Consensus Comparative Analysis of Human Embryonic Stem Cell-Derived Cardiomyocytes

作者: Shaohong Zhang , Ellen Poon , Dongqing Xie , Kenneth R. Boheler , Ronald A. Li

DOI: 10.1371/JOURNAL.PONE.0125442

关键词: BiologyMicroarrayGene expression profilingGeneGene expressionCellular differentiationGeneticsDNA microarrayMicroarray analysis techniquesRegulation of gene expression

摘要: Global transcriptional analyses have been performed with human embryonic stem cells (hESC) derived cardiomyocytes (CMs) to identify molecules and pathways important for CM differentiation, but variations in culture profiling conditions led greatly divergent results among different studies. Consensus investigation genes gene sets enriched multiple studies is revealing differential expression intrinsic differentiation independent of the above variables, reliable methods conducting such comparison are lacking. We examined between hESC hESC-CMs from microarray For single analysis, we identified that were expressed at increased levels seven datasets which not previously highlighted. set developed a new algorithm, consensus comparative analysis (CSSCMP), capable evaluating enrichment heterogeneous data sources. Based on both theoretical experimental validation, CSSCMP more efficient less susceptible than traditional methods. applied hESC-CM revealed novel (e.g., glucocorticoid stimulus), also might mediate this response. Our provide molecular information differentiation. Data Matlab codes can be downloaded S1 Data.

参考文章(31)
Xiu Qin Xu, Set Yen Soo, William Sun, Robert Zweigerdt, Global expression profile of highly enriched cardiomyocytes derived from human embryonic stem cells. Stem Cells. ,vol. 27, pp. 2163- 2174 ,(2009) , 10.1002/STEM.166
B. Zhang, S. Kirov, J. Snoddy, WebGestalt: an integrated system for exploring gene sets in various biological contexts Nucleic Acids Research. ,vol. 33, pp. 741- 748 ,(2005) , 10.1093/NAR/GKI475
Jennifer C. Moore, Jidong Fu, Yau-Chi Chan, Dawei Lin, Ha Tran, Hung-Fat Tse, Ronald A. Li, Distinct cardiogenic preferences of two human embryonic stem cell (hESC) lines are imprinted in their proteomes in the pluripotent state. Biochemical and Biophysical Research Communications. ,vol. 372, pp. 553- 558 ,(2008) , 10.1016/J.BBRC.2008.05.076
Ellen Poon, Bin Yan, Shaohong Zhang, Stephanie Rushing, Wendy Keung, Lihuan Ren, Deborah K. Lieu, Lin Geng, Chi-Wing Kong, Jiaxian Wang, Hau San Wong, Kenneth R. Boheler, Ronald A. Li, Transcriptome-Guided Functional Analyses Reveal Novel Biological Properties and Regulatory Hierarchy of Human Embryonic Stem Cell-Derived Ventricular Cardiomyocytes Crucial for Maturation PLoS ONE. ,vol. 8, pp. e77784- ,(2013) , 10.1371/JOURNAL.PONE.0077784
Shaohong Zhang, Hau-San Wong, Ying Shen, Dongqing Xie, A New Unsupervised Feature Ranking Method for Gene Expression Data Based on Consensus Affinity IEEE/ACM Transactions on Computational Biology and Bioinformatics. ,vol. 9, pp. 1257- 1263 ,(2012) , 10.1109/TCBB.2012.34
Jane Synnergren, Karolina Åkesson, Kerstin Dahlenborg, Hilmar Vidarsson, Caroline Améen, Daniella Steel, Anders Lindahl, Björn Olsson, Peter Sartipy, Molecular signature of cardiomyocyte clusters derived from human embryonic stem cells. Stem Cells. ,vol. 26, pp. 1831- 1840 ,(2008) , 10.1634/STEMCELLS.2007-1033
Abdelaziz Beqqali, Jantine Kloots, Dorien Ward-van Oostwaard, Christine Mummery, Robert Passier, Genome-wide transcriptional profiling of human embryonic stem cells differentiating to cardiomyocytes. Stem Cells. ,vol. 24, pp. 1956- 1967 ,(2006) , 10.1634/STEMCELLS.2006-0054
J.-H. Hung, T.-H. Yang, Z. Hu, Z. Weng, C. DeLisi, Gene set enrichment analysis: performance evaluation and usage guidelines Briefings in Bioinformatics. ,vol. 13, pp. 281- 291 ,(2012) , 10.1093/BIB/BBR049
Heinrich Sauer, Gohar Rahimi, Jürgen Hescheler, Maria Wartenberg, Role of reactive oxygen species and phosphatidylinositol 3-kinase in cardiomyocyte differentiation of embryonic stem cells. FEBS Letters. ,vol. 476, pp. 218- 223 ,(2000) , 10.1016/S0014-5793(00)01747-6
William M. Rand, Objective Criteria for the Evaluation of Clustering Methods Journal of the American Statistical Association. ,vol. 66, pp. 846- 850 ,(1971) , 10.1080/01621459.1971.10482356