Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA.
PLoS Comput Biol. 2009 Dec;5(12):e1000607. doi: 10.1371/journal.pcbi.1000607. Epub 2009 Dec 18.
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.
胚胎干细胞的分化是由多能性相关转录本的逐渐丧失和分化基因的诱导启动的。因此,在分化的早期检测差异表达基因可以帮助鉴定促进或抑制分化的因果基因。以前通过比较不同细胞类型来鉴定差异表达基因的方法不可避免地会包括很大一部分对分化过程有反应而不是调节的基因。我们通过使用生物重复和一种新的统计方法证明,在没有预先分离细胞类型的情况下获得的基因表达数据对于检测分化早期的差异表达基因是有信息的。我们应用所提出的方法来分析小鼠胚胎干细胞的分化,鉴定并随后通过实验验证 Smarcad1 是多能性和自我更新的一个新的调控因子。我们将这种统计方法形式化为一种统计检验,该检验通常可应用于分析其他分化过程。