Nucleosome Positions: Predicting Gene Architecture

DNA, the molecule that carries the genetic blueprint for all living organisms, is organized within cells to enhance its functionality. Nucleosomes are crucial for compacting DNA and are instrumental in regulating gene expression and various biological functions.

A research team led by Dr. Modesto Orozco at IRB Barcelona has created a cutting-edge computational technique to forecast gene architecture based on nucleosome positioning. This method integrates experimental strategies with machine learning and principles from signal transmission theory. Their research findings have been published in the journal Nucleic Acids Research.

In recent years, scientists have used experimental approaches like MNase-seq to map nucleosome positions. In contrast, Dr. Orozco’s model utilizes DNA sequence information and physical attributes to not only replicate experimental data but also predict nucleosome locations more quickly and accurately.

"The accuracy of our model is on par with the most sophisticated experimental methods available," remarks Dr. Orozco, who leads the Molecular Modelling and Bioinformatics lab at IRB Barcelona and serves as a Full Professor at the University of Barcelona.

The study shows that nucleosomal architecture is significantly shaped by the DNA sequence and physical signals originating from the ends of genes. These signals influence the placement of both the first and last nucleosomes, as well as their arrangement along the gene.

"Our findings indicate that the structure of nucleosomes may influence gene expression in ways that are more nuanced than previously understood," states Alba Sala, a Ph.D. student and lead author of the study.

This innovative method is essential for future investigations into how alterations in chromatin structure can contribute to various diseases. By improving our understanding of DNA organization and nucleosome placement, researchers can discover new therapeutic targets and create more effective treatment options.