Tag Archives: Tiktaalik

Does Behe’s “First Rule” Really Show that Evolutionary Biology Has a Big Problem?

Michael Behe has a new book coming out this month called Darwin Devolves. Nathan Lents, Joshua Swamidass, and I wrote a review of that book for the journal Science. (You can also find an open-access copy of our review here.) It provides an overview of the problems we see with his thesis and interpretations. As our review states, Behe points to many examples of evolution in which genes and their functions have been degraded, but he largely ignores the ways that evolution generates new functions and thereby produces complexity. That’s a severe problem because Behe uses the evidence for the ease of gene degradation to support his overarching implication that the current scientific understanding of the mechanisms of evolution is inadequate and, consequently, the field of evolutionary biology has a “big problem.”

I won’t attempt to summarize Behe’s entire book nor our short review, as people can read those for themselves if they want. Instead, I hope to accomplish three things in this post and two more that will follow. In this first post, I explain why Behe’s so-called “first rule of adaptive evolution” does not imply what he says it does about evolution writ large. In the second post, I’ll discuss whether my long-term evolution experiment (the LTEE for short) does or doesn’t provide strong support for Behe’s position in that regard. In my third post, I’ll explain why I think that Behe’s positions, taken as a whole, are scientifically untenable.

I. Behe’s “First Rule of Adaptive Evolution” Confounds Frequency and Importance

Behe’s latest book is centered around what he calls “The First Rule of Adaptive Evolution: Break or blunt any gene whose loss would increase the number of offspring.” As he wrote in an immediate, dismissive response to our review: “The rule summarizes the fact that the overwhelming tendency of random mutation is to degrade genes, and that very often is helpful. Thus natural selection itself acts as a powerful de-volutionary force, increasing helpful broken and degraded genes in the population.”

Let’s work through these two sentences, because they concisely express the thrust of Behe’s book. The first sentence regarding “the tendency of random mutation” is not too bad, though it is overly strong. I would tone it down as follows: “The tendency of random mutation is to degrade genes, and that is sometimes helpful.” My reasons for these subtle changes are that: (i) many mutations are selectively neutral or so weakly deleterious as to be effectively invisible to natural selection; (ii) while loss-of-function mutations are sometimes helpful to the organism, I wouldn’t say that’s “very often” the case (though it may be in some systems, as I’ll discuss in part II); and (iii) even those degradative mutations that are not helpful on their own sometimes persist and occasionally serve as “stepping stones” on the path toward new functionality. This last scenario is unlikely in any particular instance, but given the prevalence of degrading mutations it may nonetheless be important in evolution. (This scenario does not fit neatly within the old-fashioned caricature of Darwinian evolution as only proceeding by strictly adaptive mutations, but it is certainly part of modern evolutionary theory.)

Behe’s next sentence then asserts the power of the “de-evolutionary” process of gene degradation. This is an unjustifiable extrapolation, yet it is central to Behe’s latest book. (It’s not the sort of error I would expect from anyone who is deeply engaged in an earnest effort to understand evolutionary science and present it to the public.) Yes, natural selection sometimes increases the frequency of broken and degraded genes in populations. But when it comes to the power of natural selection, what is most frequent versus most important can be very different things. What is most important in evolution, and in many other contexts, depends on timescales and the cumulative magnitude of effects. As a familiar example, some rhinoviruses are the most frequent source of viral infections in our lives (hence the expression “common cold”), but infections by HIV or Ebola, while less common, are far more consequential.

Or consider an investor who bought stocks in 100 different companies 25 years ago, of which 80 have been losers. Ouch? Maybe not! A stock can’t lose more than the price that was paid for it, and so 20 winners can overcome 80 losers. Imagine if that investor had picked Apple, for example. That single stock has increased in value by well over 100-fold in that time, more than offsetting even 80 total wipeouts all by itself. (In fact, research on the stock market has shown the vast majority of long-term gains result from a small minority of companies that, like Apple, eventually become big winners.)

In the same vein, even if many more mutations destroy functions than produce new functions, the latter category has been far more consequential in the history of life. That is because a new function may enable a lineage to colonize a new habitat or realm, setting off what evolutionary biologists call an “adaptive radiation” that massively increases not only the numbers of organisms but, over time, the diversity of species and even higher taxa. As one example, consider Tiktaalik or some relative thereof, in any case a transitional kind of fish whose descendants colonized land and eventually gave rise to all of the terrestrial vertebrates—amphibian, reptiles, birds, and mammals. That lineage left far more eventual descendants (including ourselves), and was far more consequential for the history of life on Earth, than 100 other lineages that might have gained a transient advantage by degrading some gene and its function before eventually petering out.

Asteroid impacts aren’t common either, but the dinosaurs (among other groups) sure felt the impact of one at the end of the Cretaceous. (There remains some debate about the cause of that mass extinction event, but whatever the cause its consequences were huge.) Luckily for us, though, some early mammals survived. Evolution often leads to dead ends, sometimes as a consequence of exogenous events like asteroids, and other times because adaptations that are useful under a narrow set of conditions (such as those caused by mutations that break or degrade genes) prove vulnerable over time to even subtle changes in the environment. It has been estimated that more than 99% of all species that have ever existed are now extinct. Yet here we are, on a planet that is home to millions of diverse species whose genomes record the history of life.

Summing up, Behe is right that mutations that break or blunt a gene can be adaptive. And he’s right that, when such mutations are adaptive, they are easy to come by. But Behe is wrong when he implies these facts present a problem for evolutionary biology, because his thesis confuses frequencies over the short run with lasting impacts over the long haul of evolution.

[The picture below shows the Tiktaalik fossil discovered by Neil Shubin and colleagues.  It was posted on Wikipedia by Eduard Solà, and it is shown here under the indicated Creative Commons license.]




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Favorite Examples of Evolution

When the cold bites, When the review stings, When the news is sad, I simply remember these evolving things, And then I don’t feel so bad! — with apologies to Rodgers and Hammerstein

Over on Twitter, the biology students from George Jenkins High School in Lakeland, Florida, asked me and many others: “What’s your favorite example of evolution?”  There are so many fascinating examples that it’s hard for me to pick just one. So, here are half a dozen examples that are among my favorites.

  • The discovery by Neil Shubin and colleagues of Tiktaalik, an extinct fish (pictured below) from the Devonian that was poised to give rise to terrestrial vertebrates. You can read about this work in Shubin’s award-winning book, Your Inner Fish, which was also made into a PBS show.
  • The discovery by Svante Pääbo and colleagues of the Denisovans, an extinct lineage of humans, based on sequencing a complete genome from the finger bone of a girl who lived tens of thousands of years ago.
  • The analysis by Tami Lieberman, Roy Kishony, and colleagues of the genetic adaptation of an opportunistic species of bacteria to the lungs of patients with cystic fibrosis. I’ve blogged about that paper here.
  • Here’s one from the long-term experiment in my own lab — the evolution of the ability to use citrate that arose in just one of the 12 populations and after more than 30,000 generations. There are nice summaries of this work in Carl Zimmer’s blog here and here.
  • A study by Hod Lipson and Jordan Pollack on the evolution of robots. I remember hearing about this paper and being shocked: “Wait a second. Robots are expensive, and most things go extinct during evolution. How could they even afford do this?” I had to read the paper to realize they were evolving virtual robots in a physical simulation of the real world. They then built and tested the winners in the physical world. And indeed, the robots worked as they had evolved to do.
  • Applying the mechanisms of evolution to artificial systems is a fascinating approach useful for both biology and engineering. One of my favorite basic-science uses of this approach was a paper where we used digital organisms – computer programs that self-replicate, mutate, and compete for resources – to show how very complex functions could evolve if simpler functions were favored along the way. These simpler functions provided building blocks for the more complex functions, illustrating how evolution works by tinkering and borrowing already existing structures and functions and using them in new ways. Incidentally, this work involved collaboration between a computer scientist (Charles Ofria), a philosopher (Rob Pennock), a physicist (Chris Adami), and a biologist (me).

Readers: Please feel free to add your own favorite examples of evolution in the comments section below.

[The picture below shows the Tiktaalik fossil discovered by Neil Shubin and colleagues.  It was posted on Wikipedia by Eduard Solà, and it is shown here under the indicated Creative Commons license.] Tiktaalik


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