Moscot framework: Reshaping single-cell genomics and analyzing the entire process of cell development

Recently, an interdisciplinary research team from the Technical University of Munich, the University of Helmholtz and the ETH Zurich released an important study, proposing an innovative framework called Moscot (optimal transmission of multiomic single-cells), which successfully The developmental trajectory of 1.7 million mouse embryonic cells at 20 time points was reconstructed. The study, published in the journal Nature, marks a major breakthrough in the field of single-cell genomics.

The design of the Moscot framework is inspired by the 18th century optimal transmission theory, which aims to efficiently move objects from one place to another. The researchers achieved the integration of multimodal data by converting biological mapping and alignment tasks into optimal transmission problems and using a series of consistent algorithms to solve these problems. Compared with previous methods, Moscot not only improves the scalability of computing, but also unifies its application in the fields of time and space, solving several key challenges currently faced in single-cell genomics.

Traditional methods often only provide limited cell snapshots and cannot fully understand the dynamic changes of cells during development, says Dominik Klein, the lead author of the study. Through Moscot, the research team was able to more accurately depict the developmental trajectory of mouse embryos and reveal the interactions of cells in different spaces and times. For example, in their study of pancreatic development in mice, they successfully portrayed the development process of hormone-producing cells and discovered NEUROD2, a key regulator in human-induced pluripotent stem cells. This finding provides a new perspective for understanding the underlying mechanisms of diabetes.

In addition, Moscot's open source features make it available to a wider scientific research community. The research team hopes to use this framework to promote in-depth research on disease mechanisms to achieve more targeted treatment methods.