Realistic 3D models help scientists understand genome interaction


A new approach to visualizing the physical and structural attributes of chromosomes to provide scientists with realistic 3D models that will help them better understand which parts of a genome are interacting with one another.


A team of researchers at UMass Medical School and the Prince Felipe Research Centre in Spain have developed a new technology capable of producing high resolution, three-dimensional images of dense genetic areas in the human chromosome. This new approach to visualizing the physical and structural attributes of chromosomes—published this week in Nature Structural & Molecular Biology—promises to provide scientists with realistic 3D models that will help them better understand which parts of the genome are interacting with one another.

Scientists know that the shape and structure of the human genome varies from cell to cell depending on which genes are active. Current efforts to study the human genome, however, are often done in a two-dimensional, linear sequence, an approach that fails to adequately account for how the physical shape and structure of the genome contributes to its ability to regulate genes and carry out tasks. Recent insights indicate that genetic elements spaced far apart along the genome may, in fact, be interacting thanks to “folding” or “looping” that brings them into close physical proximity—much like folding a narrow piece of paper down the middle brings the ends into contact.

“Having a 3D image of a chromosome tells us where to look for areas of the genome that we may not know are interacting,” said Job Dekker, PhD, associate professor of biochemistry & molecular pharmacology and molecular medicine and lead researcher on the study. “It could help identify new genes that are active in diseased cells or regulatory elements that are helping to control those genes.”

The team’s research details how genetic interaction and spatial proximity data can be translated into an accurate 3D model of a chromosomal segment using a computational model known as integrated modeling platform (IMP). To test their method, Dr. Dekker and colleagues focused on nearly identical, 500 kilobase segments on human chromosome 16 in two different types of cells—a lymphoid cell and a leukemia cell. An already extensively studied region of the genome that houses a number of active genes responsible for basic cellular maintenance regardless of cell type, chromosome 16 differs in one important way in these two cells: a group of genes not active in the lymphoid cells are highly expressed in the leukemia cells, giving Dekker and colleagues a readily identifiable model for comparison.

“By using thousands of experimental data points that tell us which parts of the genome are near each other and combining that data with a computational tool that accounts for all these various interactions spatially, we were able to produce a 3D model that accurately expresses how the chromosome appears in its natural state,” said Dekker. Results of these experiments, which are consistent with known looping interactions between distant elements in lymphoid and leukemia cells, show distinct physical characteristics between the two cells.

Dekker and colleagues have already observed likely interactions that have not previously been described, such as the relative positioning of active genes and regulatory elements along the genome. “Our next step will be to further develop the technology so that we can model the structure of the entire chromosome.”

Also contributing to the work are UMMS post-doc Amartya Sanyal and graduate student Bryan R. Lajoi, who are members of the Dekker lab. Jeanne B. Lawrence, PhD, professor of cell biology, provided chromosome imaging expertise in validating the models.