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Dissecting early differentially expressed genes in a mixture of differentiating embryonic stem cells.

Authors :
Feng Hong
Fang Fang
Xuming He
Xiaoyi Cao
Hiram Chipperfield
Dan Xie
Wing H Wong
Huck H Ng
Sheng Zhong
Source :
PLoS Computational Biology, Vol 5, Iss 12, p e1000607 (2009)
Publication Year :
2009
Publisher :
Public Library of Science (PLoS), 2009.

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.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
1553734X and 15537358
Volume :
5
Issue :
12
Database :
Directory of Open Access Journals
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.ff17833f002a4c7196cf72172ef51e7d
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pcbi.1000607