The third force of evolution is mutation. There are a lot of platitudes and details about mutation that we just don’t need to care about. One of my favorites is that (genetic) mutation is both the weakest and strongest evolutionary force. Weakest because at least genetic mutations occur at a very low rate, and have a much smaller influence on gene frequency than other forces; strongest because it is ultimately the source of all heritable variation. Others include things like Fisher’s geometric model that says that beneficial mutations tend to be small, and that most mutations are neutral or deleterious. The details are things like the various types of mutations we recognize – insertion, deletion, point mutations etc. As far as the phenotypic view goes, to quote Rhett Butler “Frankly, my dear, I don’t give a damn.”
That is not quite true. There is one rumor I have heard that, and I emphasize I don’t know if this is true, apparently most of the major Drosophila mutations that Morgan and his students identified were transposable element insertions and deletions, basically with the transposon inserted you get the mutant non-functional form, and with the transposon absent you have the functional gene, or vice versa. I love this because in traditional population genetics there are two ways of modeling mutations. One is the two-allele model with reversible mutations:
which seems to fit remarkably well to the transposable element model of mutations. The other is the “infinite alleles” model, which would seem to fit well with the “point mutations” that we learned about in introductory genetics.
If you are unfamiliar with these equation, μ and ν are mutation rates, and the second equation is the standard drift equation found in any population genetics text multiplied by the probability that neither gene being compared is mutant. I love that with all our new-found knowledge, our original models of mutation, developed before the discovery of DNA were essentially solid models to which modern discoveries have added little beyond validating their basic utility. But, you say, what about all of the deep structure of the genome, the fact that most mutations are in regulatory regions yadda yadda yadda? This is where Rhett Butler comes in. From the phenotypic perspective these facts are fascinating, and important to know, but honestly they are better classified as gene physiology than evolutionary biology. As an analogy, consider a scientist studying the ecology of some animal, say a rabbit. They need to know that the rabbit has organs, such as a heart, and that the heart functions, but they do not need to know the details of how it functions. In contrast a physiologist might care very much how a heart functions, but very little about how that heart helps rabbits avoid predators. It is much the same for evolutionists: They need to know that mutations occur, and that the mechanism for generating them exists, but other than that they generally will care very little about the details. In contrast, the gene physiologist may care very much about the mechanisms that cause mutations, but care very little about what that does to phenotypic variation in a population.
This is not to say that the molecular knowledge of mutations has been without value. Consider Dollo’s law (Dollo, L. 1893. Bulletin de la Société Belge de Géologie de Paléontologie & D’Hydrologie 7:164-166) in which he states that “An organism is unable to return, even partially, to a previous stage already realized in the ranks of its ancestors.” In more recent restatements this has been interpreted to mean that a trait, once lost, can never be re-evolved in its ancestral form. Thus, fish have dorsal fins, but when whales re-evolved them they are a new evolution with significant differences. That is, once the dorsal fin of fishes was lost it was lost forever, and when whales returned to the sea they had to re-evolve them. This is a nice idea, and often, as in the case of whales, appears to be true, but there have since been several good examples of apparent reversals. This ability to re-generate lost traits actually makes sense now that we know that most mutations are in regulatory regions. That is, it is reasonable to presume that regulatory mutations simply “turn off” the trait. It is then presumably possible to turn it back on by evolving a new regulatory pathway. As a caveat: There are almost certainly limits on this because the unexpressed gene would be insulated from selection, and presumably eventually be destroyed by mutations that are neutral as long as the gene is not expressed.
Since I seem to have about used up my allotment this week talking about genetics, I will mention one of the more delightful graphs I have seen in recent years:
I see two things that interest me. First, remember all that energy you spent learning the triplicate code in genetics class? Well it explains 2% of the genome. 98% pays no attention to it. I am not sure what to make of that, except perhaps that there sure is a lot we don’t know about the genome, and that the McDonald/Kreitman test (McDonald and Kreitman 1991. Nature 351: 652-654), and other tests that depend on comparing synonymous and non-synonymous mutations don’t work for 98% of the genome. The other thing I find fascinating is that LINEs, SINEs, and various transposons account for over 40% of the genome. As far as we know these are mostly dead viruses and active or inactive transposable elements, or in other words junk and parasitic DNA. Its not particularly relevant to a discussion of mutations, but it still amazes me.
So, to bring this full circle, from a phenotypic perspective we really don’t care very much about mechanisms of mutations, although there are a number of examples where knowledge of mechanism helped our understanding of the effect of genetic mutations on the phenotype. However, it is really a good thing that we don’t need to know much about the mechanism, because even at this point there is little we do know about the genome and the effects of mutations. After all, the paradigmatic studies of DNA and the discovery of the triplicate code still leaves us with 98% of the genome that we really don’t understand. Thus the bottom line is that there is a lot we don’t know about mutations, and that is ok because in general we don’t need to know most of it.