"Mutation Space"- A Potential Litmus Test

From the site:

http://www.ics.uci.edu/~aasuncio/idesign.htm

"Tuesday, April 04, 2006
Biological Interdependency and Mutation Space

Any software engineer can tell you that modularity is an essential characteristic of any program that must be actively developed, or even just maintained. Without modularity, any small change to one piece is liable to break a completely different piece in unpredictable ways. Adding a new feature to an unmodular system is difficult because it requires making many simultaneous changes to various pieces of a program that have no obvious relationship to each other or to the feature being added.

The same thing is true with Biology. In fact, it isn't controversial that the more complex an organism becomes, the less likely it is to evolve novel function, largely because of the intricate dependencies that must be maintained. What hasn't been attempted, so far as I know, is a quantification of approximately how much room an organism has in which to evolve – call this "mutation space" – as a function of its interdependecy complexity. In other words, how much functionality could be added/edited without requiring an unrealistic number of simultaneous compensatory changes elsewhere?

If it could be shown that any reasonably complex lower organism did not have room in its mutation space for the sort of evolution required to produce higher organisms (that is, any introduction of novel function would require an unrealistic amount of compensatory mutations to get off the ground), it would provide incredibly strong evidence for ID.

I'm not sure exactly how to quantify interdependency complexity and mutation space, but it seems like there ought to be a way to do it. Suggestions and/or reasons why this is a nutty idea that will never work are welcome."

[Bradford]: I'm not sure either. It looks like a complex undertaking. This is interesting in that at either extreme (life's origins or a highly complex organism) the generation of a novel biological system looks like a daunting prospect. At the point of origins the difficulty lies in generating a genetic structure with minimal function. No easy undertaking given the fact that maintenance functions such as the detection of genetic errors and their repair are found even in prokaryotic organisms. The inference that intolerable genomic corruption is inevitable in the absence of such functions is reasonable. In addition the encoded end products of DNA (proteins and RNA) are an integral part of the translation process and other encoded end products have vital roles in maintaining necessary cellular homeostasis. Yet faith in abiogenesis lives on.

The problem at the other extreme is of a different nature. As the author points out (my comments added in parenthesis): "Adding a new feature to an unmodular system (new function to a biological system) is difficult because it requires making many simultaneous changes (can require genetic changes affecting numerous interacting proteins) to various pieces of a program that have no obvious relationship to each other or to the feature being added" (or in the case of new biological systems indicate no intermediate pathways that are not the product of much imagination). The author's point is most clearly in evidence during prenatal development. Organisms develop in accordance with a tightly sequenced cascade of genetic instructions. Natural disruptions of them are evidenced in the form of birth defects.

Software engineers would be frustrated no end with the necessity of ignoring modularity in favor of always having to make a series of slight modifications of existing code to get from one objective to another. Engineers designing new vehicles want the freedom to eliminate and replace systems rather than having to modify only existing parts. There is a recognition that the degree to which change is limited by the necessity to alter existing parts also limits the viability and range of possible change. The interdependency and functional sequence relationship of parts determines the range of possible change. The capacity to generate biological change is not an exception to this principle.

The author's proposal to determine structural inhibitions to change by quantifying "interdependency complexity and mutation space" offers not only a means to evaluate the likelihood that novel biological functions evolve, it offers a measuring rod to determine limitations to change. ID has been criticized for lacking a mechanism for change and a predictive capacity. The mechanism in this case is the very same one cited by ID opponents. The prediction is that existing systems inhibit the type of changes required by an evolutionary paradigm. Evidence is found in hox genes. That entails a series of blog entries to come.