Supat Thongjuea

I am a computational biologist who has a long-standing interest in gene regulation and the dynamics of gene regulatory networks during lineage commitment and differentiation of normal hematopoiesis. I obtained my PhD from the University of Bergen (2010-2014) with professor Boris Lenhard. My PhD focused on the analysis of transcription factor complexes and their associated chromatin interactions during erythropoiesis. 

I went to do post-doctoral training at MRC Weatherall Institute of Molecular Medicine, University of Oxford (2013-2015) with professors Claus Nerlov and Sten Eirik Jacobsen, followed by time as a research scientist at RIKEN Center for Life Science Technologies (2015-2017). Currently, I have a role as a junior principal investigator at the MRC WIMM Centre for computational biology.

My research focuses on a rare population of hematopoietic stem cells (HSCs) which is necessary and sufficient for replenishing all mature blood cells for a person’s lifetime. Studying the heterogeneity and molecular functions of HSCs is essential to understand how different pools of HSCs fine-tune the dynamic process of lineage commitment to maintaining the production of normal blood cells under steady-state and stress conditions.

I mainly develop and apply computational approaches for the analysis of large-scale single-cell transcriptomes produced by different types of single-cell technologies (i.e. 10x genomics) for studying the complexity of HSCs and progenitor cell subpopulations. The aims are to identify novel HSC and progenitor cell populations in normal hematopoiesis, to discover signature genes, regulatory networks and cellular pathways that drive their heterogeneity, and to determine how perturbations to the identified regulatory networks lead to blood developmental defects and cause leukemia. In addition, I also have an interest in studying the roles of non-coding transcripts (i.e. long-noncoding RNAs) that are involved in the cell fate decision particularly in the HSC lineage bias (i.e. platelet-bias).