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STEM CELL GENETICS AND GENOMICS

Selection of Neural Differentiation-Specific Genes by Comparing Profiles of Random Differentiation

^aDepartment of Computer Science and Engineering, Ewha Womans University, Seoul, Korea;
^bIlchun Molecular Medicine Institute and Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Korea;
^cMacrogen Inc., Seoul, Korea;
^dSeoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea

Key Words. Embryonic stem cells • Microarray • Neural differentiation • Random differentiation • Spearman's correlation

Correspondence: Woong-Yang Park, M.D., Ph.D., Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, 28 Yongondong, Chongnogu, Seoul 110-799, Korea. Telephone: +82-2-740-8241; Fax: +82-2-744-4534; e-mail: wypark{at}snu.ac.kr

Received July 17, 2005; accepted for publication April 10, 2006.
First published online in STEM CELLS EXPRESS   April 20, 2006.



Differentiation of embryonic stem cells (ESCs) into neurons requires a high level of transcriptional regulation. To further understand the transcriptional regulation of neural differentiation of ESCs, we used oligonucleotide microarray to examine the gene expressions of the guided differentiation (GD) model for dopaminergic (DA) neurons from mouse ESCs. We also determined the gene expression profiles of the random differentiation (RD) model of mouse ESCs into embryoid bodies. From K-means clustering analysis using the expression patterns of the two models, most of the genes (1,282 of 1,884 genes [68.0%]) overlapped in their expression patterns. Six hundred twenty-two differentially expressed genes (DEGs) from the GD model by random variance F-test were classified by their critical molecular functions in neurogenesis and DNA replication (Gene Ontology analysis). However, 400 genes among GD-DEGs (64.3%) showed a high correlation with RD in Spearman's correlation analysis (Spearman's coefficient p_s .6). The genes showing marginal correlation (–.4 < p_s < .6) were present in the early stages of differentiation of both GD and RD, which were non-specific to brain development. Finally, we distinguished 66 GD-specific genes based on p_s –.4, the molecular functions of which were related mainly to vesicle formation, neurogenesis, and transcription factors. From among these GD-specific genes, we confirmed the expression of Serpini1 and Rab33a in P19 differentiation models and adult brains. From these results, we identified the specific genes required for neural differentiation by comparing gene expressions of GD with RD; these would potentially be the highly specific candidate genes necessary for differentiation of DA neurons.

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