Monday, November 24, 2008

How Complexity Evolves

[Slightly altered excerpt from an invited review on the evolution of (nervous system) complexity]

The evolution of complexity is an enduring and fundamental topic in biology. Recent research is allowing new insights into the origins of complexity. Namely, scientists now have access to the components of complex structures, and their evolutionary histories. "The eye" is no longer an anonymous collection of components - Darwin may have known an eye is composed of lens retina and nerve - but he did not know what lenses or retinas were composed of, nor did he know in much detail how they functioned. We now know many of the protein components of structures like eyes and how they function, and we know that these components have evolutionary histories. Since biological entities from genes to ecosystems arise from existing entities, general patterns emerge as to where those entities came from. They either duplicate/diverge; split/diverge; or fuse in new combinations.

What is biological complexity?
Numerous definitions have been suggested for biological complexity, from mathematical and information theoretic formulas [2,3] to intuitive definitions, such as the numbers of parts or components that can be counted in a system [4,5]. In practice, a researcher’s choice of definition for complexity often boils down to his ability to measure it. In investigator-defined computer simulations [2] or circumscribed biological systems [3], information theoretic definitions using explicit mathematical formulas are tractable. However, in extensive biological systems, especially those that encompass multiple levels of biological organization with varied properties, the relationship between structure and function (e.g. genotype and phenotype) is often largely unknown, and may itself be complicated and variable. These unknowns complicate the formulation of explicit, yet general, mathematical definitions of complexity for extensive biological systems. Instead, some have argued that counting the numbers of parts of a system is an appropriate measure of complexity [4]. Although often focused on structural units, such as cell types, genes, or species, and not on the functions of those units, McShea [5] has also argued that counting structural parts should often be a good estimate of functional complexity.
Herein, we follow previous authors [4,5] and define more complex systems as those that have more parts. “Part” is used as a term that spans levels of biological organization [4]. Species are parts of ecological communities. Organs (like brains or ganglia) are parts of species. Cell types (like neuronal types) are parts of organs and of species. Proteins are parts of cells and of networks, and domains and amino acids are parts of proteins. Many other biological units are also parts [6]. For the current discussion, we are concerned less with defining or counting parts, and concerned more with how new parts originate during evolution. According to the definition of complexity that we employ, new parts (that do not come at the expense of existing parts) increase biological complexity. Therefore, those mechanisms that cause the evolution of new parts are of particular interest because those are the mechanisms that cause increases in biology complexity.

"those mechanisms that cause the evolution of new parts are of particular interest because those are the mechanisms that cause increases in biology complexity."

General patterns of increased complexity
By definition, complex systems have many parts, and the histories of those parts are varied. As such, we cannot expect a simple, one dimensional answer to the question of how complexity evolved. Nevertheless, at all levels of biological organization, conceptually similar patterns (Figure 1) have resulted from a varied array of mechanisms that historically increased complexity.

Figure 1 - Generalized patterns of increased biological complexity. The top of the figure represents an ancestral state, the bottom a descendant state. Shapes represent “parts”, a generic term for a biological feature at any level of organization. Parts can be species, genes, protein domains, pathways, brain regions, and many other biological units [see 6]. A. Copying and divergence B. Fission and divergence C. Copying and fusion. Without copying or fission, complexity does not increase because divergence (or fusion) maintains the same number of parts. Without differential divergence or fusion of parts, complexity only increases marginally.

First, parts may exhibit a pattern consistent with differential divergence of copied elements (Fig. 1a). A prime example of a specific mechanism leading to this pattern is gene duplication plus divergence. Duplicated genes are initially identical, and they gradually diverge over time, increasing genomic complexity. Second, parts may exhibit a pattern consistent with differential divergence of split elements (Fig. 1b). Here, a prime example is speciation, where populations of individual organisms, originally all of the same species, split into multiple populations that diverge to the point of becoming separate species. Splitting (fission) can also occur in an asymmetric fashion (Fig 1c), generating two uncoupled parts that together would sum to one ancestral part. Third, parts may exhibit a pattern consistent with fusion of copied parts (Fig. 1d). For example, copied protein domains often join together to generate a new gene. Another example of fusion is expression of genes in new combinations, a process termed co-option [reviewed in 7]. A primary goal of this paper is to review cases in nervous system evolution that provide specific and more detailed mechanisms that account for these patterns at different levels of biological organization.

The patterns in figure 1 are produce by a number of different mechanisms, including gene duplication, alternative splicing, retrotransposition, co-option, etc.

[The specific mechanisms leading to the general patterns is the topic of the rest of the paper from which this excerpt is taken].

References Cited
1. Striedter GF: Principles of Brain Evolution. Sunderland, MA: Sinauer; 2005.

2. Adami C, Ofria C, Collier TC: Evolution of biological complexity. Proceedings of the National Academy of Sciences of the United States of America 2000, 97:4463-4468.
3. Adamowicz SJ, Purvis A, Wills MA: Increasing morphological complexity in multiple parallel lineages of the Crustacea. Proceedings of the National Academy of Sciences of the United States of America 2008, 105:4786-4791.
4. Bonner JT: The Evolution of Complexity. Princeton: Princeton University Press; 1988.
5. McShea DW: Functional complexity in organisms: Parts as proxies. Biology & Philosophy 2000, 15:641-668.
6. McShea DW, Venit EP: What is a part? In The Character Concept in Evolutionary Biology. Edited by Wagner GP: Academic Press; 2001:259-284.
7. True JR, Carroll SB: Gene co-option in physiological and morphological evolution. Annual Review of Cell and Developmental Biology 2002, 18:53-80.

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