The Violinist's Thumb: And Other Lost Tales of Love, War, and Genius, as Written by Our Genetic Code (47 page)

The sticking point, obviously, isn’t Maybelline-like variations in skin tone but other potential differences. Bruce Lahn, a geneticist at the University of Chicago, started his career cataloging palindromes and inversions on Y chromosomes, but around 2005 he began studying the brain genes
microcephalin
and
aspm,
which influence the growth of neurons. Although multiple versions exist in humans, one version of each gene had numerous hitchhikers and seemed to have swept through our ancestors at about Mach 10. This implied a strong survival advantage, and based on their ability to grow neurons, Lahn took a small leap and argued that these genes gave humans a cognitive boost. Intriguingly, he noted that the brain-boosting versions of
microcephalin
and
aspm
started to spread, respectively, around 35,000 BC and 4,000 BC, when, respectively, the first symbolic art and the first cities appeared in history. Hot on the trail, Lahn screened different populations alive today and determined that the brain-boosting versions appeared several times more often among Asians and Caucasians than among native Africans.
Gulp.

Other scientists denounced the findings as speculative, irresponsible, racist, and wrong. These two genes exercise
themselves in many places beyond the brain, so they may have aided ancient Europeans and Asians in other ways. The genes seem to help sperm whip their tails faster, for one thing, and might have outfitted the immune system with new weapons. (They’ve also been linked to perfect pitch, as well as tonal languages.) Even more damning, follow-up studies determined that people with these genes scored no better on IQ tests than those without them. This pretty much killed the brain-boosting hypothesis, and Lahn—who, for what it’s worth, is a Chinese immigrant—soon admitted, “On the scientific level, I am a little bit disappointed. But in the context of the social and political controversy, I am a little bit relieved.”

He wasn’t the only one: race really bifurcates geneticists. Some swear up and down that race doesn’t exist. It’s “biologically meaningless,” they maintain, a social construct.
Race
is indeed a loaded term, and most geneticists prefer to speak somewhat euphemistically of “ethnic groups” or “populations,” which they confess do exist. But even then some geneticists want to censor investigations into ethnic groups and mental aptitude as inherently wounding—they want a moratorium. Others remain confident that any good study will just prove racial equality, so what the hey, let them continue. (Of course the act of lecturing us about race, even to point out its nonexistence, probably just reinforces the idea. Quick—don’t think of green giraffes.)

Meanwhile some otherwise very pious scientists think the “biologically meaningless” bit is baloney. For one thing, some ethnic groups respond poorly—for purely biochemical reasons—to certain medications for hepatitis C and heart disease, among other ailments. Other groups, because of meager conditions in their ancient homelands, have become vulnerable to metabolic disorders in modern times of plenty. One controversial theory argues that descendants of people captured in slave raids in Africa have elevated rates of hypertension today in part because
ancestors of theirs whose bodies hoarded nutrients, especially salt, more easily survived the awful oceanic voyages to their new homes. A few ethnic groups even have higher immunity to HIV, but each group, again, for different biochemical reasons. In these and other cases—Crohn’s disease, diabetes, breast cancer—doctors and epidemiologists who deny race completely could harm people.

On a broader level, some scientists argue that races exist because each geographic population has, indisputably, distinct versions of some genes. If you examine even a few hundred snippets of someone’s DNA, you can segregate him into one of a few broad ancestral groups nearly 100 percent of the time. Like it or not, those groups do generally correspond to people’s traditional notion of races—African, Asian, Caucasian (or “swine-pink,” as one anthropologist put it), and so on. True, there’s always genetic bleed-over between ethnic groups, especially at geographic crossroads like India, a fact that renders the concept of race useless—too imprecise—for many scientific studies. But people’s self-identified social race does predict their biological population group pretty well. And because we don’t know what every distinct version of every stretch of DNA does, a few polemical and very stubborn scientists who study races/populations/whatever-you-want-to-call-thems argue that exploring potential differences in intellect is fair game—they resent being censored. Predictably, both those who affirm and those who deny race accuse the other side of letting politics color their science.
^*

Beyond race and sexuality, genetics has popped up recently in discussions of crime, gender relations, addiction, obesity, and many other things. Over the next few decades, in fact, genetic factors and susceptibilities will probably emerge for almost every human trait or behavior—take the over on that one. But regardless of what geneticists discover about these traits or behaviors, we should keep a few guidelines in mind when applying genetics
to social issues. Most important, no matter the biological underpinnings of a trait, ask yourself if it really makes sense to condemn or dismiss someone based on how a few microscopic genes behave. Also, remember that most of our genetic predilections for behavior were shaped by the African savanna many thousands if not millions of years ago. So while “natural” in some sense, these predilections don’t necessarily serve us well today, since we live in a radically different environment. What happens in nature is a poor guide for making decisions anyway. One of the biggest boners in ethical philosophy is the naturalistic fallacy, which equates nature with “what’s right” and uses “what’s natural” to justify or excuse prejudice. We human beings are
humane
in part because we can look beyond our biology.

In any study that touches on social issues, we can at least pause and not draw sensational conclusions without reasonably complete evidence. In the past five years, scientists have conscientiously sought out and sequenced DNA from more and more ethnic groups worldwide, to expand what remains, even today, an overwhelmingly European pool of genomes available to study. And some early results, especially from the self-explanatory 1,000 Genomes Project, indicate that scientists might have overestimated the importance of genetic sweeps—the same sweeps that ignited Lahn’s race-intelligence firecracker.

By 2010 geneticists had identified two thousand versions of human genes that showed signs of being swept along; specifically, because of low diversity around these genes, it looked as if hitchhiking had taken place. And when scientists looked for what differentiated these swept-along versions from versions not swept along, they found cases where a DNA triplet had mutated and now called for a new amino acid. This made sense: a new amino acid could change the protein, and if that change made someone fitter, natural selection might indeed sweep it through a population. However, when scientists examined other regions,
they found the same signs of sweeps in genes with
silent
mutations—mutations that, because of redundancy in the genetic code, didn’t change the amino acid. Natural selection cannot have swept these changes along, because the mutation would be invisible and offer no benefits. In other words, many apparent DNA sweeps could be spurious, artifacts of other evolutionary processes.

That doesn’t mean that sweeps never happen; scientists still believe that genes for lactose tolerance, hair structure, and a few other traits (including, ironically, skin color) did sweep through various ethnic groups at various points as migrants encountered new environments beyond Africa. But those might represent rare cases. Most human changes spread slowly, and probably no one ethnic group ever “leaped ahead” in a genetic sweepstakes by acquiring blockbuster genes. Any claims to the contrary—especially considering how often supposedly scientific claims about ethnic groups have fallen apart before—should be handled with caution. Because as the old saw says, it’s not what we don’t know that stirs up trouble, it’s what we do know that just ain’t so.

Becoming wiser in the ways of genetics will require not only advances in understanding how genes work, but advances in computing power. Moore’s Law for computers—which says that microchips get roughly twice as powerful every two years—has held for decades, which explains why some pet collars today could outperform the Apollo mission mainframes. But since 1990 genetic technology has outstripped even Moore’s projections. A modern DNA sequencer can generate more data in twenty-four hours than the Human Genome Project did in ten long years, and the technology has become increasingly convenient, spreading to labs and field stations worldwide. (After
killing Osama bin Laden in 2011, U.S. military personnel identified him—by matching his DNA to samples collected from relatives—within hours, in the middle of the ocean, in the dead of the a.m.) Simultaneously, the cost of sequencing an entire genome has gone into vacuum free-fall—from $3,000,000,000 to $10,000, from $1 per base pair to around 0.0003¢. If scientists want to study a single gene nowadays, it’s often cheaper to sequence the entire genome instead of bothering to isolate the gene first and sequence just that part.

Of course, scientists still need to
analyze
the bajillions of A’s, C’s, G’s, and T’s they’re gathering. Having been humbled by the HGP, they know they can’t just stare at the stream of raw data and expect insights to pop out,
Matrix
style. They need to consider how cells splice DNA and add epigenetic marginalia, much more complicated processes. They need to study how genes work in groups and how DNA packages itself in three dimensions inside the nucleus. Equally important, they need to determine how culture—itself a partial product of DNA—bends back and influences genetic evolution. Indeed, some scientists argue that the feedback loop between DNA and culture has not only influenced but outright dominated human evolution over the past sixty thousand years or so. Getting a handle on all of this will require serious computing horsepower. Craig Venter demanded a supercomputer, but geneticists in the future might need to turn to DNA itself, and develop tools based on its amazing computational powers.

On the software side of things, so-called genetic algorithms can help solve complicated problems by harnessing the power of evolution. In short, genetic algorithms treat the computer commands that programmers string together as individual “genes” strung together to make digital “chromosomes.” The programmer might start with a dozen different programs to test. He encodes the gene-commands in each one as binary 0s and 1s and
strings them together into one long, chromosome-like sequence (0001010111011101010…). Then comes the fun part. The programmer runs each program, evaluates it, and orders the best programs to “cross over”—to exchange strings of 0s and 1s, just like chromosomes exchange DNA. Next the programmer runs these hybrid programs and evaluates them. At this point the best cross over and exchange more 0s and 1s. The process then repeats, and continues again, and again, allowing the programs to evolve. Occasional “mutations”—flipping 0s to 1s, or vice versa—add more variety. Overall, genetic algorithms combine the best “genes” of many different programs into one near-optimal one. Even if you start with moronic programs, genetic evolution improves them automatically and zooms in on better ones.

On the hardware (or “wetware”) side of things, DNA could someday replace or augment silicon transistors and physically perform calculations. In one famous demonstration, a scientist used DNA to solve the classic traveling salesman problem. (In this brainteaser, a salesman has to travel to, say, eight cities scattered all over a map. He must visit each city once, but once he leaves a city he cannot visit it again, even just to pass through on his way somewhere else. Unfortunately, the cities have convoluted roads between them, so it’s not obvious in what order to visit.)

To see how DNA could possibly solve this problem, consider a hypothetical example. First thing, you’d make two sets of DNA snippets. All are single-stranded. The first set consists of the eight cities to visit, and these snippets can be random A-C-G-T strings: Sioux Falls might be AGCTACAT, Kalamazoo TCGACAAT. For the second set, use the map. Every road between two cities gets a DNA snippet. However—here’s the key—instead of making these snippets random, you do something clever. Say Highway 1 starts in Sioux Falls and ends in Kalamazoo. If you make the first half of the highway’s snippet the A/T and C/G
complement of half of Sioux Falls’s letters, and make the second half of the highway’s snippet the A/T and C/G complement of half of Kalamazoo’s letters, then Highway 1’s snippet can physically link the two cities: