New USTAR Team Seeks to Become a World Leader in Genetic Discovery

The Utah Science Technology and Research initiative, in partnership with the University of Utah Health Sciences, has created a new Genetic Discovery team housed in the School of Medicine in order to develop and commercialize computational methods of discovering relationships between genes and diseases, enabling more effective diagnoses and treatments, making marketable agricultural discoveries and improving forensic identification methods. 


The mission of the genetic discovery team is facilitating the discovery of medically and clinically important genes. Gabor Marth, a human genetics professor with expertise in sequence analysis, and Mark Yandell, a human genetics professor with expertise in interpreting data, will co-direct the center. The two have worked together for more than fifteen years.

“Mark and I started our careers together,” said Marth. “I develop hardcore computational algorithms for more accurate, more efficient variant discovery. Mark occupies a slightly different but overlapping area. He’s got computational tools and software and algorithms that can sift through various genetic defects and find the one or ones that are most likely to actually be causing the disease.”

Collecting data from the sequence of an individual’s chromosomes enables researchers to look for defective genes, or genes that are typically associated with certain diseases. Knowing there’s a specific defect in a gene and that there is a therapy available that relates to it can steer a patient towards appropriate treatment.

Marth says some diseases are not always caused by the same exact defect or a defect even in the same gene. It could be that any one of twenty genes could be the cause of the disease. In some cases finding a defect in a gene may only tell you that you have a higher probability of developing a certain disease, but it doesn’t necessarily mean that you are going to get it. 

“A good example of this is mutations related to breast cancer,” said Marth. “If there are certain mutations in your genes, you have a high chance that you will develop breast cancer, but it’s not certain. You might have a 50 percent chance of developing breast cancer, but there are preventative options available.” 

The Genetic Discovery team will build a computational software infrastructure to store and annotate DNA sequence data from specific patients enrolled in medical research studies. The data will be processed and analyzed in order to discover defective genes that are causing disease in an individual or a family. 

“We are also putting together systems where a single patient’s genome comes through, and we layer on top of it other information we know about the particular disease,” said Marth. “The hope is that we gain an understanding of which variant causes the disease in that particular individual, and build systems that will enable us to enter that data into the electronic health record so they can go further down the line to a clinician.”

With the combined expertise of Marth and Yandell, the team positions Utah as a world leader in genetic discovery. Utah’s family-centered population makes it a unique and invaluable resource when it comes to family-based genetics. Having access to multiple family members’ DNA enables researchers to single-out the defective gene or genes more easily. For example, if there are multiple individuals in a family that are afflicted with the same disease, it is likely that the same genetic variant is causing it. 

 “A real competitive advantage for this center is that we will be able to access not only a single individual’s DNA, but probably the DNA of an individual’s family members as well,” said Marth. “What we are doing is important and necessary, because it turns out there is no complete discovery system that can do what we are describing here.”

Marth hopes the Genetic Discovery team can create a continuous loop between patients, genetic scientists and physicians to discover variants in individuals, interpret them, and use this genetic information to guide treatment plans.