GoKawiilEvery cell in the human body squeezes over six feet of DNA into a miniscule speck invisible to the naked eye—like compressing a whole house into a single sugar cube. In order to fit in a cell and remain organized, DNA is carefully wrapped around spool-like protein clusters called nucleosomes.
For decades, the prevailing view held that DNA is coiled so tightly around a nucleosome that it’s basically locked away and the cell can’t access it. Scientists believed only unwrapped DNA could be active. Now, a study from Gladstone Institutes and the Arc Institute challenges that black-and-white view.
Using a new AI-powered computational method, scientists discovered that most nucleosomes contain sections of DNA that are partially accessible to the cell, rather than fully wound up and packed away. The findings, published in the journal Nature, point to a previously unrecognized way that cells control their genes.
“The conception before was that, when it came to nucleosomes, genes were either turned on or off, but we’re finding it’s more like a volume dial,” says Gladstone Investigator Vijay Ramani, PhD, one of the scientists who led the new study. “This is a completely new organizational code for the genome.”
A New Way to Read DNA Packaging
All cells in the body carry the same DNA, but different cells use only the genes relevant to their specific jobs. To achieve this, cells have elaborate systems for controlling which genes are accessible and which are stored away. Nucleosomes have long been considered one of the primary elements of this filing system.
This is why researchers often study chromatin—which is all of a cell’s DNA packaged using nucleosomes—to get a sense of what genes a cell is using.
“Our findings suggest that the genome is far more dynamic and accessible that the scientific community realized.”
Vijay Ramani, PhD
The Ramani lab previously developed a technology called SAMOSA, which for the first time mapped where nucleosomes were located along individual DNA molecules. Their new tool, IDLI (Iteratively Defined Lengths of Inaccessibility), builds on that foundation using an AI model trained to recognize subtle differences between nucleosome structures within the SAMOSA sequencing data.
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