Mathematician receives grant to create 3D genome models
SF State researcher Javier Arsuaga will share in a $1.5 million, four-year grant from the National Institutes of Health to create three-dimensional reconstructions of genomes.
The project, which combines biology and mathematical modeling, could help researchers better understand chromosome alterations that occur in certain cancers and with other DNA-damaging toxins, said Arsuaga, an associate professor of Mathematics.
Arsuaga is co-principal investigator on the NIH grant and will work with co-investigator Mariel Vazquez, associate professor of mathematics at SF State, and co-principal investigator Mark Segal, director of the Center of Bioinformatics & Molecular Biostatistics at University of California, San Francisco.
Arsuaga and colleagues want to test several 3D models of genome architecture to get a better look at how genome structure contributes to these key biological processes. “When we learn biology at school we always think of the genome as a static structure where enzymes come and go,” he explained. “However, the genome can be very dynamic, and how these processes occur may be very different from what we envision.”The massive amounts of data contained in a genome must be packed inside cells with exquisite architectural precision. The human genome, for instance, gets squeezed into a volume 10,000 times smaller than when allowed to unravel freely. This precise packing guides critical processes such as transcribing and translating genes, and DNA repair.
The research team will use the grant to expand upon simpler models that have so far provided only a limited view of how the genome looks and behaves in 3D. “One needs to be able to reconstruct the entire structure to begin asking questions about how biology works, and how we can better use it to our advantage in the development of therapies,” Arsuaga said.
The sheer amount of data contained in even the smallest genome means that a diverse set of researchers must work together to gain a clear understanding of how biology works at the DNA level, Arsuaga said.
In the past 20 years, he explained, biology has been revolutionized by technologies that allow researchers to analyze thousands or even millions of biological variables at once. “The question for computational biologists, mathematicians and statisticians is how to make sense of this ocean of information and how to find parameters that are truly relevant.”
His SF State master’s students encounter this revolution when they work on their theses, combining biology with computer science, algorithm design, statistics and physics. “When they are faced with a problem like this, students first realize that the boundaries among scientific disciplines are just not there,” Arsuaga said. “I personally think this is one of the most beautiful aspects of our research.”
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