Gene expression changes during mouse skeletal myoblast ...

Physiol Genomics 10: 103–111, 2002. First published June 25, 2002; 10.1152/physiolgenomics.00011.2002.

Gene expression changes during mouse skeletal myoblast differentiation revealed by transcriptional profiling JENNIFER L. MORAN, YIZHENG LI, ANDREW A. HILL, WILLIAM M. MOUNTS, AND CHRISTOPHER P. MILLER Department of Genomics, Wyeth Research, Cambridge, Massachusetts 02140 Received 5 February 2002; accepted in final form 19 June 2002

Moran, Jennifer L., Yizheng Li, Andrew A. Hill, William M. Mounts, and Christopher P. Miller. Gene expression changes during mouse skeletal myoblast differentiation revealed by transcriptional profiling. Physiol Genomics 10: 103–111, 2002. First published June 25, 2002; 10.1152/ physiolgenomics.00011.2002.—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

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 musclespecific 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

SKELETAL MUSCLE DIFFERENTIATION

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: [email protected]).

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

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 ␮g/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]

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TRANSCRIPTIONAL PROFILING OF MYOBLAST DIFFERENTIATION

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 Physiol Genomics • VOL

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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

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). Enrichment of functional categories within expression clusters. To identify biological processes coordinately regulated during muscle proliferation and differentiation, we classified all known differentially expressed genes using a hierarchical classification scheme and determined whether expression clusters were enriched in transcripts with similar biological functions. Genes with a variety of cellular functions are enriched in individual clusters (Table 1). Statistically significant functional category enrichment is observed in 10 of 16 expression clusters with fold enrichments ranging from 3.0 to 25.6 and P values ranging from 1.9 ⫻ 10⫺4 to less than 7 ⫻ 10⫺14. Muscle contraction and cytoskeletal organization genes. Clusters 1,1 and 1,2 are enriched in genes involved in muscle contraction (Tables 1 and 2). Transcripts in cluster 1,2 increase by day 1 of differentiation, whereas transcripts in cluster 1,1 increase by day 4 (Fig. 2). Of 28 genes classified in the general muscular contraction category, 19 of these were found in

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. www.physiolgenomics.org

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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 ⫻ 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).

cluster 1,1, and six were present in cluster 1,2. Genes with roles in skeletal muscle contraction were assigned to a specific subcategory of muscular contraction. Cluster 1,1 is enriched in these genes 7.3-fold compared

with all other clusters. Transcripts encoding components of the muscle contractile apparatus (myosin light and heavy chains, troponins, actinins, and actins) constitute the majority of muscle contraction genes in clusters 1,1 and 1,2 (Table 2). Genes whose protein products regulate neurotransmitter activity and creatine synthesis, in addition to several genes encoding Ca2⫹-transporting ATPases and voltage-gated calcium channels, are important for muscle contraction and cluster with the muscle structural proteins. Cytoskeletal organization genes are enriched in two clusters, clusters 1,1 and 1,4. In cluster 1,1, the majority of these genes are assigned muscle contraction functions, whereas enriched genes in cluster 1,4 primarily function in actin cytoskeletal rearrangements. 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 ␤-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, matrixassociated 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,

Table 1. Functional category enrichment within expression clusters Cluster

Functional Category

Genes in Category per Cluster/ Total in Category

Fold Enrichment

P Value

1,1 (72)

muscular contraction muscular contraction skeletal muscle contraction cytoskeletal organization amino acid transport muscular contraction extracellular matrix function cell adhesion inflammation cell adhesion carbohydrate metabolism immunity cell adhesion-mediated signaling cytoskeletal organization mitochondrial transport cell cycle control and mitosis chromosome segregation B cell and antibody-mediated signaling mRNA transcription chromatin modification DNA replication

19/28 8/14 11/12 14/32 2/2 5/14 9/22 6/21 6/11 7/21 2/5 2/5 2/3 6/32 4/9 14/52 5/11 2/2 9/38 6/16 7/24

5.4 4.6 7.3 3.5 8.0 5.4 6.2 4.3 6.8 4.2 25.6 25.6 15.4 4.3 8.8 3.0 5.1 10.7 3.2 5.0 3.9

7.6 ⫻ 10⫺14 5.6 ⫻ 10⫺6 5.9 ⫻ 10⫺12 7.2 ⫻ 10⫺7 ⬍7.6 ⫻ 10⫺14 1.1 ⫻ 10⫺4 1.7 ⫻ 10⫺7 1.8 ⫻ 10⫺4 3.4 ⫻ 10⫺6 8.3 ⫻ 10⫺5 2.6 ⫻ 10⫺5 2.6 ⫻ 10⫺5 7.3 ⫻ 10⫺5 2.0 ⫻ 10⫺4 2.5 ⫻ 10⫺5 8.3 ⫻ 10⫺6 1.1 ⫻ 10⫺4 6.3 ⫻ 10⫺14 1.9 ⫻ 10⫺4 5.5 ⫻ 10⫺5 1.5 ⫻ 10⫺4

1,2 (38) 1,3 (38) 1,4 (46) 2,1 (9) 2,4 (25) 3,1 (29) 3,2 (51) 3,3 (54) 4,3 (43)

Number of distinct genes in each cluster is denoted in parentheses. The fold enrichment is the ratio of (the percentage of genes of a particular category appearing in a given cluster) to (the percentage of genes of a particular category among all clustered genes). Total number of functional classifications is 576. Only P values for statistically significant gene categories are listed, since the probability of obtaining a fold enrichment by chance for 167 categories tested is less than 0.05 for categories with P ⬍ 2.0 ⫻ 10 ⫺ 4. Physiol Genomics • VOL

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Table 2. Genes in enriched functional categories Accession

Gene

Table 2.—Continued

Description

Accession

Cluster 1,1 Muscular contraction AA221393 Atp2a2 ATPase, Ca2⫹ transporting, slow twitch 2 U91483 Casq2 calsequestrin 2 M30514 Chrng acetylcholine receptor gamma M74149 Ckb creatine kinase, brain W13236 Ckmm creatine kinase, muscle W85566 Mylpf2* myosin light chain 2 M19436 Myla* myosin light chain, alkali, cardiac atria L45799 Tnnt2* troponin T2, cardiac Skeletal muscle contraction W34429 Actn2* actinin alpha 2 AA098356 Actn3* actinin alpha 3 X67140 Atp2a1 ATPase, Ca2⫹ transporting, fast twitch 1 AA061886 Cacng1 calcium channel, voltage-dependent, gamma 1 M74753 Myh3* myosin heavy chain 3, embryonic skeletal muscle M12289 Myh8* myosin heavy chain 8, perinatal skeletal muscle M29793 Tncc* troponin C, cardiac/slow skeletal W29418 Tncs* troponin C, fast skeletal J04992 Tnni2* troponin I, skeletal, fast 2 W08218 Tnnt1* troponin T1, skeletal, slow L49470 Tnnt3* troponin T3, skeletal, fast Cytoskeletal organization* X69063 Ank1 ankyrin 1, erythroid W08774 Csrp3 cysteine-rich protein 3 Amino acid transport U25708 Mdu1 4F2 cell-surface antigen heavy chain (4f2hc) D83262 Slc1a6 solute carrier family 1, member 6 (Eeat4) Cluster 1,2 Muscular contraction M12347 Acta1† W58987 Actc1 X03986 Chrna1 M14537 Chrnb1 W75072 Ckb W29468 Mylpf

actin, alpha 1, skeletal muscle actin, alpha, cardiac acetylcholine receptor alpha acetylcholine receptor beta creatine kinase, brain myosin light chain 2

Col3a1 Col4a1 Col4a2 Col5a2 Nid2 Tgfbi Vcam1

Gro1 oncogene interleukin 18 serum amyloid A3 Cluster 2,1

Carbohydrate D32250 AA600607 Immunity AA097051 M18466

metabolism Akr1b1 aldo-keto reductase family 1, member B1 Gyg1 glycogenin Ly6 Ly6c

lymphocyte antigen 6 complex, locus E lymphocyte antigen 6 complex, locus C Cluster 2,4

Cell adhesion-mediated signaling AA038511 Flna filamin A L22482 Tgfb1i1 transforming growth factor beta 1 induced 1 Cytoskeletal organization X54511 Capg capping protein (actin filament), gelsolinlike Z19543 Cnn2 calponin 2 W08453 Dsn destrin AA038511 Flna filamin A L41154 Tagln transgelin L22482 Tgfb1i1 transforming growth factor beta 1 induced 1 Cluster 3,1 Mitochondrial transport C78107 Slc25a5 solute carrier family 25, member A5 (Ant2) AA209596 Timm13a translocase, inner mitochondrial membrane 13a AA219964 Timm23 translocase, inner mitochondrial membrane 23 AA050662 Timm9 translocase, inner mitochondrial membrane 9 Cell cycle control and mitosis‡ X64713 Ccnb1-rs1 cyclin B1, related sequence 1 U15562 Cdc25c cell division cycle 25 homolog C U58633 Cdc2a cell division cycle 2 homolog AA289122 Cks2 cyclin-dependent kinase regulatory subunit 2 D73368 Erh enhancer of rudimentary homolog X62154 Mcmd mini chromosome maintenance deficient AA689977 Mcmd6 mini chromosome maintenance deficient 6 AA271109 Ppp1r7 protein phosphatase 1, regulatory subunit 7 AA592163 Prc1 protein regulator of cytokinesis 1 Chromosome segregation‡ AA259399 Bub3 budding uninhibited by benzimidazoles 3 A163900 Ran RAN, member RAS oncogene family U08110 Rangap1 RAN GTPase activating protein 1 AA241064 Smc4l1 structural maintenance of chromosome 4-like 1 C77864 Tubb2 tubulin, beta, 2

procollagen, type VI, alpha 1 procollagen, type VI, alpha 2 procollagen, type VIII, alpha 1 dystroglycan 1 fibrillin 1 matrillin 2 matrix metalloproteinase 2 osteoglycin syndecan 2 CD 81 antigen procollagen, type VI, alpha procollagen, type VI, alpha 2 procollagen, type VIII, alpha 1 dystroglycan 1 syndecan 2

Cluster 3,3 B cell and antibody-mediated signaling X53825 Cd24a CD24a antigen W07963 Fus Fus

Cluster 1,4 Cell adhesion AA259937 J04694 J04695 L02918 AA063985 L19932 X67783

Inflammation J04596 Gro1 D49949 Il18 X03479 Saa3

Description

Cluster 3,2

Cluster 1,3 ECM function X66405 Col6a1 X65582 Col6a2 X66976 Col8a1 U43512 Dag1 L29454 Fbn1 U69262 Matn2 M84324 Mmp2 D31951 Ogn U00674 Sdc2 Cell adhesion W98255 Cd81 X66405 Col6a1 X65582 Col6a2 X66976 Col8a1 U43512 Dag1 U00674 Sdc2

Gene

procollagen, type III, alpha 1 procollagen, type IV, alpha 1 procollagen, type IV, alpha 2 procollagen, type V, alpha 2 nidogen 2 transforming growth factor, beta induced vascular cell adhesion molecule 1

Cluster 4,3 mRNA transcription§ AA616337 Hnrpab M69293 W30290

Idb2 Lmo4

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heterogeneous nuclear ribonucleoprotein A/B inhibitor of DNA binding 2 LIM only 4 Continued



Table 2.—Continued Accession

Gene

Description

Chromatin modification§ AA415606 Actl6 actin-like 6 AF012709 Cenpa centromere autoantigen A U80780 Hdac1 histone deacetylase 1 AA200970 Hmg4 high mobility group 4 AF034610 Nasp nuclear autoantigenic sperm protein D12513 Top2a topoisomerase (DNA) II alpha DNA replication AA690055 Ask activator of S phase kinase L26320 Fen1 flap structure specific endonuclease 1 D26089 Mcmd4 mini chromosome maintenance deficient 4 D13546 Pola2 DNA polymerase alpha 2 D13544 Prim1 DNA primase, p49 subunit AA259483 Tmk thymidylate kinase D12513 Top2a topoisomerase (DNA) II alpha U27267 Scyb5 small inducible cytokine B5 U19482 Scya9 small inducible cytokine A9 X67783 Vcam1 vascular cell adhesion molecule * These genes are classified both as muscular contraction or skeletal muscle contraction and cytoskeletal organization. † Acta1 is classified under the skeletal muscle contraction category. ‡ Chromosome segregation is a subcategory of cell cycle control and mitosis; hence, all chromosome segregation genes are also classified under the cell cycle control and mitosis category. § Chromatin modification is a subcategory of mRNA transcription; hence, all chromatin modification genes are also classified under the mRNA transcription category.

Ncam, and M-cadherin (Cdh15)] are expressed at highest levels in terminally differentiated myocytes (Fig. 3). Immune function genes. Unexpectedly, several clusters are enriched in genes involved in general immune functions, B cell and antibody-mediated signaling, and inflammation (Tables 1 and 2). Of eleven genes classified overall as having inflammatory functions, three are found in cluster 2,4, and six are found in cluster 1,4, with the latter enrichment being statistically significant (Table 2). Both pro-and anti-inflammatory genes were differentially regulated and include several chemokines [Scya5 (cluster 1,1), Scya9 and Scyb5 (both cluster 1,4), and Scya2 and Scya7 (both cluster 2,4)], interleukin-18 (Il18; cluster 1,4), IL-1 receptor antagonist (Il1rn; cluster 2,3), and IL-10 receptor beta (Il10rb, cluster 2,4) (Fig. 2). 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 XAG 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 Physiol Genomics • VOL

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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, p21Cip1 (Cdkn1a; cluster 1,1) and p57Kip2 (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). mRNA transcription genes are over-represented in cluster 4,3, and six of these nine genes are classified in the statistically enriched subcategory, chromatin modification (Tables 1 and 2). In addition to genes functioning in mRNA transcription and chromatin modification, the related cluster, cluster 3,3, also contains genes with roles in mRNA splicing (Supplemental Data). 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 TGF␤ gene family of secreted signaling molecules, activin (Inhbb) and TGF␤3 (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. 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.


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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. DISCUSSION

Our high-density oligonucleotide microarray analyses described here have identified several hundred genes whose mRNA expression is regulated during the myogenic program in the well-characterized mouse C2C12 myoblast cell line. Most regulated genes exhibit marked expression changes during the transitions from proliferating to early differentiating cells and from early to late differentiating cells, consistent with the mitotic to postmitotic cellular transition and the dramatic change in cellular phenotype accompanying myogenic differentiation, respectively. Clustering and functional classification of differentially regulated genes and subsequent statistical analysis of the distribution of functional categories identi-

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). Physiol Genomics • VOL

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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).

fied 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, cellcell 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. www.physiolgenomics.org


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), p21Cip1 (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 differenPhysiol Genomics • VOL

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tiating 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 immediateearly 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 www.physiolgenomics.org

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