Researchers at Kyushu University have revealed how spatial distance between specific regions of DNA is linked to bursts of gene activity. Using advanced cell imaging techniques and computer modeling, the researchers showed that the folding and movement of DNA, as well as the accumulation of certain proteins, changes depending on whether a gene is active or inactive.

The study, published on December 6 in Science Advances, sheds insight into the complicated world of gene expression and could lead to new therapeutic techniques for diseases caused by improper regulation of gene expression.

Gene expression is a fundamental process that occurs within cells, with two main phases: transcription, where DNA is copied into RNA, and translation, where the RNA is used to make proteins. For each cell to carry out its specific functions in the body, or to respond to changing conditions, the right amount of a protein must be produced at the right time, meaning genes must be carefully switched on and off.

In a recent study published in Nature Communications, a team of researchers at the Carl R. Woese Institute for Genomic Biology reports a new, robust computational toolset to extract biological relationships from large transcriptomics datasets. These efforts will help scientists better investigate cellular processes.

Living organisms are governed by their genome—an instruction manual written in the language of DNA that dictates how an organism grows, survives, and reproduces. By regulating the abundance of different RNA transcripts, cells control their protein expression level, thereby shaping their functions and responses to the environment.

Transcriptomics is the study of gene expression through cataloging the presence and abundance levels of active RNA transcripts generated from the genome under different conditions. Through the lens of RNA, transcriptomics technologies allow scientists to study the complex interactions that enable life and cause disease, as well as assess the biological effects of therapeutics.

Cell–cell alignment and a background of stationary cells together shape the emergence of cellular clusters in a primary tumor.

In a cancer patient, tumor cells that circulate throughout the body in clusters pose a greater threat of metastasis than those that circulate individually. Those clusters are thought to come together while the cells are still within the primary tumor, but researchers still don’t understand the formation mechanism. Quirine Braat at Eindhoven University of Technology in the Netherlands and her colleagues have now used computer simulations to identify some of the factors at play [1].

The team used a computational lattice model of cells and tissues (the cellular Potts model) to examine a 2D layer of two types of cells—one motile (able to move) and one nonmotile. The tendency of the motile cells to migrate was represented in the model by an external force applied to each one. For a given cell, this force could align strongly or weakly with the forces acting on its neighboring cells.