Ajay Royyuru: Genographer
Royyuru manages a computational biology lab and runs the computing research for the Genographic Project
Where did we come from? How did we get here? The Genographic Project—a joint effort of the National Geographic Society, in Washington, D.C., and IBM Corp.—aims to answer those big questions once and for all. Using genetic data from thousands of people around the world, it plans to construct a map of human migration, spanning millennia from our origins in Africa to the present.
If this is anthropology’s moon shot—as some say it is—then its chief rocket scientist is Ajay Royyuru, senior manager of the Computational Biology Center at IBM’s Thomas J. Watson Research Center, Yorktown Heights, N.Y. “We get to pursue an innovation that will hopefully touch every individual on the planet,” Royyuru says of the project. “You don’t get to do that all the time.”
The Genographic Project, which began in April 2005 and is scheduled to run for five years, aims to collect DNA and anthropological data—such as languages spoken—from thousands of volunteers, including more than 100 000 of the world’s remaining indigenous people. It will then study the mutations, called markers, in certain stretches of their DNA to infer ancestry.
For example, a mutation going by the ungainly name of “mitochondrial haplogroup D” first happened about 25 000 years ago in Central Asia and is one of five mutations found in all Native American DNA. But it’s also common in the DNA of indigenous people in northeast Asia, evidence that the first Americans arrived by migrating from that part of Asia across the Bering Strait.
The project’s scientists already know of dozens of markers and hope to find many more. That still leaves the hard problem of figuring out where and when they occurred—in other words, uncovering who our common ancestors were. It’s a job well suited to clever algorithms and complex computation, perfect for the mix of biologists and computer scientists Royyuru leads.
Royyuru is curious and enthusiastic, but also exacting. In a single afternoon’s conversation, he mentions the importance of doing the computational work of the Genographic Project correctly no fewer than three times.
Although a molecular biologist by training, he has been doing computer science his whole career, starting with his Ph.D. at the Tata Institute of Fundamental Research, in Mumbai, hundreds of kilometers west of his central Indian hometown of Bhilai. In a way, Royyuru, 41, was born at the right time. Computational biology—the use of information technology to solve biological problems—came of age as a discipline just as he did himself, during his college and graduate school years. As the volume of gene sequences, molecular structures, and other biological data ballooned, computers began to take a starring role in making sense of it all. “I was lucky to be there from the time it began happening,” he says.
By the time he left the Tata Institute, his research was done almost completely in front of a computer instead of at a lab bench. He went from Mumbai to a postdoctoral research spot in New York City at Memorial Sloan-Kettering Cancer Center, where he developed computational tricks to reveal the three-dimensional structure of a bovine version of HIV. “Most of my research was taking the data, analyzing it, and breathing meaning into it.”
Having spent so much time solving biology’s problems with computers, developing software to help other scientists do the same seemed like a natural next step. He moved to San Diego for a position at Accelrys Software Inc., a maker of molecular modeling programs, but found disappointment. “That’s where I realized that research was my true calling, not software,” he says. Developing software so other people could answer the big questions wasn’t for him. He wanted to get back to answering them himself.
When Royyuru came back to the New York City area to join IBM’s life sciences research division in 1998, it consisted of only a few people. But as the idea grew that life sciences could showcase the cutting edge of computing technology, so did the number of researchers. Today he runs the computational biology section just like an academic laboratory, with a focus on publishable research results, open debate, and occasional argument. His team of 35 scientists and engineers works on a host of research problems besides the Genographic Project, and he’s in charge of choosing which problems his lab should tackle next. “What’s really fun is seeing what the future is,” he says in a conspiratorial tone. “The role of the strategist is what I enjoy the most.”
It’s a big challenge for him to pinpoint which biological questions deserve IBM’s computational might. “The opportunities are immense, and yet you can’t do all of it at once,” he says. He looks for projects that not only are exciting and scientifically valuable but also give his researchers and IBM the expertise to tackle other worthy—and potentially profitable—problems.
The Genographic Project is a case in point. Even though those thousands of volunteers have offered no personal medical information, the algorithms Royyuru is developing to sift through their genetic and cultural data will be useful in extracting meaning from electronic medical records. The ability to interpret such data is key to the promise of personalized medicine, in which therapies can be tailored to a person’s genetic peculiarities—avoiding unpleasant side effects and potentially deadly mistakes.
While it’s part of his job to find such tangible value for IBM, Royyuru’s motivations are far from mercenary. “We get to do something that will make a difference for the vast majority of the planet,” he says.
Ajay Royyuru (M)
What he does: Manages a computational biology lab and runs the computing research for the Genographic Project, a five-year effort to map human migration, from its origins to the present, using clues in human DNA.
For whom: IBM Corp.
Where he does it: IBM’s Thomas J. Watson Research Center, in Yorktown Heights, N.Y.
Fun factor: His computational algorithms could tell us where we all came from and how we got here.