A phenotypic view of evolution Evolution in Structured Populations

Sewall Wright’s Seven Generalizations about Populations

Once again I seem to be reorganizing my plan of attack, and this will be a big one. I think it would be entertaining to move over to a discussion of Wright’s shifting balance theory. This is not a minor topic, and indeed, I am told that the two longest papers ever published in Evolution were on this topic (Coyne Barton and Turelli 1997, Evolution 51;643-671; Wade and Goodnight 1998, Evolution 52:1537-1548; see also Coyne Barton and Turelli 2000, Evolution 54:306-317; Goodnight and Wade 2000, Evolution 54:317-324 – FYI there is a hidden message in Goodnight and Wade. Write down the first letter of each paragraph).

It is surprising I haven’t talked much about Wright up to this point. He is one of my heroes, and one of the first luminaries of evolutionary biology I ever met—ok, lying there a bit. I was at the University of Chicago when Wade, Lande, Arnold, Teeri, and later Schemske were all starting out, but they really don’t count because none of them had tenure when I first met them. . .


One of the classic pictures of Sewall Wright while he was at the University of Chicago.

One of the fascinating things about Wright is that, unlike Fisher, he was an experimentalist, rather than a pure theoretician. The problem with doing experiments, of course, is that they are messy and rarely fit into the simple schemes that we develop for our models. Wright, as is often noted, and as is obvious from his books, bred a lot of guinea pigs and carefully examined the genetics of their coat colors and patterns.

guinea pigs

Guinea pigs come in a wide array of colors and patterns (http://emmasguineapigs.blogspot.com/p/cavy-colours.html).

Wright development fig

Wright’s view of developmental genetics.  (Wright 1968: Evolution and the Genetics of Populations, Vol. 1)

This is a situation we have seen before. True experimentalists are confronted with complexity that theoreticians are inclined to ignore. The difference is that Wright was genius, and both a good experimentalist and a brilliant theoretician, putting him the position of being both aware of this complexity, and having the mathematical skills to actually do something with it.

I actually think that there is another piece of history that may have been realized by Crow (Crow 1998 Genetics 148:923-928), but has generally been ignored. Wright received his Ph.D. in 1915 under the direction of William Castle, first at the University of Illinois, and ending at Harvard. Parallel to this, Shull began his work on corn genetics at the University of Illinois in 1905 (and coined the term heterosis in 1914), and East was similarly working on corn genetics at the Connecticut State Agricultural College. What is important here is that Connecticut State is where the Harvard scientists went during the summer both because it was cooler, and there was more land for field experiments. This was the time when the concepts of inbreeding and hybridization and the “magic” of hybrid corn was first being discovered. Importantly, this was also the time and place where Wright was a graduate student, and my guess is that he would have been interacting with the corn breeders on a more of less daily basis. Thus, it is interesting to speculate that the development of hybrid corn gave us not only hybrid corn, but also the shifting balance theory.

In any case, whether guinea pigs or corn or both Wright came up with a set of seven generalizations about populations. In his own words (Wright 1968: Evolution and the Genetics of Populations, Vol. 1)

“There are a number of broad generalizations that follow from this netlike relationship between genome and complex characters. These are all fairly obvious but it may be well to state them explicitly.

(1)   The variations of most characters are affected by a great many loci (the multifactor hypothesis).

(2)  In general, each gene replacement has effects on many characters (the principle of universal pleiotropy)

(3)  each of the innumerable possible alleles at any locus has a unique array of differential effects on taking account of pleiotropy (uniqueness of alleles)

(4)  The dominance relation of two alleles is not an attribute of them but of the whole genome and the environment. Dominance may differ for each pleiotropic effect and is in general easily modifiable (relativity of dominance).

(5)  The effects of multiple loci on a character in general involve much nonadditive interaction (universality of interaction effects)

(6)  Both ontogenetic and phylogenetic homology depend on calling into play similar chains of gene-controlled reactions under similar developmental conditions (homology)

(7)  The contributions of measurable characters to overall selective value usually involve interaction effects of the most extreme sort because of the usually intermediate position of the optimum grade, a situation that implies the existence of innumerable different selective peaks (multiple selective peaks).”

This is the genetics that Wright envisioned. It was a world in which all traits are determined by a large number of loci (multifactor hypothesis), and each of those loci affected a large number of traits (universal pleiotropy) and interacted intensively with each other (universal interaction effects).   The conclusion from this is that there are multiple ways to achieve high fitness (multiple selective peaks). What I find remarkable about this is that this theory was laid out in 1931 (Wright 1931, Genetics 16: 97-159), and yet it is clearly the outline of a complex system model, even down to using the words like “netlike relationship”, and “complex characters”. Basically, this model was developed before computers, before DNA, and really before we knew anything about genes other than that they behaved in a Mendelian fashion. In contrast, complexity theory, being generous, traces back to the 1940s at the earliest (http://www.ralph-abraham.org/articles/MS%23108.Complex/complex.pdf).

Wright was interested in how evolution could occur in this complex system (in both the formal and informal sense) he was envisioning. His world was very different from Fishers. The big difference is that the genetic complexity he was embracing, and his belief that species tended to be divided into small semi-isolated demes (more on that on another day), resulted in his seventh generalization, that there were multiple selective peaks. In contrast, Fisher thought that migration rates were generally large enough that the species could be considered approximately a single random mating population. In this situation, regardless of the amount of gene interaction, there will be only a single adaptive peak. Thus, the big difference between their world views was whether we could model evolution as a single fitness peak (Fisher), or whether we needed to model it as multiple fitness peaks (Wright).

Adaptive Landscapes

Adaptive landscapes.  Top:  Fisher’s world view  implies a simple fitness landscape with a single adaptive peak.  No matter where it starts on the landscape with only mutation and selection a population will eventually evolve to the top of the peak.  Bottom:  Wright’s world view explicitly incorporates a complex landscape multiple adaptive peaks.  In this landscape with only mutation and selection a population will always climb the nearest peak whether or not it is the “optimal” solution.  Once on a local adaptive peak the population will be stuck there. (image taken from http://www.terrorismanalysts.com/pt/index.php/pot/article/view/30/html)

In Wright’s view Fisher’s model, in which mutation and recombination generated variation and selection sorted out the good alleles from the bad ones, was simply not adequate to describe how evolution would occur on these complex landscapes. Thus, we can imagine his goal was to describe how evolution actually did occur on this complex landscape.

Wright’s model, as I have emphasized, was published in the 1930s. A lot has changed in the last 80 plus years. In subsequent posts I will describe Wright’s shifting balance process, but not from the historical perspective of what Wright envisioned, rather from my perspective in 2014 embracing my (obviously insufficient) knowledge of modern biology. I hope people will chime in when I have missed things or gotten things wrong.



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  1. (1) Getting stuck is me. And I was specifically referring to a theory based on large population size. It was a bit of historical hyperbole. I think that Wright would have agreed with that statement. These days I am not so sure, now that you mention it.

    (2) Yes there are other ways of crossing landscapes. I think it is important to recognize that Wright’s model is 80 years old. I would be very surprised if he had gotten it completely right on his first try 80 years ago. Thus for example, Gavrilets’ holey landscape (which as you know has its own problems) provides an alternative to valley crossing. Also peak shifts can potentially occur in very large population sizes based on the occurrence of rare events. I actually wrote a commentary on that once.

    (3) Funny story about Wright. When I was a first year graduate student I went to Madison for a symposium that my adviser (Wade) was participating in. I wandered in and sat next to this old guy, and he told me the seat was taken, so I moved over a few seats. Then this really old guy sat down where I had been sitting. I introduced myself. Turns out the old guy was Jim Crow, and the really old guy was Sewall Wright. We ended up going out to lunch together.

    (4) Ignore the wii. We finished the message before we finished the paper.

  2. “Once on a local adaptive peak the population will be stuck there.”

    Your words or Wright’s?

    Whether the population gets stuck depends on mutation rate and population size, and on the detailed structure of the fitness landscape around that peak. As for SBT, demes are definitely not needed to cross valleys in static landscapes, and Turelli pointed out to me that there is no evidence to show that populations actually ever evolve according to SBT.

    P.S. Did you meet Wright while in Chicago?

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