The National Human Genome Research Institute (NHGRI) recently awarded Degui Zhi, Ph.D., SBMI associate professor, with a grant worth more than $2.3 million dollars. The grant title is “Scalable methods for identity by descent.”
Zhi, the grant contact principal investigator, is working with Co-Principal Investigator Shaojie Zhang, Ph.D., an associate professor in computer science from the University of Central Florida.
“With this grant, our team is developing algorithms to identify shared DNA segments within large cohorts,” Zhi stated. “We aim to advance genetic research by building new informatics tools that reveal detailed genetic relationships between humans.”
The research team developed an efficient tool called RaPID. It is the first computationally feasible method for inferring identity-by-descent (IBD) segments among individuals in a biobank-scale cohort. The core algorithm within the tool lets researchers evaluate data in linear time, giving researchers the ability to identify shared segments and reconstruct genetic history.
“Recently, IBD segment detection tools were used to identify the Golden State Killer, who was uncaught for over 40 years before a DNA search found a relative of the killer in a large online database,” said Zhi. “While it took hours for existing tools to find the match, it would take RaPID seconds.”
Beyond the medical relevance the research has for investigators looking for ways to leverage genetic information, there are recreational benefits of the research as well. Identifying shared DNA segments allows people to connect by way of common ancestry.
“All human are connected into a giant pedigree,” noted Zhi. “Any two individuals share some common ancestor – often several generations into the past and their connections cannot be easily traced. DNA is a book that holds our genetic history and this research gives us the ability to see how humans are connected.”
The project will begin June 1 and concludes at the end of March 2022.
published on 5/31/2018 at 12:10 p.m.