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Renfrew sees this last approach, which he calls archaeogenetics, as progressing most rapidly. So far, archaeogenetics has relied principally on analysis of human mitochondrial DNA (mtDNA), which is found not in the paired chromosomes within cell nuclei but in tiny loops, called plasmids, inside the mitochondria that generate most of the cell’s chemical energy. Unlike chromosomal DNA, mtDNA derives only from the ovum–so it represents only the maternal lineage–and does not recombine from generation to generation. Thus, it’s essentially static. Yet over thousands of years, single-­nucleotide polymorphisms–mutations that alter a ­single DNA base pair–do occur in mitochondria at a statistically predictable rate. Given that mutation rate, modern researchers can analyze and compare mtDNA ­samples from individuals throughout the world, using the similarities and differences to construct a great human family tree.

Furthermore, Renfrew told me, “studies of mtDNA mutation rates give an approximate chronology that ties quite nicely to data from radiocarbon dating of fossil remains.” Like radiocarbon dating itself, mtDNA analysis has refuted long-cherished myths about race by showing that humankind almost certainly had a single origin in Africa, with our main dispersal out of that continent occurring about 60,000 years ago and proba­bly involving a relatively small number of humans. During humanity’s global diaspora, many populations grew isolated. Today, mitochondrial haplogroups–groups that share common ancestors–are identifiable as originating in Africa, Europe, Asia, the Americas, and the Pacific Islands.

Mitochondrial-DNA analysis is only one tool in an expanding genomic arsenal. The fuller picture is, perhaps, even more dramatic than Renfrew suggests. Increasingly, we look like just one taxonomic variant within the continuum of the hominid clade: a FOXP2 gene variant strongly implicated in our language capabilities, for instance, is one we shared with Neanderthals 60,000 to 100,000 years ago. According to John Hawks, an anthropologist and population geneticist at the University of Wisconsin-Madison, Neanderthals and Homo sapiens may well have interbred: “No primate species have established reproductive boundaries into sterility in less than a couple of million years. Neanderthals and ourselves ­resemble, maybe, chimps and bonobos, which are geographically separated in nature but hybridize freely if placed together in a zoo.” In short, though we tend to be species-centric about the concept of humanity, the reality is that all organisms are temporary receptacles into which DNA pours itself, and inter­species boundaries are more fluid and tenuous than we’ve thought. In a sense, the idea of Homo sapiens as a distinct species is one more racial myth.

Other assumptions don’t hold up any better. Not only did Cro-Magnons have larger brains than we do, for example, but the difference was big. “In the last 10,000 years, our brains have shrunk about 200 cubic centimeters,” Hawks explains. “If we shrunk another 200, we’d be the equivalent of Homo erectus. One possi­bility is this represents greater efficiency–our brains using less energy, needing less developmental time, and signaling faster. Alternatively, of course, we’re getting dumber.”

Pondering these and similar questions, Hawks and other researchers wondered if data from the International HapMap Project–a consortium established to catalogue the patterns of human genetic variation in different populations around the globe–could help clarify matters.

In population genetics, “linkage disequilibrium” means that certain alleles–the alternative versions of a given gene responsible for variations such as brown or blue eyes–occur together more frequently than can be explained by chance. It is a sign that evolutionary selection has been working: advantageous new mutations are appearing. Hawks and his colleagues applied novel genome-scanning approaches to HapMap data to track linkage disequilibrium and then, in December 2007, published a controversial paper, “Recent Acceleration of Human Adaptive Evolution,” in the Proceedings of the National Academy of Sciences.

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Credit: Bettmann/Corbis

Tagged: Biomedicine, computer modeling

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