Predicting gene expression level by the transcription factor binding signals in human embryonic stem cells

- The distributions of 57 kinds of transcription factors binding signals in the genome are computed.
- Transcription factors synthetic indexes (TFSIs) are defined by their association strength.
- A statistics model for predicting gene expression level is established by 57 TFSIs.
- The Up-regulated and Down-regulated genes of 57 kinds of transcription factors are predicted.
- 8 TFSIs which are vital for predicting gene expression are selected out.

The transcription factor (TF) binding signals play important role in the control of gene expression. In this study, to elucidate the relationship between the transcription factor binding signals and gene expression, we firstly analyze the distributions of 57 kinds of TFs' binding signals in human H1 embryonic stem cells. Their distributions in highly and lowly expressed genes are further compared. On this basis, a statistic model of predicting gene expression level is constructed by using 57 kinds of transcription factor synthetic indexes (TFSIs). Then, the TF's Down-regulated and Up-regulated genes are predicted and the statistics significance is estimated by one-sided Kolmogorov-Smirnov test. Based on the stepwise regression analysis, the “optimal” TFSIs are selected out, and the better results for predicting the expression level of genes with high CpG content promoters (HCPs) and low CpG content promoters (LCPs) are obtained.