Laboratory for Cellular Function Conversion Technology

Current Research

 

DNA methylation is a fundamental epigenetic modification to regulate mammalian gene expression, where each type of cell creates specific methylation profile during its differentiation. Little is known about how cell-type-specific DNA methylation profiles are developed. We recently demonstrated that RUNX1 induces DNA demethylation by recruiting DNA demethylation machinery to its binding sites, which likely contributes to hematopoietic development. In addition, we analyzed omics data including DNA methylation profiles during hepatocyte differentiation and found GATA6 as a key transcription factor (TF) for its binding motif dependent chromatin activation and DNA demethylation in definitive endoderm differentiation. These studies indicates that certain TFs play a role of not only transcriptional regulation of the downstream genes, but also regulation of the binding site-specific DNA methylation status. Therefore, we developed a screening system to identify TFs that promote binding site-directed DNA methylation changes, and 9 out of 15 master TFs for cellular differentiation are identified as TFs with DNA-demethylation-promoting activity. Furthermore, we developed a bioinformatics pipeline to predict TFs with DNA-demethylation-promoting activity and identified approximately 30 TFs with the activity.

 

 In parallel with above research, we are analyzing mechanism of disease onset induced by abnormality of DNA methylation regulatory factors. We generated RUNX1 mutation without DNA demethylation ability to understand the role of RUNX1-mediated DNA demethylation in hematopoiesis. Further, we are analyzing abnormality of DNA methylation induced by RUNX1 mutations found in myelodysplastic syndromes. Furthermore, we are analyzing knockout effect of Ten-Eleven Translocation-2 (TET2), known as a DNA demethylation factor, in hematopoietic differentiation.

 

We are also exploring detailed molecular mechanism of epithelial-mesenchymal transition (EMT) and its reverse transition (MET) by utilizing multiple omics data, where the knowledge will also be applied to understand disease such as cancer. Further, we started to analyze mechanism of germ cell differentiation.