Advanced model predicts gene architecture via nucleosome position

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

A team of scientists led by Dr Modesto Orozco from IRB Barcelona has developed an advanced computational technique to predict gene architecture through the position of nucleosomes. The method combines experimental approaches with machine learning techniques and signal transmission theory. The study was published in the journal Nucleic acid research.

A predictive model that rivals experimental methods

In recent years, scientists have used experimental techniques such as MNase-seq to map nucleosomes. The model developed by Dr. Orozco’s team uses information about DNA sequences and physical characteristics not only to reproduce experimental data, but also to more quickly and accurately predict the location of nucleosomes.

“The accuracy of our model is comparable to that of the most advanced experimental methods,” says Dr. Orozco, head of the Molecular Modeling and Bioinformatics Laboratory 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 DNA sequence and physical signals emitted by gene ends. These signals determine the location of the first and last nucleosome (+1 and -last) and also affect the position of nucleosomes along the gene.

“Our work suggests that the structure of nucleosomes may impact gene expression in a more complex way than we thought,” adds Alba Sala, Ph.D. student at IRB Barcelona and first author of the study. ‘study.

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