Editors note: This is part of a series of interviews produced in cooperation with the World Economic Forum with members of its program on Young Scientists, who will be appearing at the Forum’s Annual Meeting of the New Champions. A Q&A with applied mathematics researcher Erez Lieberman follows.
Your work has included analyzing 5 million books for Google, developing a shoe that helps people prone to falling, and developing a theory relating evolution and economics: is there one guiding philosophy that underpins your work?
Some labs are practitioners of particular methods, and hunt for problems that are a good fit with their method. My lab is different. We are always trying to work on the most fascinating and important problems in science, even if we don’t know anything about them at the outset. As we work on a problem, we very gradually figure out what we need to do—the methods we need to master—to solve it. Like the best teachers, a good problem exposes you to new ideas that you never imagined would interest you, and to new collaborators, whom you otherwise wouldn’t talk to. Along the way, it rewards your efforts with discoveries—usually tiny ones—and encourages you to keep at it and do your very best. Recently I heard someone say that, intellectually, you are the product of the five people you know best. There’s some truth to that, but I would also say that, intellectually, you are the product of the five problems you’ve worked on the most. Choose your problems wisely!
You developed the Hi-C, a new technique for reverse-engineering how genomes fold, when you were still in your twenties. How has this work moved on since?
Since my work with Nynke van Berkum, Louise Williams, Andi Gnirke, Job Dekker and Eric Lander to develop Hi-C, the method has been used to create hundreds of 3D maps, spanning an extraordinary range of organisms. It has been very exciting to see all the progress. Not a day goes by without new Hi-C results appearing. Actually, the U.S. National Institutes of Health has created a 10-year 4D Nucleome initiative to map the human genome in 3D. I was very pleased to serve on the advisory panel for that and am tremendously excited about the potential for new discoveries.
Still, I confess that I was for a very long time a bit disappointed in Hi-C. That is because my personal interest in 3D maps has always centered on a very specific problem. One of the great mysteries in modern genetics is the problem of “spooky action at a distance”: how is it that a gene that lies in one place in the human genome can be turned on or off by bits of DNA that lie far away along the DNA strand? For decades, people suspected that when the genome folds, it forms loops, and that these loops are responsible for the “spooky” action. The reason I originally proposed Hi-C – the killer app, if you will—was that I thought it would eventually be possible to use Hi-C to map all the loops in the human genome. Unfortunately, though the original Hi-C method made a lot of discoveries possible, it couldn’t achieve anything close to the resolution that was needed to map loops. So this problem, mapping the loops, was gnawing at me for a long time.
Fortunately, two crazy students of mine—Suhas Rao and Miriam Huntley—spent five years leading an effort in my lab to overcome the resolution issue in Hi-C. By dramatically improving the resolution, they showed that it was possible to map the loops in the human genome. They could even figure out the rules for when loops form, and show how loops turn genes on and off—basically, they showed that looping is in many ways a new form of genetic regulation which obeys its own set of rules. Those results just appeared in December 2014. So now, for the first time, I feel I can wholeheartedly say that Hi-C is pretty good.
If you could make one thing happen in the world of science right now, what would it be?
Humans are the ultimate apex predator—faster and faster, our activities are causing species around us to disappear. For a thousand reasons, we need to learn to become responsible citizens of the Earth. But unfortunately, it’s proven extremely hard to muster the resources and the collective will to change how we live. Changing that reality is essential.
Nevertheless—though it pains me to say it—as a stop-gap measure, we ought to consider using genome-sequencing technology to create an archive of the genomes of all living things. Such an archive would aid conservation efforts, and may allow us to bring back species that have gone extinct. The effort would probably cost about as much as the original human genome project—it’s doable, and we should do it.