The revolution sparked by the Human Genome Project will soon produce more genetic information than our computers can currently handle.
Question: What does your research consistrn of on a day-to-dayrnbasis?
rnrnMichael Wigler: Our lab studies the genome rnof organisms andrnalso the genome of cancer cells. rnAnd we work on two kinds of problems: the evolution and outcome rnofrncancers, and also on genetic disorders of a spontaneous sort, that is,rnnon-heritable genetic disorders. rnAnd those are two very—it sounds like two very different things, rnbutrnthey’re related by our methodology, which is genomic analysis.
rnrnWhat we do is called difference analysis, for rnexample, ifrnwe’re looking at a cancer, we’ll want to see where that cancer has rnmutatedrnrelative to the genome of the person who gave rise to that cancer. That’s differential genomicrnanalysis. And it tells us wherernthe cancer has mutated. And fromrnthe types of mutations, the number of mutations, we can infer a lot rnaboutrncancer etiology.
rnrnQuestion: Is biology becoming a more rnquantitative thanrnqualitative science?
rnrnMichael Wigler: Well, biology has always rnbeen influencedrnstrongly by quantitative types. rnMany physicists in the late ‘30s, early ‘40s, ‘50s, came into rnbiology,rnstrongly influenced it. There wasrna period, I would say, from the time I was a graduate student in the rnmid-‘70srnuntil the mid- to late-‘90s, where it was not particularly quantitative,rn and that wasrnlargely because of the revolution in recombinant DNA. So,rn really all you needed to be a good biologist was a goodrnsense of logic and a good imagination. rnAnd mathematical and statistical skills weren’t really that rnnecessaryrnfor much of biology. And I was inrnthat group actually. I had studiedrnearlier on as a mathematician but I used almost none of those rnmathematicalrntools when doing biological research. rnOf course, the logic comes in handy, but the tools were not veryrnvaluable. There was no place forrnthem because the kind of data that we were getting was very individual rndata andrnI actually had a rule of thumb. I actually disliked statistics early on rnin myrnlife and I felt that if I needed to do statistics to see what I was rnobserving,rnthen I wasn’t really observing anything.
rnrnBut that changed with the advent of the sequencing rnof thernhuman genome. That changedrneverything. And the development ofrnnew high throughput methods of extracting data, it forced biologists tornreconsider the value of statistics and mathematics in the analysis of rntheirrnsubject. So, a number ofrnbiologists moved in that direction. rnNot a lot, but quite a number did. rnAnd I was one of those who moved in that direction.
rnrnQuestion: How has the sequencing of the rngenome “changedrneverything”?
rnrnMichael Wigler: You know, we are so close, rnhistorically, tornthat period, and the data that’s coming out of that effort is still rnbeingrngenerated. I think it’s very hardrnfor any of us to really judge the impact that it has had. rn It was a huge revolution in terms ofrnthe kinds of experiments one can conceive of doing. Thern only thing comparable in my lifetime was the recombinantrnDNA revolution which changed entirely the kinds of experiments people rndid.
rnrnSince sequencing methods are changing so fast, the rncost ofrnsequencing has dropped enormously. rnAnd with each drop in the cost, it changes entirely how you thinkrn ofrnattacking the problem. So, in arnfew years from now we’ll be in a position to have DNA sequence of a veryrn highrnquality for a million people and know the medical history of these rnmillionrnpeople. And there’ll be—I don’trneven think our computers are yet to a stage where they will be able to rnhandlerndata of that type and the kind of analysis tools that will be needed to rnanalyzernthat haven’t been developed yet. rnSo, we’re in a really a strange point in the history of biology rnwherernthings are changing so rapidly, we can’t quite see the shape of the rnfuturernyet.
Recorded April 12, 2010