Decoding gene transcription
Huge advances have been made to genome mapping, but while this "blueprint" contains instructions that could help us understand biological processes that are responsible for functions in an organism, such as development of organs, progression of disease and other complex biological events such as aging, the information is encoded and difficult to interpret.
A bioinformatics team led by Professor Lyu Aiping, Dean of School of Chinese Medicine (SCM), Professor Zhang Ge, Director of Technology Development Division and Associate Director of Teaching and Research Division (CMTR), and Dr Zhu Hailong, Assistant Professor of CMTR, has developed the world’s first model framework and "LogicTRN" algorithm to accurately establish gene regulatory routes for better understanding of molecular mechanisms and analysis of genetic function. Their work was published in the prestigious academic journal Nature Communications.
Understanding interactions and relationships
Instructions contained in DNA are read and processed by cells in two steps. The first of these biochemical processes is transcription, the process of "copying down" DNA by proteins called transcription factors (TFs). Dr Zhu explains: “TFs can stimulate or repress the transcribing of related genes. By being able to switch genes on and off, TF ensure the right genes are expressed in the right cell at the right time and in the right amount in order to execute various functions."
Although the regulation of gene transcription is the most common form of gene control and understanding it is important for molecular biology and is of great interest in medicine, the correlation between TFs is so complex that the regulatory network is often unknown or not fully understood. To illustrate, Dr Zhu says: "TFs are themselves regulated by its upstream gene. A single outcome is only produced by a specific combination of TFs. The complicated and combinatorial nature of TF regulation explains why 2,000-3,000 TFs are enough to control the spatio-temporal expression of over 30,000 genes."
A new dawn for biometrics
"It was difficult in the past to develop a reliable relationship for gene regulation due to the lack of a theoretical model. Our Logic TRN combines TF regulatory logics and transcription kinetics into one model framework, offering a powerful analytical tool for unravelling key pathways," says Professor Lyu Aiping.
Decoding the gene regulatory route plays a crucial role in research on disease and drug discovery. Developments in treatment of targeted genes have been hindered by an incomplete understanding of the complicated correlation between TFs. Professor Zhang says, "Using computational modelling techniques and big data analytics, LogicTRN can decode underlying mechanisms of gene transcription, and thereby reveal new therapeutic targets of complicated diseases such as cancer."
LogicTRN successfully analysed datasets representing the estrogen-induced breast cancer and human-induced pluripotent stem cell (hiPSC)-derived cardiomyocyte (CM) development. The derived networks are consistent with existing knowledge and previous experiments.
Dr Zhu adds, "LogicTRN" is an open model framework which can be potentially extended to integrate the influences of various processes such as gene mutation, TF-DNA binding, miRNA regulation, protein translation, and protein-protein-interaction."
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