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Expression profiling and identification of novel genes involved in myogenic differentiation¹

KINGA K. TOMCZAK^*,, VOICHITA D. MARINESCU^,, MARCO F. RAMONI^,, DESPINA SANOUDOU^*,, FEDERICA MONTANARO^*,, MEI HAN^*,, LOUIS M. KUNKEL^*,, ISAAC S. KOHANE^, and ALAN H. BEGGS^*,,2

^* Genomics Program and Division of Genetics, Children’s Hospital,
Children’s Hospital Informatics Program; and
Harvard Medical School, Boston, Massachusetts, USA

²Correspondence: Genetics Division, Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115, USA. Email: beggs{at}enders.tch.harvard.edu

SPECIFIC AIMS

The primary aim of this study was to create a genome-wide catalog of genes whose expression levels change over the time course of skeletal muscle differentiation in vitro and to classify them according to several main functional categories.

PRINCIPAL FINDINGS

Affymetrix MG_U74Av2 and Cv2 GeneChips were used to analyze gene expression over a 12 day time course in C2C12 myoblasts induced to differentiate in vitro. Triplicate cultures were studied during cell proliferation (days -2 and -1), at cell cycle withdrawal (day 0) and during myogenic fusion and maturation of multinucleated myotubes (days 2, 4, 6, 8, 10).

1. Patterns of gene expression in proliferating and differentiating myoblasts
CAGED 1.1, a new computational tool specifically designed for hierarchical cluster analysis of temporal microarray experiments using a Baysian approach, was used to classify 2,895 probe sets, that met requirements for reproducible signal detection and fold change, into 22 clusters with distinct expression patterns. Broadly, we have distinguished four groups of clusters. Groups I through III contained transcripts that were significantly up or down-regulated over the time course (Fig. 1 ), while group IV consisted of transcripts only minimally changed in expression. A detailed list of genes with their annotations in all 22 clusters is available as supplementary data Tables 1–4 (http://www.chb-genomics.org/beggslab).

View larger version (45K): [in this window] [in a new window]   Figure 1. Classification of 1,395 transcripts into 17 temporally related clusters by CAGED 1.1. Natural log transformed average expression patterns for probe sets in each cluster are grouped and plotted at left. Gene ontology functional classifications for transcripts in each group are shown at right.

2. Clusters of genes down-regulated in differentiating cells (group I)
Group I comprises three clusters with a total of 467 probe sets. Transcripts in these clusters had high expression values at day -2 and day -1 when the cells were rapidly dividing and decreased expression by -1.45 to -335.2-fold (average=–22.7) over the 12-day time course. Genes in these clusters are mainly involved in cell-cycle regulation (41), cell signaling (25), ion transport (24) as well as nucleic acid and protein metabolism (Fig. 1) .

3. Clusters of genes with the highest expression values at cell cycle withdrawal and the switch toward fusion (group II).
This group contains five clusters of genes for which the expression levels peaked on day 0 followed by a temporary or permanent decrease on day 2 (clusters 4–8) (Fig. 1) . These clusters contain a total of 313 probe sets among which 266 represent a fold change between day 0 and day -2 greater than 2. Twenty-three percent (62) represent un-annotated transcripts.

4. Clusters of genes up-regulated at differentiation (group III)
Group III includes 9 clusters of 615 genes whose expression was very low or undetectable at the beginning of the time course and progressively increased after day 0 or 2 (clusters 9–17). Fold changes by day 10 ranged from +1.47 to +687.6 (average=+19.3). Between days 2 and 10, myoblasts ceased proliferating and the majority of them fused into postmitotic myotubes and began sarcomere assembly. Not surprisingly, clusters in group III contain many genes involved in muscle contraction (29) and muscle development (22), as well as genes involved in metabolism, cell signaling (43), ion transport (33) and transcription (30). Five of the nine clusters (numbered 9–13), contain 255 of the most dramatically up-regulated genes at differentiation, 47% of which are known to be expressed in muscle. Included in the group III clusters are 167 probe sets for uncharacterized or unannotated genes.

5. Transcriptional changes in C2C12 myoblasts detected by microarrays correlate well with protein levels
Several known and novel genes that exhibited changing expression patterns in differentiated cells were chosen for validation using different methods. In each case examined, quantitative rtPCR confirmed the GeneChip findings, although the magnitude of the fold changes varied somewhat. Western blot and indirect immunofluorescence studies confirmed the transcription data for several muscle membrane and sarcomeric proteins (Fig. 2 ). Interestingly, Aquaporin-1 (Aqp1), a down-regulated transcript from cluster 1, exhibited an inverse correlation between transcript and protein levels of its mature 45 kDa glycosylated form.

View larger version (62K): [in this window] [in a new window]   Figure 2. Correlations between GeneChip transcriptional data (A) and protein levels and localization by Western blot analysis (B) and indirect immunofluorescence (C–E). B) Time points are indicated above Western blots and proteins are named at right. Aquaporin-1 exists as a 28 kD unglycosylated form and larger glycosylated forms. C) expression of caveolin-3 (green) is limited to plasma membranes of mature myotubes. D) The sarcomeric proteins -actinin-3 (green) and myosin heavy chain (red) are similarly induced and colocalize (eg., appear yellow) at this magnification. E) -dystroglycan (red) is also induced late in differentiation while aquaporin-1 (green) is present throughout in unfused cells. (C–E) Nuclei are stained with DAPI (blue).

6. Identification of candidates for novel genes
In this study, 927 ESTs and other unknown transcripts clustered together with known, often well characterized genes. 368 of these exhibit large changes in gene expression over the time course and were classified into groups I-III (clusters 1–17). Many of these putative novel genes have either some homology to known genes or conserved protein domains.

CONCLUSIONS AND SIGNIFICANCE

Early stages of myogenesis were recapitulated by differentiating C2C12 cells which progressed through a predictable pattern of myogenic events during the 12 day time course. Expression changes for several major transcription factors involved in myoblast differentiation were apparent only over the first few days while genes for many markers of late muscle differentiation were not turned on until later in the time course. The primary muscle regulatory factors (MRFs) Myf5 and Myod1, were scored "Present" throughout the entire time course. However, Myf5 expression (cluster 3) decreased gradually while Myod1 transcripts peaked on day 0 (cluster 5). In contrast, the secondary MRFs, myogenin (cluster 10) and Myf6 (cluster 15), were induced later in the time course.

At day -2, the cultures contained rapidly proliferating mononucleate myoblasts but by day 0, the cells were confluent and becoming quiescent. As expected, the cyclins Ccna2, Ccnb2, Ccnd1 were significantly down-regulated between day -1 and day 0 while Ccnd3 expression increased between days -1 and +2 and remained high throughout the rest of the time course. Furthermore, Ccnd3 is a member of cluster 14 together with two probe sets for the Retinoblastoma (Rb) gene. Active Rb family members and cyclin-dependent kinase inhibitors need to be up-regulated for permanent withdrawal of myoblasts from cell cycle. Conversely, the negative regulators of cell division, Cdkn1a (P21) and Cdkn1c (P57), are required for myogenic differentiation, and in our experiment, were induced between days -1 and 2.

The switch from a proliferative to a differentiative state in this time course occurred primarily between day -1 and day 2 and was associated with a transient peak of expression for a large class of transcripts clustered into Group II. Genes in these clusters include Vcam1, Itgb3, Itga5 and Vcl. Vcam1 is known to be involved in the process of cell fusion while Itga5 (fibronectin receptor ) is an integrin important for proper adhesion. Interestingly, several genes that belong to this group were not previously associated with a role in skeletal muscle fusion. A good candidate for a novel gene involved in this process is the prostaglandin E receptor 4 (Ptger4), which is up-regulated specifically on day 0 (fold change 2.1).

Between days 2 and 10, differentiating myotubes matured considerably, increasing in number and size as well as in complexity. Sarcomere assembly occurred throughout this period leading to development of a functional contractile apparatus as evidenced by significant numbers of spontaneously contracting myotubes between days 6 and 10. Many known muscle-specific genes were considerably up-regulated at the start of this phase, with transcription remaining at high levels throughout the remainder of the time course. Markers of late differentiation, such as genes coding for proteins involved in the assembly of the sarcomeric contractile apparatus including various isoforms of myosins, troponins, myomesins and many others, were scored "Absent" by MAS 5.0 early in the time course but "Present" after myogenic fusion began (i.e., day 2 and later). In contrast, a number of transcripts involved in excitation contraction coupling, including 14 transcripts with GO classification as calcium ion binding proteins (such as ATPase Atp2a2) were primarily scored "Present" from the beginning of the time course (i.e., at day -2) but their expression increased dramatically on day 0 and remained up-regulated for the remainder of the time course. Moreover, clusters in this group contain voltage-dependent calcium channels, acetylocholinesterase, ryanodine receptor 1 cholinergic receptors, and many other genes important for cellular excitability and contraction.

Of the 2,895 probe sets included in the CAGED analysis, 927 (32%) represent transcripts for uncharacterized genes. These were distributed among almost all clusters representing all four groups of expression kinetics. Multiple probe sets for unknown genes were classified together with known genes involved in every step of muscle differentiation. As shown in Fig. 3 (flow chart) a relational database that integrates outcome of CAGED cluster analysis with Affymetrix annotations including GenBank, LocusLink as well as protein databases annotations (SwissProt, Pfam, InterPro) can serve as a useful tool for identification of candidates for novel genes involved in myogenesis. Further characterization and more detailed studies of each will lead to a better understanding of muscle differentiation. Moreover, these data are available to serve as a basis for comparison with gene manipulation studies aimed at understanding human muscle diseases by over or under expressing normal and abnormal neuromuscular disease genes in vitro.

View larger version (35K): [in this window] [in a new window]   Figure 3. Schematic diagram illustrating the experimental design and analytical approach.

FOOTNOTES

¹ To read the full text of this article, go to http://www.fasebj.org/cgi/doi/1096/fj.03-0568fje;

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