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Blog - hierarchical organization and biological evolution (part 2)

This page is a blog article in progress, written by Cameron Smith. To discuss this article while it’s being written, visit the Azimuth Forum.

An attempt to review some of the literature on major transitions in evolution and multi-level selection, sketch a few connections to concepts in category theory, and discuss the potential for using experimental evolution to investigate and strengthen those connections.

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If anyone should find my initially loose, metaphorical, intuition-first approach here frustrating, I would be honored to suggest this book to you:

I fully intend to use this approach to bootstrap these informal concepts toward formal ones, but I don’t want to start computing before I’m a little more confident.

Never make a calculation until you know the answer. -John Wheeler, Spacetime Physics

Nested and non-nested hierarchies

Even within the molecular level of biological systems, we observe a form of structural:


and functional:


hierarchical organization. I don’t think this distinction is necessarily worth making, but I’ll try to explain this point of view anyway. The first picture shows the physical structure of the genome. The structural hierarchy here from micro\rightarrowmacro is roughly DNA\rightarrowNucleosome\rightarrowChromatosome\rightarrow fibers of increasing size… (see the descriptions in the numbered bubbles). The second figure shows several of the components involved in the regulation of gene expression. A protein called a transcriptional regulator may bind to a particular type of DNA sequence called a promoter. If the regulator is of the activator type, once bound to the promoter it may recruit another type of protein called RNA polymerase to increase the rate of (or increase the probability of in a stochastic model) production of complementary RNA from the DNA template. However, the transcriptional activator may be prevented from accessing the promoter DNA if the DNA is tightly wound up around the proteins called histones. The enzymes that regulate the degree to which certain stretches of the DNA are condensed around histones are called histone modification enzymes. The process by which histone modification enzymes regulate gene expression is a form of epigenetic regulation (of which there are several other types). Thus, we see that here we have something that might be termed a functional hierarchy wherein the histone modification enzymes control the transcriptional activators, which in turn control gene expression.

There is a property that allegedly differs between these examples of structural and functional hierarchy. The structural hierarchy is nested (lower levels are physically contained within higher levels like Russian dolls)

whereas the functional one is apparently non-nested like the hierarchy of control in the military.

Now let me explain why I think this distinction between structural and functional could be misleading if not carefully interpreted. Presumably, the structure of the genome is itself functional, and the way in which I have presented genome organization and regulation has implied a potentially false dichotomy. I believe the description I have provided above is representative of what most biologists are taught. In the light of evolution the genome structure can be viewed as a functional hierarchy whose timescale of change is, on average, longer than that of the expression of individual genes. The tendency to impose a semantic distinction between structural and functional hierarchies, as I have recapitulated here, is, I suspect, simply a method of implicitly expressing relative timescales of stability. Nested hierarchies may evolve from non-nested hierarchies if the relatively transient interactions that constitute the non-nested hierarchy are stabilized via some selective process. If this occurs, however, a previously non-existant level emerges at which a non-nested hierarchy may come to exist. If this process were iterated, nested hierarchies emerging from non-nested ones and vice versa, it would bring into existence succesively higher levels: non-nestedn_n n=n+1\stackrel{n=n+1}{\leftrightarrow} nestedn_n. I owe this intuition, at least in part, to the exciting book of Andrée Ehresmann and Jean-Paul Vanbremeersch, which I first learned about here:

It’s sort of conventional to think of evolution as being lazy, kind of like certain programming languages for the computer scientists out there. So, if it is true that there has been some kind of ascent through levels of hierarchical organization, what might be the driving force? What I’m going to argue here and in the future is that it has to do with the relationship between organisms and their environments; what is perhaps another false dichotomy that I’m not sure yet how or whether it would be useful to dispose of.

The organism-environment duality

Population genetics is a branch of biology that takes as its mode of abstraction the proportions of particular genotypes within a given population. The lack of a coherent conceptualization of fitness, that both addresses most intuitive caveats and for which concrete examples can be devised, seems to me to be a significant impediment to population genetics theory. One reason for this is that any type of individual entity, no matter the hierarchical level on which it is perceived to exist, is composed of a network of traits that interact both among themselves (e.g. epistasis among genes) and with a dual network of factors that constitute said individual entity’s environment.

It might be useful to go further and abstract away the conceptual division between organism and environment altogether, in order to incorporate both into a single network, as I believe many theoretical ecologists would argue. But, if we are to maintain the conceptual organism-environment distinction, I think it will be necessary to incorporate models of the environment which are at least equally complex to that of the organism. As an example in this direction, the notion of a so-called fitness landscape as exhibited by the NK model

takes a step in the right direction. This model enables the explicit representation of a discrete fitness landscape where the value of the fitness metric associated to a particular location or node within the landscape is dependent upon contributions from KK other nodes of the landscape. KK is a parameter of the model. When KK is small we can imagine that nodes in the network provide relatively independent contributions to fitness whereas when KK gets larger the contribution of an individual node to the value of the fitness metric has a higher number of dependencies. If you’d like more detail, there’s a nice simple example on Wikipedia. From this point of view, the relationship between organism and environment is more like the frustration exhibited by spin glasses than a smooth climb up a fitness peak of a continuous fitness landscape. One example that has been studied directly in biology is that of host-parasite antagonistic coevolution, which I consider to be a specific case of the more general environment-organism antagonistic coevolution with environment and organism being analogous to host and parasite respectively. I would like to keep this point of view in mind as I consider the emergence of higher-ordered levels of organization in the so-called major transitions in evolution.

major transitions in evolution

Blog - hierarchical organization and biological evolution (part 2)

One of the first attempts to consider so-called major transitions in evolution comprehensively was Maynard Smith and Szathmary’s book:

One question about these hierarchical evolutionary transitions that I’m quite interested in is whether they have some things in common (possess any properties that are independent of scale).

, multi-level selection theory in particular,

Still putting together what I want to say about this…


Blog - hierarchical organization and biological evolution (part 2)

T. F. H. Allen and T. B. Starr, Hierarchy: Perspectives for Ecological Complexity. Chicago: University of Chicago Press, 1982, p. 326. \hookleftarrow

A. J. Arnold and K. Fristrup, The theory of evolution by natural selection: a hierarchical expansion, Paleobiology, vol. 8, no. 2, pp. 113–129, 1982. \hookleftarrow

A. C. Ehresmann and J. P. Vanbremeersch, Memory Evolutive Systems; Hierarchy, Emergence, Cognition, Volume 4 (Studies in Multidisciplinarity). Elsevier Science, 2007, p. 402. \hookleftarrow

G. L. Farre, The Energetic Structure of Observation: A Philosophical Disquisition, American Behavioral Scientist, vol. 40, no. 6, pp. 717-728, May. 1997. \hookleftarrow

S. A. Frank, George Price’s contributions to evolutionary genetics., Journal of theoretical biology, vol. 175, no. 3, pp. 373-88, Aug. 1995. 1\hookleftarrow^1 2\hookleftarrow^2

S. A. Frank, Foundations of social evolution. Princeton Univ Press, 1998. \hookleftarrow

S. Okasha, Evolution and the levels of selection. New York: Oxford University Press, USA, 2006. \hookleftarrow

G. R. Price, Selection and Covariance, Nature, vol. 227, no. 5257, pp. 520-521, Aug. 1970. \hookleftarrow

G. R. Price, Extension of covariance selection mathematics, Annals of Human Genetics, vol. 35, no. 4, pp. 485-490, Apr. 1972. \hookleftarrow

G. R. Price, The nature of selection, Journal of Theoretical Biology, vol. 175, no. 3, pp. 389-396, Aug. 1995. (written ca. 1971 and published posthumously) \hookleftarrow

H. A. Simon, The architecture of complexity, Proceedings of the American Philosophical Society, vol. 106, no. 6, pp. 467–482, 1962. 1\hookleftarrow^1 2\hookleftarrow^2

H. A. Simon, Near decomposability and the speed of evolution, Industrial and Corporate Change, vol. 11, no. 3, pp. 587-599, Jun. 2002. 1\hookleftarrow^1 2\hookleftarrow^2 3\hookleftarrow^3

J. Maynard Smith and E. Szathmáry, The major transitions in evolution. New York: Oxford University Press, USA, 1995. \hookleftarrow

Blog - hierarchical organization and biological evolution (part 2)

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