A good example is short sight. In a society where only half the people are literate, the correlation between genes for short sight and short-sightedness is quite poor. In a society where everybody's reading books as a child, the correlation gets much better. So when the environmental factor, which is early reading, becomes stronger, the genetic variability becomes stronger. So actually what these studies are picking up is that the environment is good enough in American society to bring out the genetic variation between people. On the whole you're holding it constant. You're sending them to similar schools, giving them similar curriculums, and giving them similar toys to play with and similar television stations to watch. So you're bound to pick up the genetic differences. However, the twin studies have done a fantastic job of proving heritability of things like personality in particular societies. Going from that to finding out which genes are involved has proved immensely disappointing. There's no question that this is a huge failure. A lot of people ten years ago would have said it's now going to be comparatively easy to start walking down the genome, hunting the actual genes involved in extroversion or neuroticism, and it just doesn't work. Endless results show a small positive effect and then vanish, because it turns out either that the effect is associated only with one population, or it just doesn't replicate. Why is that? Is it because there are so many genes involved in these things that you can't pick out the ones with very small effects? Most of them do have very small effects. I don't think so; it's subtler than that. What's happening is that you're getting gene-environment interactions that are under the radar of the normal gene-hunting techniques.

A very nice example of this, which is still quite a controversial study, is Terrie Moffitt's work on antisocial behavior and the mono-amine oxidase-A gene on the x-chromosome, which is going to set the standard for how to understand the genes involved in personality and behavior. I write about it in Nature via Nurture. She's done a study of a cohort of New Zealanders in Dunedin who've been followed ever since birth. All the kids in this town were followed every year of their life to see what happened to them. It's about a thousand kids. If you take the 400 boys in the sample who have all-white genetic ancestry up to the grandparent level—boys because we're talking about a gene on the x-chromosome—and you look at their mono-amine oxidase-A gene, and you look at whether it's the high-active or low-active version—there are essentially two versions of this gene according to how active they are, according to whether the promoter on the front of the gene has got a certain number of repetitions or a lesser number—does the less active version of the gene correlate with ending up a young adult who is antisocial and who's in trouble with the law? No, it doesn't, in significant correlation. If you then break the data down, though, into those who were abused in their childhood and those who weren't, you find a very strong correlation with this gene. It turns out that if you have the low-active version of this gene, and you had an abusive childhood, then you're going to end up with an antisocial adult—not deterministically, but with a high probability. That seems to me to be a terribly important study, because it shows that when you parcel out the gene-environment interaction, you can find genes in here that you wouldn't have found with the conventional gene-hunting techniques—genes that correlate with behavior, but that react to the environment.

What are the social implications of finding this? Well, essentially there are none, because we were against child abuse before we knew which genes were involved, and we're against child abuse afterwards. It's possible that you can start to say to a kid who has been abused and it's too late to intervene, "You are going to be all right, because you don't have the particularly responsive version of the gene," or "You're not going to be all right, and therefore we should start putting you on Ritalin or Prozac to try and adjust your brain chemistry during your life." We're a long way from that yet, but that's the kind of social implication you could pull out of it.


If you go back to before the first two months of 1953, and ask yourself what people thought life was, you find nobody with anything like the right guess. Absolutely nobody is talking in terms of a linear digital code, until the morning of the 28th of February, 1953, when Jim Watson puts the base pairs together, and suddenly the idea of spelling out an infinitely long, infinitely variable, but completely faithfully reproducible code falls into place. You can say that Schrödinger used the term code script at one point, but he talked much more about quantum mechanical ideas and things like that. There were ideas that the secret of life was going to be some kind of piece of chemistry, a piece of energy, or a piece of quantum mechanics. There were all sorts of ideas out there, but nobody thought it would have anything to do with linear digital information, like we use in books, strings of alphabetical letters. That is why that is such an important moment, not because the thing was shaped like two spirals—that's just aesthetically pleasing—but because the world changed on that day. It took a long time for the world to realize it had changed, and Watson and Crick got invited to give zero seminars in Cambridge during the next three years, which is worth remembering, and there was nothing in the newspapers about it. 1953 was better known for many, many years as the year when Everest was climbed, the Queen was crowned, the first issue of Playboy was printed, and all these other tremendous anniversaries. But in retrospect we can see that it doesn't really click with the population at large until O. J. Simpson and Monica Lewinsky put DNA on the map in the '90s. It's forensic DNA, Alec Jeffries' discovery of DNA fingerprinting, that really brings it home to people what we're talking about here, which is a bar code, a message.

It's uncanny the way Turing and Shannon and all these people come together with ideas of computability, digital information theory, and cybernetics at around the same time as DNA falls into place. Suppose the base pairing mechanism of the double helix had been discovered in the 1920s, which is not totally impossible. The x-ray diffraction stuff wouldn't have been possible, but it's conceivable that a chemist could have worked out what was going on in DNA without x-ray diffraction. In the '20s, before computing, would we have even understood what we were looking at? Possibly not. Would we have been able to imagine one day reading it, and having the storage capacity to decode it? Or the other way of looking at it then is to suppose that DNA happens on schedule and we invent machines for sequencing DNA, but we haven't actually got computers by the '90s. How do we store the data? Do we have a lot of clerks writing it down instead of computers? It is wonderful the way the two branches of information technology, one called life and the other called electronics, fall into place at the same time. I don't understand how that kind of serendipity works in history, but it's an intriguing one.

In retrospect it became inevitable once we knew the genetic code and how it was spelled out that one day we'd read the entire script of the human recipe. It's quite surprising to think back to the mid-'80s and realize how controversial it was that people suggested it. It was a tremendous distraction for biology from most important tasks. It's far too expensive, and most of it is junk anyway. We shouldn't read the whole thing, but should just do the interesting bits. The idea of the human genome was a very controversial one. But a lot of people had faith that if you start reading genes, the technology will catch up and get cheap enough so that you can finish the job. And so it proved. Let's face it, the human genome project started in about 1986 or '87, and between 1986 and 1998 it read maybe 10% of the genome. And then it read 90% in the last year. I personally think that the trajectory would have been much the same without Craig Venter's intervention. What would not have happened is the publishing of a draft rough sequence in 2000. The key date would have been the finishing of the golden, perfect sequence in 2003, which is just happening as we're speaking. The trajectory to getting to that actually wasn't changed by Venter's intervention, but in order for the human genome project to announce a dead heat with Craig Venter's shotgun sequencing technique, we all think of 2000 as being the year when it was finished. In fact, what was finished then was a pretty messy draft that wasn't much use.

What's next? Lots of other genomes. It's going to be very important to get the chimpanzee genome. The dog is going to be interesting, because then we can start to look at the behavioral differences between breeds of dogs, and that'll pull out genes to do with behavior. The mouse is obviously a key one for medical research. We've already got the mouse genome. The rat comes soon. All the others like the rice genome, which has just been finished. There's going to be scores and scores of genomes sequenced. Then we can start talking about individual genomes, and Craig Venter foresees the day when you or I can have our genome done for a thousand dollars. I suspect there won't be much point in doing whole genome sequencing for individuals, but there's going to be a huge significance in doing the interesting bits once we start to work out what they are.

There's no question that the discovery moves in silicon now. In other words, a huge amount of the significant stuff that we do next has to be both understood inside a computer and modeled inside computers. The modeling of gene interactions is something that is beyond the power of a man with a pencil. It's going to require people who are good at systems dynamics. People who come out of business schools are quite good at this kind of thing. It's going to come from some funny directions. The economists are quite good at this kind of thing. The genome is going to turn out to be quite like an economy. When you adjust interest rates you have some effects here and other effects there, and then they have effects and they affect what affects interest rates and so it all feeds back on itself. A lot of genomic phenomena are going to turn out to be like that. So I do think that bioinformatics is the way a lot of this is going. You only have to look inside a molecular biology lab these days and see that they spend half their time comparing sequences on the Web with other sequences, pulling out sequences that are similar, saying, "Oh my goodness, this gene is like that one in fruit flies." But there's still going to be room for a lot of very important wet biology in this, particularly when you get inside the brain, because what's going to turn out is that the gross structure of the brain conceals immense amounts of detail about which nerve cells are talking to which nerve cells, and the genes are going to be the key to finding out what's going on there. These alternatively spliced genes that seem to enable each nerve cell to have almost a unique bar code on it that tells it who it needs to link up with when it gets to its target. There's still room for some heroic biology in there.

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