X chromosome inactivation equalizes the active X chromosomes between mammals with two X chromosomes and mammals with one X and one Y chromosome – however, the mechanisms of this inactivation have not been understood at a granular level due to the coarseness of experimental imaging. Now, researchers at Los Alamos National Laboratory (LANL) have modeled the process on supercomputers, helping researchers to understand the exact processes of the inactivation.

Using data from Harvard University and Massachusetts General Hospital, the researchers created a 3D model of the process that includes the motion of the chromosome and the RNA particles surrounding it. The model was run on Los Alamos’ in-house supercomputers.

“From experimental data alone, which is 2D and static, you don’t have the resolution to see a whole chromosome at this level of detail,” explained Anna Lappala, a visiting scientist at LANL and a polymer physicist with Harvard and Massachusetts General Hospital. “With this modeling, we can see the processes regulating gene expression, and the modeling is grounded in 2D experimental data from our collaborators[.]”

The model shows RNA particles covering the X chromosome, then entering it to inactivate the chromosome. “This is the first time we’ve been able to model all the RNA spreading around the chromosome and shutting it down,” Lappala said.

The researchers say that this model will help scientists understand gene expression and related diseases, especially those that occur when the second X chromosome is not fully inactivated or reactivates later in life. “Our main goal was to see the chromosome change its shape and to see gene-expression levels over time,” said Karissa Sanbonmatsu, a structural biologist at LANL and project lead for the computational approach. “The hypothesis is that a compacted, tightly structured chromosome tends to turn off genes, but there are not a lot of smoking guns about this. By modeling 3D structures in motion, we can get closer to the relationship between structural compaction and turning off genes.”

The researchers are also excited about the implications of their research for other outstanding modeling roadblocks. “What’s been missing in the field is some way for a user who’s not computationally savvy to go interactively into a chromosome,” Lee said, explaining that the model developed through LANL allows users to much more easily navigate the chromosome model. “The method allows us to develop an interactive model of this epigenetic process,” added Jeannie T. Lee, a professor of genetics at Harvard Medical School and vice chair of molecular biology at Massachusetts General Hospital.

To learn more, read the release from LANL here.