A team of scientists led by Dr. Modesto Orozco at IRB Barcelona, based in the Barcelona Science Park, has developed an advanced computational technique to predict gene architecture through nucleosome position. The method combines experimental approaches with machine learning techniques and signal transmission theory. The study, published in the journal Nucleic Acids Research, is key for future research on how alterations in chromatin structure can influence the onset of diseases. 

DNA—the molecule that carries the genetic information of all living organisms—is packaged within cells in a complex manner that allows it to function efficiently. Nucleosomes facilitate DNA compaction and also play a crucial role in regulating gene expression and other biological processes.

The model developed by Dr. Modesto Orozco‘s team uses DNA sequence information and physical characteristics not only to reproduce experimental data but also to predict nucleosome locations more quickly and accurately. “The precision of our model is comparable with that of the most advanced experimental methods”, says Dr. Orozco, head of the Molecular Modelling and Bioinformatics lab at IRB Barcelona and full professor at the University of Barcelona.

Implications for gene regulation and biomedicine

The study demonstrates that nucleosomal architecture is greatly influenced by the DNA sequence and physical signals that are emitted by the ends of the genes. These signals determine the location of the first and last nucleosomes (+1 and -last) and also affect the position of the nucleosomes along the gene. “Our work suggests that nucleosome structure may impact gene expression in ways that are more complex than we thought”, adds Alba Sala, PhD student at IRB Barcelona and first author of the study.

Image / IRB Barcelona.

This approach is key for future research on how alterations in chromatin structure can influence the onset of diseases. By better understanding the organisation of DNA and nucleosomes, scientists can identify new therapeutic targets and develop more effective treatments.

» Reference article: Alba Sala, Mireia Labrador, Diana Buitrago, Pau De Jorge, Federica Battistini, Isabelle Brun Heath, Modesto Orozco, An integrated machine-learning model to predict nucleosome architecture, Nucleic Acids Research, Volume 52, Issue 17, 23 September 2024, Pages 10132–10143, DOI: 10.1093/nar/gkae689

» Link to the news: IRB Barcelona website [+]