Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1000607
Title: Dissecting early differentially expressed genes in a mixture of differentiating embryonic stem cells
Authors: Hong F.
Fang F.
He X.
Cao X.
Chipperfield H.
Xie D.
Wong W.H.
Ng H.H. 
Zhong S.
Keywords: animal cell
article
cell differentiation
cell separation
cell type
controlled study
embryo
embryonic stem cell
gene expression
mouse
nonhuman
pluripotent stem cell
animal
biological model
biology
cytology
gene expression profiling
gene expression regulation
gene regulatory network
genetics
methodology
physiology
Poisson distribution
Murinae
Animals
Cell Differentiation
Computational Biology
Embryonic Stem Cells
Gene Expression Profiling
Gene Expression Regulation, Developmental
Gene Regulatory Networks
Mice
Models, Genetic
Poisson Distribution
Issue Date: 2009
Citation: Hong F., Fang F., He X., Cao X., Chipperfield H., Xie D., Wong W.H., Ng H.H., Zhong S. (2009). Dissecting early differentially expressed genes in a mixture of differentiating embryonic stem cells. PLoS Computational Biology 5 (12) : e1000607. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1000607
Rights: Attribution 4.0 International
Abstract: The differentiation of embryonic stem cells is initiated by a gradual loss of pluripotency-associated transcripts and induction of differentiation genes. Accordingly, the detection of differentially expressed genes at the early stages of differentiation could assist the identification of the causal genes that either promote or inhibit differentiation. The previous methods of identifying differentially expressed genes by comparing different cell types would inevitably include a large portion of genes that respond to, rather than regulate, the differentiation process. We demonstrate through the use of biological replicates and a novel statistical approach that the gene expression data obtained without prior separation of cell types are informative for detecting differentially expressed genes at the early stages of differentiation. Applying the proposed method to analyze the differentiation of murine embryonic stem cells, we identified and then experimentally verified Smarcad1 as a novel regulator of pluripotency and self-renewal. We formalized this statistical approach as a statistical test that is generally applicable to analyze other differentiation processes. © 2009 Hong et al.
Source Title: PLoS Computational Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/161669
ISSN: 1553734X
DOI: 10.1371/journal.pcbi.1000607
Rights: Attribution 4.0 International
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