So it should be clear how important genetic analysis is for reconstructing evolutionary trees. Yet it has not always been so clear. When Zuckerkandl and Pauling wrote, half a century ago, that hemoglobin offered a good basis for comparing humans to gorillas, prominent biologist Gaylord Simpson shot them down in impressive fashion, saying that their proposal was nonsense. Now today, Simpson lies on the wrong side of history, but at the time, perhaps Zuckerkandl and Pauling were the radicals. Since that time, genetic analysis has been applied to answer a huge number of biological questions related to evolutionary tree reconstruction. For example, until the 1980s, it was unclear whether the giant panda should be classified as a bear or as a RACCOON (not marsupial). The giant panda looks like a bear in some ways, but it's also similar to raccoons in other ways. The panda doesn't hibernate in the winter, and its male genitalia are tiny and backward-pointing. I'm going to let you insert your own joke on that one. In 1938, Edwin Colbert wrote, "so the quest has stood for many years with the bear proponents, and the raccoon adherents, and the middle of the road group advancing their several arguments with the clearest of logic. While in the meantime, the giant panda lives serenely in the mountains of Sichuan with never a thought about the zoological controversies he is causing by just being himself." Now, whereas using anatomical or behavioral characters led to endless debate in this subject, Steve O'Brien used genetic data in 1985 to demonstrate that the giant panda should, in fact, be considered a bear - a conclusion that has lasted to this day. We can also turn genetic analysis inward onto ourselves, and construct an evolutionary tree for human populations. When we look at this tree, we see a very clear division into Africans, shown in red, and non-Africans, shown in other colors, where each color represents a different continent. But we also see that the most recent common ancestor of all non-Africans is at a much more recent point than the most recent common ancestor of all Africans, which is at the root of the tree. In 1987 Rebecca Cann, Mark Stoneking and Allan Wilson deduced from this information that because the origin of modern humans predates the origin of all non Africans, all non-Africans must have originated somewhere in Africa. This became known as the out-of-Africa hypothesis. And although it is still the subject of some debate, it has become widely accepted today. As more genotyping data has been obtained, researchers have been able to infer human migrations around the world from evolutionary trees. Yet this is not to say that genetic data immediately is able to answer all of our questions. One problem arises when different genetic data sets yield differing phylogenies. For example, using the dopamine D4 receptor gene suggested that chimpanzees were closer to gorillas than they were to humans. On the other hand, if we used the beta-globin gene, that suggested that chimpanzees were closer to humans than they were to gorillas. Not until 1996 did enough genetic data become available to conclude that the phylogeny on the right is most likely the correct one. Even at the beginning of this century, many biologists believed that humans are more closely related to dogs than humans are related to mice. This seems reasonable, since we seem to be more similar to dogs than mice at first glance. But recent research has shown otherwise, as indicated by this phylogeny. Finally, evolutionary trees constructed from genetic analysis have even been used as evidence in criminal trials. A landmark instance of this occurred in 1998, when a doctor in Louisiana went on trial for the attempted murder of his estranged mistress. She claimed that he had injected her with an HIV-tainted syringe. After the police chief collected HIV samples from around the area, researchers constructed an evolutionary tree for these samples. And what they found was that the HIV samples from the victim, shown here in blue, were similar to samples taken from one of the doctor's patients, shown in red. This evidence supports conviction, which was the eventual verdict. But this evolutionary tree taken by itself is far from conclusive, which is what brings us to the challenge problem for this chapter. The evolutionary tree that we constructed on the previous slide was constructed based on an alignment of just one HIV protein. What happens when you construct alignments for other HIV proteins? Do they all support conviction? Or do some of these other proteins paint a murkier picture? So I will let you go and work on implementing the algorithms for evolutionary tree construction that we have encountered in this chapter. I want to say thank you for joining me on this journey. I can only hope that this chapter has been as enjoyable for you as it has been for me.
