliferating and differentiating C2C12 cells and have clustered these genes according to expression profiles. Systematic evaluation of the distribution of genes by biological function has revealed many clusters statistically enriched in functions relevant to skeletal muscle growth and differentiation.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Cell Culture and RNA isolation.
C2C12 cells (6) were plated at a density of 53,000 cells per 100-mm-diameter plate in growth medium (GM; DMEM plus 20% fetal bovine serum, 200 mM L-glutamine, 10 U/ml penicillin, and 10 µg/ml streptomycin). After 72 h (80% confluence), cells were rinsed briefly with PBS then grown in differentiation medium (DM; DMEM plus 1% bovine serum albumin) to initiate myogenic differentiation. Cells were harvested by lysis with Trizol Reagent (Invitrogen, Carlsbad, CA) 48 h and 72 h after plating in GM [GM and day 0 (d0) time points, respectively] and 24 h and 96 h after switching to DM [day 1 (d1) and day 4 (d4) time points, respectively]. Total RNA was isolated by Trizol extraction, and mRNA was isolated using the PolyATract mRNA Isolation System IV (Promega, Madison, WI).

Preparation of labeled targets and high-density oligonucleotide array hybridization.
Poly(A)⁺ mRNA samples were prepared independently from two total RNA samples at each time point. One microgram of each poly(A)⁺ mRNA sample was used to generate amplified, biotin-labeled cRNA. Ten micrograms of fragmented, biotin-labeled cRNA was mixed with 11 internal control labeled spike-in transcripts and hybridized in duplicate to oligonucleotide arrays containing 11,000 distinct murine genes and expressed sequence tags (ESTs). cRNA labeling, microarray hybridization, staining, and visualization was performed as described by Hill et al. (15).

Data analysis.
Absolute decision calls ("present," "absent," or "marginal") for each gene on the arrays were determined by the GeneChip Software (Affymetrix, Santa Clara, CA). Transcript levels, indicated as gene frequency, were quantified as described by Hill et al. (15). There were 5,303 genes we called "present," with a frequency higher than the sensitivity of detection in a minimum of 4 of 16 arrays (4 replicates at 4 time points), and these were selected for further data analysis.

The experimental design has both a treatment variable and a time variable, where treatment refers to the two conditions in which the cells were grown: GM or DM. Cells grown under each treatment condition were harvested at two time points (treatment intervals). Frequency values for 5,303 genes were subjected to one-way nested analysis of variance (ANOVA) tests. ANOVA P values calculated for each gene were adjusted with the Bonferroni method of multiple comparison to control for type I error rate (33). Genes with Bonferroni-adjusted significance levels less than 1% (n = 644) were considered to have statistically significant changes in gene expression between treatments and/or between treatment intervals. Mean frequencies for each gene at each time point were calculated from the individual frequency values over four replicates. For low-frequency genes (maximum mean frequencies less than 40 for all time points), additional criteria were imposed to increase confidence that the estimated changes reflect real differences in expression levels. To qualify, low-abundance mRNAs had to exhibit an arithmetic difference greater than 10 and at least a 2.5-fold difference between the maximum and minimum mean frequencies for all time points. Fifteen genes with low mean frequencies did not pass these additional criteria. For cluster analysis, mean expression frequencies of 629 genes with differential expression were scaled so that each gene had a mean value of zero and a variance of one, and the scaled expression profiles were clustered using a self-organizing map (SOM) algorithm (36).

Enrichment of functional categories within expression clusters.
BLAST searches were performed with EST sequences against GenBank and Affymetrix Hu6800 gene sequences to identify gene hits and provide annotation. We classified 544 distinct genes into functional categories using a hierarchical classification scheme modified from Cho et al. (8) with 167 categories. Assignments were made to one or more categories using gene annotation from GeneExpress 2000 (Gene Logic, Gaithersburg, MD) and publicly available databases. Of 433 distinct annotated genes, 382 were assigned to functional categories, with 193 being assigned more than one category. We designated 111 sequences as ESTs. Since the classification scheme is hierarchical, with several categories having multiple subcategories, fold enrichment and P values were calculated for each level of the hierarchy independently. For each category in each cluster, a fold enrichment value was calculated based on the frequency of the category in the cluster compared with the frequency of the category in the entire set of 544 transcripts. P values were calculated using the hypergeometric probability distribution (38) and represent the probability of observing fold enrichment of the category among a random sampling of genes.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

Expression profiling of proliferating and differentiating C2C12 cells.
To identify genes that may play a role in myogenesis, we examined the expression profiles of thousands of genes during myocyte proliferation and differentiation in C2C12 cells (Fig. 1). There are 629 transcripts, representing 433 distinct genes and 111 distinct ESTs, that are differentially regulated during the differentiation time course. SOM analysis (36) identified clusters of tightly regulated transcripts with similar expression profiles, independent of their overall expression level (Fig. 2). The resulting clusters highlight two predominant expression patterns: an increase of mRNA levels during the differentiation time course (e.g., clusters in row 1 of the matrix) and a decrease in mRNA levels (e.g., clusters in rows 3 and 4). Most differential mRNA expression occurs during the transition from GM to DM (e.g., cluster 1,4), and from early DM to late DM (e.g., cluster 1,1).

View larger version (9K): [in this window] [in a new window]   Fig. 1. C2C12 differentiation time course. C2C12 myocytes were plated in growth media containing 20% fetal bovine serum until 80% confluence and then grown in differentiation media in the absence of serum. Cells were harvested for RNA isolation at 4 time points: growth media (GM), day 0 (d0), day 1 (d1), and day 4 (d4). The GM and d0 cells were harvested 1 day and just prior to serum withdrawal, respectively. The d1 and d4 cells were harvested 1 day and 4 days, respectively, after serum withdrawal.

View larger version (55K): [in this window] [in a new window]   Fig. 2. A self-organizing map (SOM) of C2C12 gene expression profiles. Here, 629 sequences show regulated gene expression during C2C12 differentiation. These were grouped into 16 clusters using a 4 x 4 SOM. The labels above each cluster indicate the name of the cluster (in parentheses) followed by the number of sequences grouped into the cluster. Normalized expression levels (with a mean of 0 and a variance of 1) are shown on the y-axis, and time points [growth media (GM), day 0 (d0), day 1 (d1), and day 4 (d4)] are on the x-axis (see cluster 4,1 for x-axis labels).

Cell adhesion and extracellular matrix genes.
Cluster 1,3 is significantly enriched in genes with extracellular matrix (ECM) and cell adhesion functions, and cluster 1,4 is significantly enriched in cell adhesion genes (Table 2). In both clusters, genes are often classified as having both ECM and cell adhesion functions.

Multiple components of the myocyte basal lamina [type IV collagens (Col4a1, Col4a2), nidogen 2 (Nid2), and ß -dystroglycan (Dag1)] have maximal transcript levels 24 h after serum withdrawal (Fig. 3A). Five additional collagen transcripts (Col6a1, Col6a2, Col8a1, Col3a1, Col5a2) and other ECM protein-encoding transcripts, including matrix metalloprotease 2, matrix-associated glycoprotein 2 (Magp2), matrillin 2, syndecan 2, and matrix Gla protein (Mglap), are also upregulated during early myoblast differentiation (Table 2). Several genes with cell adhesion functions [decorin (Dcn), Cd81, tetraspanin-3 (Tm4sf8), Vcam1, Ncam, and M-cadherin (Cdh15)] are expressed at highest levels in terminally differentiated myocytes (Fig. 3).

View larger version (24K): [in this window] [in a new window]   Fig. 3. Absolute mRNA levels for selected genes with cell adhesion and extracellular matrix (ECM) functions during C2C12 differentiation. The mean frequency of each gene over 4 replicates is plotted for each time point (GM, d0, d1, and d4). Genes that are upregulated in early differentiating myoblasts are shown in A, and genes with maximal expression in differentiated myotubes are shown in B.

Genes involved in cellular metabolism.
Cluster 2,1 is enriched in genes with roles in carbohydrate metabolism (Tables 1 and 2), and other key glycolytic enzymes (Pfka and Pygm) are observed in the related cluster 1,1. Cluster 1,1 is enriched in amino acid transport genes, Slc1a6 (Eeat4) and Mdu1 (4F2hc), which are members of the transport systems X_AG^- and L,y⁺, respectively (Tables 1 and 2).

Cluster 3,1 is significantly enriched in transcripts encoding mitochondrial transport proteins (Timm9, Timm13a, Timm23, Slc25a5), which are coregulated with genes required for oxidative respiration [cytochrome c (Cycs) and ATP synthase (Atp5g1)].

Genes involved in cell cycle regulation, DNA replication, mRNA transcription, and chromatin modification.
Clusters in rows 3 and 4 of the cluster matrix (Fig. 2) are enriched in genes with functions necessary for actively proliferating cells: mRNA transcription, DNA replication, and cell cycle control and mitosis. Cluster 3,2 is significantly enriched in genes functioning in cell cycle control and mitosis as well as the subcategory chromosome segregation. In addition, 20 cell cycle control genes are present in clusters 3,3 and 4,3 (Tables 1 and 2; and Supplemental Data¹ published online at the Physiological Genomics web site). Such coordinately regulated genes include cyclins (Ccna2, Ccnb1-rs1), protein kinases (Cdc2a, Cdk4, Cks1, Cks2), protein phosphatases (Cdc25c, Cdkn3, Ppp1r7), and chromosome segregation genes (e.g., Bub3, Ran, Rangap1, Ranbp1) (Fig. 4A). The cyclin-dependent kinase inhibitors, p21^Cip1 (Cdkn1a; cluster 1,1) and p57^Kip2 (Cdkn1c; cluster 1,4), as well as other genes functioning in negative growth control (Bin1, Gadd45a, Gadd45b, and Gadd45g), are appropriately expressed in an opposite pattern to cell cycle promoting genes (Figs. 2 and 4B).

View larger version (29K): [in this window] [in a new window]   Fig. 4. Absolute mRNA levels for genes with roles in cell cycle control and mitosis (A) and negative growth control (B). The mean frequency of each gene over 4 replicates is plotted for each time point (GM, d0, d1, and d4).

DNA replication genes are enriched in cluster 4,3, and additional replication genes are found in rows 3 and 4 of the cluster matrix, including minichromosome-deficient family members, ribonuclease reductase M1 genes, and proliferating cell nuclear antigen A (Pcna) (Tables 1 and 2; Fig. 4A; and Supplemental Data).

Other proliferation and differentiation genes.
A number of transcription factors and signaling molecules with regulatory roles in cellular proliferation and differentiation were differentially regulated during C2C12 myogenesis (Fig. 5). Transcription factors increasing during muscle differentiation include MyoD1, Six1, Stat3, Hes6, Klf4, and Osf2 (Fig. 5A). Members of the Id gene family of differentiation inhibitors, Idb1, Idb2, and Idb3, were all expressed at higher levels in proliferating myoblasts and decrease in expression in differentiating cells (Fig. 5B). Expression of the secreted growth and differentiation factor, Igf2, is increased greater than 10-fold upon differentiation in C2C12 cells, as are transcripts for several IGF binding proteins (Igfbp2, Igfbp5, and Nov) (Fig. 5C). Members of the TGFß gene family of secreted signaling molecules, activin (Inhbb) and TGFß3 (Tgfb3) as well as the bone morphogenetic protein (BMP) inhibitor, follistatin (Fst), increase in expression at day 0 and peak in differentiating muscle cells (Fig. 5C). Other signaling pathways important in cellular differentiation, the Notch and Wnt pathways, have members [Notch3 and Sfrp-2 (Sdf5), respectively] that are expressed at highest levels in differentiated C2C12 cells.

View larger version (21K): [in this window] [in a new window]   Fig. 5. Absolute mRNA levels for selected genes with regulatory roles in proliferation and differentiation during C2C12 differentiation time course. The mean frequency of each gene over 4 replicates is plotted for each time point (GM, d0, d1, and d4). Transcription factors upregulated (A) or downregulated (B) during myogenesis and secreted signaling molecules (C).

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

Clustering and functional classification of differentially regulated genes and subsequent statistical analysis of the distribution of functional categories identified both expected and unexpected results. Enrichment for genes involved in muscle contraction, cytoskeletal organization, cell adhesion, cell-matrix interactions, cellular metabolism, cell cycle regulation, DNA replication, and mRNA transcription were anticipated.

Transcripts encoding muscle contractile apparatus proteins, proteins regulating muscle contraction, cell-cell interactions, and cell-matrix interactions increase in expression during the differentiation process (Fig. 2; Table 2). Cell-matrix and cell-cell interactions mediate terminal differentiation of myoblasts including cell fusion and assembly of the muscle contractile apparatus (26, 27). Thus, besides upregulating the expression of genes responsible for muscle contraction, differentiating myocytes promote muscle integrity and function by expressing genes encoding structural and regulatory components of the myocyte extracellular matrix and plasma membrane.

Muscle cells utilize glucose, fatty acid, ketone bodies, and amino acids as fuel sources and store glucose mainly as glycogen. In addition, muscle is the major storage tissue of amino acids. Our study identified several genes that are upregulated in differentiating cells that function in carbohydrate metabolism (Table 2). Elevated expression of amino acid transporters in differentiated myotubes (Table 2) may be due to an increase in amino acid storage requirements or may be a cellular response to low nutrient levels induced by serum starvation.

Cell cycle progression requires ATP for many cellular processes including protein synthesis, degradation, and cytoskeletal rearrangements. Most cellular ATP is synthesized through mitochondrial oxidative phosphorylation. We found that transcripts encoding proteins required for oxidative respiration were coregulated with transcripts encoding mitochondrial transport proteins (Table 2; Fig. 2). In addition to metabolic requirements, actively proliferating cells require DNA replication, mRNA transcription, and cell division. Several clusters with genes that are downregulated upon the initiation of myogenic differentiation are enriched in such functional categories (Table 2).

Surprisingly, our study revealed several clusters that are enriched in genes with immune functions (Table 2). Of all genes with immunity roles, the majority function during the inflammatory process. Inflammation in response to muscle injury or disease is intimately associated with muscle regeneration (18). In muscle tissue, inflammation involves chemokine and cytokine production by damaged fibers, leukocyte and macrophage migration, and activation of muscle satellite cell proliferation and differentiation, followed by phagocytic apoptosis (4, 18, 31). Upregulation of chemokine and cytokine mRNA expression during early or late differentiation may act as a trigger to promote muscle regeneration through leukocyte and macrophage recruitment, bone-marrow-derived stem cell recruitment (10), or may be part of a cellular response to serum deprivation.

Many of the genes that we have identified as differentially regulated transcripts by DNA microarray expression profiling have been characterized previously in C2C12 cells or other skeletal muscle cell lines by mRNA transcription methods and/or by functional analysis. Those characterized by both expression and functional analyses by others include Igf2 (reviewed in Ref. 11), p21^Cip1 (Cdkn1a) (14), Bin1 (25), caveolin 3 (Cav3) (12, 37), M-cadherin (Cdh15) (21, 43), FasL (31), decorin (Dcn) (30), Idb1 (17), Idb3 (3, 7), and DNA methyltransferase (Dnmt1) (24, 35). In all of these cases, the RNA expression profile we have detected agrees with published reports.

In addition to identifying genes with previously characterized functions in muscle cell differentiation, our results highlight genes for which a potential role in skeletal muscle differentiation has not been defined. Several of these genes function in osteoblasts: the transcription factor, Osf2 (cluster 1,2) (9) and the osteoblast matrix proteins, osteomodulin/osteoadherin (Omd; cluster 1,1) (34) and osteoglycin (Ogn; cluster 1,3) (32). Osf2 (Cbfa1) mRNA expression is increased by BMP treatment of C2C12 cells, which causes a transformation from myogenic to osteoblast differentiation (23). The induction of Osf2 transcripts in differentiating C2C12 myoblasts that was observed in our study has not been observed by others. This discrepancy may be due to different culturing conditions, specifically the amount of serum in the medium. The presence of osteoblast extracellular matrix components in differentiating muscle cells may be indicative of the pluripotent state of C2C12 cells, which have the capacity to differentiate into osteoblasts when challenged with the appropriate cues. Alternatively, these extracellular matrix proteins may perform a generalized ECM function in differentiated cells.

A comparison of the genes identified in our study to those that have been functionally characterized in muscle cell lines and other expression profiling studies can provide clues as to the roles these genes are playing during the C2C12 differentiation process. Two relevant large-scale expression profiling studies examining the serum response in human fibroblasts (16) and the human fibroblast cell cycle (8) have identified genes that are also regulated in our study. In addition to the induction of cell cycle and proliferation genes [e.g., p57Kip2 (Cdkn1c), Pcna, Rrm1, Rrm2] and immediate-early transcription factors (Id2, Id3), Iyer and colleagues (16) observed a striking upregulation of genes involved in the wound healing process during the serum response. These genes are involved in a variety of cellular processes: inflammation/angiogenesis [Scya2 (MCP1)], tissue remodeling (Plaur, Fmod, Col3a1), signal transduction (Sgk) and chromosome segregation (Ranbp1). Fibroblast cell cycle regulated genes that are also differentially regulated during C2C12 differentiation include those involved in cell cycle control (e.g., Ccna2, Ccnb1, Cdc2, Cdkn1a), proliferation and differentiation (Notch3, Inhbb, Gadd45a, Gro1), and cell-cell adhesion/ extracellular matrix genes (Matn2, Nid2, Plaur, Hmmr, Tm4sf1) (8). Thus the identification of common genes regulated by serum addition and/or by cell cycle progression suggests that several of the transcriptional changes we have identified in the C2C12 time course may be due to mitotic synchronization, a physiological response to serum withdrawal (8).

Importantly, our study revealed 111 distinct ESTs with no appreciable similarity to known genes. Although ESTs were not significantly enriched as a functional category in any gene cluster, it is interesting to note that 50% of all ESTs are coordinately regulated in clusters 4,1 through 4,4, representing 30% of the unique genes in each of the four clusters (Fig. 2; and Supplemental Data). Our functional category enrichment data can be used to predict gene function and would suggest that many of these uncharacterized genes may function in mRNA transcription, chromatin modification, DNA replication, and cell cycle control and mitosis.

This study provides a useful database of genes that are differentially expressed throughout myogenic proliferation and differentiation. As we have reported functional categories that are statistically enriched in expression clusters and have highlighted only a portion of genes in this study, a more detailed analysis of all the data provided (see Supplemental Data) will allow others to investigate particular genes, pathways, or cellular processes of interest. Functional analysis of genes identified in this study as well as characterization of ESTs in in vitro and in vivo models, will likely lead to the identification of genes required for cell cycle progression and withdrawal and skeletal muscle differentiation.

	ACKNOWLEDGMENTS

 
We are grateful to N. Rosenthal for providing the C2C12 cell line.

	FOOTNOTES

 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: C. P. Miller, Dept. of Genomics, Wyeth Research, 35 Cambridge Park Drive, Cambridge, MA 02140 (E-mail: cmiller{at}wyeth.com).

10.1152/physiolgenomics.00011.2002.

¹ Supplementary materials (Supplemental Tables 1 and 2 and Supplemental Fig. 1) to this article are available online at http://physiolgenomics.physiology.org/cgi/content/full/10/2/103/DC1.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

1. Andres V and Walsh K. Myogenin expression, cell cycle withdrawal, and phenotypic differentiation are temporally separable events that precede cell fusion upon myogenesis. J Cell Biol 132: 657–666, 1996.[Abstract/Free Full Text]
2. Arnold HH and Winter B. Muscle differentiation: more complexity to the network of myogenic regulators. Curr Opin Genet Dev 8: 539–544, 1998.[ISI][Medline]
3. Atherton GT, Travers H, Deed R, and Norton JD. Regulation of cell differentiation in C2C12 myoblasts by the Id3 helix-loop-helix protein. Cell Growth Differ 7: 1059–1066, 1996.[Abstract]
4. Best TM and Hunter KD. Muscle injury and repair. Sci Princ Sports Rehab 11: 251–266, 2000.
5. Black BL and Olson EN. Transcriptional control of muscle development by myocyte enhancer factor-2 (MEF2) proteins. Annu Rev Cell Dev Biol 14: 167–196, 1998.[ISI][Medline]
6. Blau HM, Chiu CP, and Webster C. Cytoplasmic activation of human nuclear genes in stable heterocaryons. Cell 32: 1171–1180, 1983.[ISI][Medline]
7. Chen B, Han BH, Sun XH, and Lim RW. Inhibition of muscle-specific gene expression by Id3: requirement of the C-terminal region of the protein for stable expression and function. Nucleic Acids Res 25: 423–430, 1997.[Abstract/Free Full Text]
8. Cho RJ, Huang M, Campbell MJ, Dong H, Steinmetz L, Sapinoso L, Hampton G, Elledge SJ, Davis RW, and Lockhart DJ. Transcriptional regulation and function during the human cell cycle. Nat Genet 27: 48–54, 2001.[ISI][Medline]
9. Ducy P, Zhang R, Geoffroy V, Ridall AL, and Karsenty G. Osf2/Cbfa1: a transcriptional activator of osteoblast differentiation. Cell 89: 747–754, 1997.[ISI][Medline]
10. Ferrari G, Cusella-De Angelis G, Coletta M, Paolucci E, Stornaiuolo A, Cossu G, and Mavilio F. Muscle regeneration by bone marrow-derived myogenic progenitors. Science 279: 1528–1530, 1998.[Abstract/Free Full Text]
11. Florini JR, Ewton DZ, and Coolican SA. Growth hormone and the insulin-like growth factor system in myogenesis. Endocr Rev 17: 481–517, 1996.[Abstract]
12. Galbiati F, Volonte D, Chu JB, Li M, Fine SW, Fu M, Bermudez J, Pedemonte M, Weidenheim KM, Pestell RG, Minetti C, and Lisanti MP. Transgenic overexpression of caveolin-3 in skeletal muscle fibers induces a Duchenne-like muscular dystrophy phenotype. Proc Natl Acad Sci USA 97: 9689–9694, 2000.[Abstract/Free Full Text]
13. Guo K, Wang J, Andres V, Smith RC, and Walsh K. MyoD-induced expression of p21 inhibits cyclin-dependent kinase activity upon myocyte terminal differentiation. Mol Cell Biol 15: 3823–3829, 1995.[Abstract]
14. Halevy O, Novitch BG, Spicer DB, Skapek SX, Rhee J, Hannon GJ, Beach D, and Lassar AB. Correlation of terminal cell cycle arrest of skeletal muscle with induction of p21 by MyoD. Science 267: 1018–1021, 1995.[Abstract/Free Full Text]
15. Hill AA, Hunter CP, Tsung BT, Tucker-Kellogg G, and Brown EL. Genomic analysis of gene expression in C. elegans. Science 290: 809–812, 2000.[Abstract/Free Full Text]
16. Iyer VR, Eisen MB, Ross DT, Schuler G, Moore T, Lee JC, Trent JM, Staudt LM, Hudson J Jr, Boguski MS, Lashkari D, Shalon D, Botstein D, and Brown PO. The transcriptional program in the response of human fibroblasts to serum. Science 283: 83–87, 1999.[Abstract/Free Full Text]
17. Jen Y, Weintraub H, and Benezra R. Overexpression of Id protein inhibits the muscle differentiation program: in vivo association of Id with E2A proteins. Genes Dev 6: 1466–1479, 1992.[Abstract/Free Full Text]
18. Jesse TL, LaChance R, Iademarco MF, and Dean DC. Interferon regulatory factor-2 is a transcriptional activator in muscle where it regulates expression of vascular cell adhesion molecule-1. J Cell Biol 140: 1265–1276, 1998.[Abstract/Free Full Text]
19. Kayo T, Allison DB, Weindruch R, and Prolla TA. Influences of aging and caloric restriction on the transcriptional profile of skeletal muscle from rhesus monkeys. Proc Natl Acad Sci USA 98: 5093–5098, 2001.[Abstract/Free Full Text]
20. Khan J, Simon R, Bittner M, Chen Y, Leighton SB, Pohida T, Smith PD, Jiang Y, Gooden GC, Trent JM, and Meltzer PS. Gene expression profiling of alveolar rhabdomyosarcoma with cDNA microarrays. Cancer Res 58: 5009–5013, 1998.[Abstract/Free Full Text]
21. Kuch C, Winnekendonk D, Butz S, Unvericht U, Kemler R, and Starzinski-Powitz A. M-cadherin-mediated cell adhesion and complex formation with the catenins in myogenic mouse cells. Exp Cell Res 232: 331–338, 1997.[Medline]
22. Lee CK, Klopp RG, Weindruch R, and Prolla TA. Gene expression profile of aging and its retardation by caloric restriction. Science 285: 390–393, 1999.
23. Lee MH, Javed A, Kim HJ, Shin HI, Gutierrez S, Choi JY, Rosen V, Stein JL, van Wijnen AJ, Stein GS, Lian JB, and Ryoo HM. Transient upregulation of CBFA1 in response to bone morphogenetic protein-2 and transforming growth factor ß1 in C2C12 myogenic cells coincides with suppression of the myogenic phenotype but is not sufficient for osteoblast differentiation. J Cell Biochem 73: 114–125, 1999.[ISI][Medline]
24. Liu Y, Sun L, and Jost JP. In differentiating mouse myoblasts DNA methyltransferase is posttranscriptionally and posttranslationally regulated. Nucleic Acids Res 24: 2718–2722, 1996.[Abstract/Free Full Text]
25. Mao NC, Steingrimsson E, DuHadaway J, Waserman W, Ruiz JC, Copeland NG, Jenkins NA, and Prendergast GC. The murine Bin1 gene functions early in myogenesis and defines a new region of synteny between mouse chromosome 18 and human chromosome 2. Genomics 56: 51–58, 1999.[Medline]
26. McDonald KA, Horwitz AF, and Knudsen KA. Adhesion molecules and skeletal myogenesis. Semin Dev Biol 6: 105–116, 1995.
27. Melo F, Carey DJ, and Brandan E. Extracellular matrix is required for skeletal muscle differentiation but not myogenin expression. J Cell Biochem 62: 227–239, 1996.[Medline]
28. Molkentin JD and Olson EN. Defining the regulatory networks for muscle development. Curr Opin Genet Dev 6: 445–453, 1996.[ISI][Medline]
29. Parker SB, Eichele G, Zhang P, Rawls A, Sands AT, Bradley A, Olson EN, Harper JW, and Elledge SJ. p53-independent expression of p21 Cip1 in muscle and other terminal differentiating cells. Science 267: 1024–1027, 1995.[Abstract/Free Full Text]
30. Riguelme C, Larrain J, Schonherr E, Henriquez JP, Kresse H, and Brandan E. Antisense inhibition of decorin expression in myoblasts decreases cell responsiveness to transforming growth factor ß and accelerates skeletal muscle differentiation. J Biol Chem 276: 3589–3596, 2001.[Abstract/Free Full Text]
31. Sandri M, Sandri C, Brun B, Giurisato E, Cantini M, Rossini K, Destro C, Arslan P, and Carraro U. Inhibition of FasL sustains phagocytic cells and delays myogenesis in regenerating muscle fibers. J Leukoc Biol 69: 482–489, 2001.[Abstract/Free Full Text]
32. Shanahan CM, Cary NR, Osbourn JK, and Weissberg PL. Identification of osteoglycin as a component of the vascular matrix. Differential expression by vascular smooth muscle cells during neointima formation and in atherosclerotic plaques. Arterioscler Thromb Vasc Biol 17: 2437–2447, 1997.[Abstract/Free Full Text]
33. Sokal RR and Rohlf J. Biometry. New York: Freeman, 1994.
34. Sommarin Y, Wendel M, Shen Z, Hellman U, and Heinegard D. Osteoadherin, a cell-binding keratan sulfate proteoglycan in bone, belongs to the family of leucine-rich repeat proteins of the extracellular matrix. J Biol Chem 273: 16723–16729, 1998.[Abstract/Free Full Text]
35. Takagi H, Tajima S, and Asano A. Overexpression of DNA methyltransferase in myoblast cells accelerates myotube formation. Eur J Biochem 231: 282–291, 1995.[ISI][Medline]
36. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander ES, and Golub TR. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA 96: 2907–2912, 1999.[Abstract/Free Full Text]
37. Tang Z, Scherer PE, Okamoto T, Song K, and Chu C. Molecular cloning of caveolin-3, a novel member of the caveolin gene family expressed predominantly in muscle. J Biol Chem 271: 2255–2261, 1996.[Abstract/Free Full Text]
38. Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, and Church GM. Systematic determination of genetic network architecture. Nat Genet 22: 281–285, 1999.[ISI][Medline]
39. Venuti JM and Cserjesi P. Molecular embryology of skeletal myogenesis. Curr Top Dev Biol 34: 169–206, 1996.[Medline]
40. Walsh K and Perlman H. Cell cycle exit upon myogenic differentiation. Curr Opin Genet Dev 7: 597–602, 1997.[ISI][Medline]
41. Wang J and Walsh K. Resistance to apoptosis conferred by Cdk inhibitors during myocyte differentiation. Science 273: 359–361, 1996.[Abstract]
42. Weindruch R, Kayo T, Lee CK, and Prolla TA. Microarray profiling of gene expression in aging and its alteration by caloric restriction in mice. J Nutr 131: 918S–923S, 2001.[Abstract/Free Full Text]
43. Zeschnigk M, Kozian D, Kuch C, Schmoll M, and Starzinski-Powitz A. Involvement of M-cadherin in terminal differentiation of skeletal muscle cells. J Cell Sci 108: 2973–2981, 1995.[Abstract]

This article has been cited by other articles:

				S. J. Ho Sui, D. L. Fulton, D. J. Arenillas, A. T. Kwon, and W. W. Wasserman oPOSSUM: integrated tools for analysis of regulatory motif over-representation Nucleic Acids Res., July 13, 2007; 35(suppl_2): W245 - W252. [Abstract] [Full Text] [PDF]

				M. Seidel, N. Rozwadowska, K. Tomczak, and M. Kurpisz Myoblast preparation for transplantation into injured myocardium Eur. Heart J. Suppl., December 1, 2006; 8(suppl_H): H8 - H15. [Abstract] [Full Text] [PDF]

				T. Nedachi and M. Kanzaki Regulation of glucose transporters by insulin and extracellular glucose in C2C12 myotubes Am J Physiol Endocrinol Metab, October 1, 2006; 291(4): E817 - E828. [Abstract] [Full Text] [PDF]

				I.-H. Park and J. Chen Mammalian Target of Rapamycin (mTOR) Signaling Is Required for a Late-stage Fusion Process during Skeletal Myotube Maturation J. Biol. Chem., September 9, 2005; 280(36): 32009 - 32017. [Abstract] [Full Text] [PDF]

				T. Y. Kostrominova, D. E. Dow, R. G. Dennis, R. A. Miller, and J. A. Faulkner Comparison of gene expression of 2-mo denervated, 2-mo stimulated-denervated, and control rat skeletal muscles Physiol Genomics, July 14, 2005; 22(2): 227 - 243. [Abstract] [Full Text] [PDF]

				A. Blais, M. Tsikitis, D. Acosta-Alvear, R. Sharan, Y. Kluger, and B. D. Dynlacht An initial blueprint for myogenic differentiation Genes & Dev., March 1, 2005; 19(5): 553 - 569. [Abstract] [Full Text] [PDF]

				J. Paris, C. Virtanen, Z. Lu, and M. Takahashi Identification of MEF2-regulated genes during muscle differentiation Physiol Genomics, December 15, 2004; 20(1): 143 - 151. [Abstract] [Full Text] [PDF]

				S. C. Goetsch, T. J. Hawke, T. D. Gallardo, J. A. Richardson, and D. J. Garry Transcriptional profiling and regulation of the extracellular matrix during muscle regeneration Physiol Genomics, August 15, 2003; 14(3): 261 - 271. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Data Supplement All Versions of this Article: 10/2/103    most recent 00011.2002v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (18) Citing Articles via Google Scholar Google Scholar Articles by Moran, J. L. Articles by Miller, C. P. Search for Related Content PubMed PubMed Citation Articles by Moran, J. L. Articles by Miller, C. P.