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Code reader After revolutionizing methods of studying
genetics, Wen-Hsiung Li reads deep into DNA sequences to unravel
molecular mysteries.
Yet in September the Milan–based International Balzan Foundation named him a winner, and in November Li, the George Beadle distinguished service professor in Ecology & Evolution and the Committee on Evolutionary Biology, traveled to Berne, Switzerland, to accept his award. The foundation cited Li’s “many fundamental contributions to molecular evolution,” including developing methods “for inferring evolutionary relationships from comparison of DNA sequences” and for “estimating the degree of accuracy of evolutionary trees.” Molecular evolution has fascinated the Taiwan native since the late 1960s. As a Brown University doctoral student in applied mathematics, he noticed that biology was one branch of science “in which mathematics was not so well developed,” and that applying math to genetics in particular might help to better explain many “mysteries in life,” such as why children resemble their parents. Before joining Chicago’s faculty in 1999, Li, who wrote the first textbook on molecular evolution, spent 26 years at the University of Texas Health Science Center in Houston. As a postdoc there he began research on the “molecular clock,” or the rate at which species’ genes mutate, determining their genetic diversification. That work produced one of his first major contributions to the field. Since 1965 researchers had used protein sequences to study molecular clocks, theorizing that protein sequences evolved at a constant rate across species. By the 1980s data for DNA sequences—which contain more information than protein sequences—had become widely available, and Li realized that they could better determine gene-mutation rates. In 1985 he and Chung-I Wu, also a University of Texas postdoc and now chair of Chicago’s Ecology & Evolution department, employed DNA data to show that molecular clocks actually are dependent on generation time: the shorter a species’ life span, the faster the clock. A rodent’s molecular clock, for example, advances five times faster than that of humans. Even more important than their discovery was the method by which they found it. Comparing human and rodent DNA sequences revealed that the two were different, but not which species evolved faster. So Li brought in a third organism, called an out-group, equally related to both human and rodent by time elapsed since splitting from a common ancestor—in this case a dog, cow, or rabbit, depending on which genes were available. Li could tell whether the rodent or the human had evolved faster by charting which animal’s DNA sequence varied more from the out-group’s. A computer analysis showed that the rodent’s sequence had changed more than the human’s—so the rodent had evolved faster. This “relative rate test,” using a third organism equally related in evolutionary time to both species under question, is now a standard method for molecular biology research. In another major contribution, Li improved ways to test statistical confidence in evolutionary trees—charts tracing organisms’ genetic relationships, such as the 1980s tree demonstrating that humans and chimpanzees are more closely related than chimps and gorillas. In 1996 he created a method of randomly selecting genetic coding from different nucleotide sites to compare organisms. Like a statistically accurate survey using a random sample, the more often the two organisms appear to be similar, the higher the confidence that the evolutionary tree is accurate. With the recent flood of biological data from the Human Genome Project, Li’s research scope has broadened dramatically. “In the old days we looked for genes by disease or by trait,” he says. Now biologists study specific DNA sequences and try to figure out what they do. One study that Li says would have taken much longer before the human genome was mapped involved the genetic mutation rates in males and females. Mutations occur during cell division, and because sperm cells divide constantly—as opposed to egg cells, which are mostly formed when a female is born—there is increased opportunity for genetic error—and thus evolution—in males. Two previous studies had argued that the male-female mutation ratio was only two to one—a difference not large enough, Li says, to account for human evolution. He and research associate Kateryna Makova compared human and monkey genetic-sequence data found on both the Y and X chromosomes, and later on both the Y and an autosome, or nonsex chromosome, finding a six-to-one ratio, which they published in the August 11, 2002, Nature. They further showed that the mutation rate is higher in rodents than in primates—confirming Li’s molecular-clock research. The human-genome information also has helped Li to home in on the mysteries of DNA itself, studying its noncoding regions—the spaces between the coding—called “junk DNA” until scientists showed that at least some of it has specific functions. Li did a computational analysis, reported in the February 12, 2001, Nature, showing that such regions make up 46 percent of the human genome. He speculated that noncoding regions may provide clues to how human genes evolve. In the coding regions, meanwhile, Li and his lab colleagues are attempting to unravel the enigma of duplicate genes. Why, researchers have wondered, would an organism need two genes with the same coding? In two articles this year—one in Trends in Genetics and one in Genome Research—Li has begun to explain this apparent redundancy. His lab, using microarrays that brighten as more copies of a gene are expressed, showed that in both yeast and humans, after genes duplicate, their expression patterns—when and where they are activated—change rapidly. So both genes, if used in different times and places, may be necessary. Li’s lab is studying why those expression patterns might alter. Second-year graduate student Geoffrey Morris, for example, is investigating yeast DNA’s noncoding regions, which, he says, control gene expression. In another experiment Li and Zhenglong Gu, PhD’03, removed each of the 6,000 genes in a yeast sample, one by one, to test how each gene’s removal would affect the yeast’s growth. As they reported in the January 2, 2003, Nature, the yeast grew better if the removed gene had a duplicate inside the sample than if the gene was unique. Duplicate genes, they showed, may help protect against harmful mutations. The findings emerging from Li’s lab at
such a rapid pace may come to show that his earlier work, which
helped him win the Balzan Prize, was only the beginning of a prolific
career. Reading deep into DNA’s nether regions could yield
an important encore.—A.M.B.
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