The Centers of Excellence in Genomic Science of the National Institutes of Health (NIH) has awarded a $11.2-million, five-year grant to an international team of researchers to establish the Center for Genome Imagine (CGI), the goal of which is to visualize the entire human genome at super-resolution.
The team is led by Ting Wu, Ph.D., at Harvard Medical School, Nicola Neretti at Brown University, Erez Lieberman Aiden at Baylor College of Medicine and Marc Marti-Renom at the Centre Nacional d’Anàlisi Genòmica – Centre for Genomic Regulation in Barcelona.
Over the past few years, the four laboratories have been developing super-resolution imaging technologies and computational methods, laying the foundation for the next phase of discovery.
“We already know how to look at relatively small subsections of the genome in super-resolution,” said Wu, who is professor of genetics at Harvard Medical School and an associate of the Wyss Institute. “The goal now is to innovate on top of our current foundation of technologies so that, soon, we will have a next generation of methods that will, finally, enable us to look at the entire human genome.”
“When it comes to the genome, the whole is truly greater than the sum of its parts,” she added, “The structure of the genome underlies both form and function and influences how our genes work.”
That structure, Wu explained, is central to everything from the proper formation of sperm and egg to replication, cell division, and development from embryo to adulthood. Every healthy cell contains a maternal and a paternal copy of the genome. The ability to observe genes during these biological events, and when they go awry, could provide new insights about genetic disease.
Current technologies for observing the genome at super-resolution and in a sequence-specific fashion can observe no more than a handful of genes—a mere 1% of the genome at a time. This is a problem, Wu explained, because genomic responses can involve hundreds to thousands of genes scattered across the entire genome. Monitoring a single gene is akin to attempting to understand human culture by observing a single person instead of a population, said Wu.
What the CGI reveals about the organization of genomes will ultimately contribute to our understanding of a wide variety of phenomena, such as chromosome stability, Wu said.
“The choreography of cell division with respect to reproduction is extraordinarily complex, with chromosomes pairing and then segregating from each other in unison across the entire genome, like a giant square dance,” said Wu.
“As with all phenomena, a better understanding of what happens when things go wrong could give us strategies for how to make things better,” said Wu.
Super-resolution imaging could also yield insights about parts of the genome that are still poorly understood, such repetitive sequences of DNA, which have been linked to genetic disease. Knowing how they are organized could help researchers better understand these links.
Each of the research groups at the four institutions has a different focus of expertise, ranging from genetics and genomics to chromosome mechanics, imaging at super-resolution, polymer-based, physics-based as well as restraint-based modeling.