Get ready for the future of gene expression technology

TLDR:

• Research led by Kyoto University has developed a method to semi-automatically estimate gene regulatory networks in multicellular organisms.
• The RENGE computational model, applied to time-series gene expression data, shows promising results in identifying key factors for cell differentiation.

Gene Expression Technology Set to Semi-Automation

The Human Genome Project provided the first sequence of the human genome, unraveling the blueprint of human biology. However, understanding gene regulatory networks remains a complex system that requires more exploration. Kyoto University researchers have introduced a method using the RENGE computational model to estimate gene regulatory networks semi-automatically in multicellular organisms by measuring time-series gene expression data.

The study, published in the journal Communications Biology, highlights the accuracy of the RENGE method in distinguishing direct and indirect gene regulations. By analyzing expression changes through gene knockouts and utilizing the latest single-cell CRISPR technology, researchers were able to infer gene regulatory networks with high precision.

The RENGE method was found to outperform existing methods in simulation data and human iPS cell measurements, identifying a network of 103 genes related to pluripotency. This approach not only provides valuable insights into cell differentiation but also signifies the potential for new technologies in creating manipulated cells with specific functions.

The versatile nature of the RENGE method allows for estimating regulatory networks beyond iPS cells, opening up new avenues for research in various life systems. This breakthrough may pave the way for enhanced understanding of gene regulation dynamics and accelerate advancements in biotechnology and medical research.