Chromosomes are masters of organization. These long strings of DNA fold down into an ensemble of compact structures that keep needed parts of the genome accessible while tucking away those that aren’t used as often. Understanding the complexity of these structures has been challenging; chromosomes are large systems, and deciphering the structure and dynamics requires a combination of experimental data and theoretical approaches. The FI-Chrom method, shared in a recent PNAS publication by Rice’s José Onuchic and Vinícius Contessoto, is a new and effective approach for creating 3D maps of chromosomes from real-world data.
FI-Chrom uses data from chromosome Hi-C maps. These maps break out the chromosome into units of length called beads — about 500,000 linear DNA bases each — and show how frequently each bead is close to other beads. This information shows only probabilities of any two beads being neighbors and no direct three-dimensional information. Imagine it as a logic puzzle where the rules, or parameters, read something like this: Bead A is 99% likely to be close to Bead B, 36% likely to be close to Bead C and 62% likely to be close to Bead D. A 3D model, the researchers knew, could be built by placing every bead in a space that didn’t violate any of the Hi-C map’s parameters. The only problem is that in Hi-C maps, there are hundreds of thousands of beads and tens of millions of mapped interactions showing bead closeness.
“We had chromosome maps that gave us, theoretically, 3D information, but we were really reading them in 2D space,” explains Onuchic, the Harry C. and Olga K. Wiess Chair of Physics and a corresponding author of the study. “Now, we have created FI-Chrom, an open-access program that can turn these Hi-C maps into 3D models of chromosomes.”
