Coyne vs. Shapiro

Jim Shapiro has been outlining his views on evolution over at the Huffington Post, including a posting entitled, What Is the Key to a Realistic Theory of Evolution?

Not surprisingly, Jerry Coyne does not like it and weighs in with a posting entitled, A colleague wrongfully disses modern evolutionary theory.

Let me focus on a key point of their disagreement.

No rest for the SRP

Earlier in the summer, I pointed to a study that shows evidence of genome reformatting during human evolution:

In new research the Leeds team reports that a protein known as REST plays a central role in switching specific genes on and off, thereby determining how specific traits develop in offspring.

The study shows that REST controls the process by which proteins are made, following the instructions encoded in genes. It also reveals that while REST regulates a core set of genes in all vertebrates, it has also evolved to work with a greater number of genes specific to mammals, in particular in the brain – potentially playing a leading role in the evolution of our intelligence.

[…]

Says lead researcher Dr Ian Wood of the University’s Faculty of Biological Sciences: “This is the first study of the human genome to look at REST in such detail and compare the specific genes it regulates in different species. We’ve found that it works by binding to specific genetic sequences and repressing or enhancing the expression of genes associated with these sequences.

“Scientists have believed for many years that differences in the way genes are expressed into functional proteins is what differentiates one species from another and drives evolutionary change – but no-one has been able to prove it until now.”

– Here

Natural Genetic Engineering

Shapiro next turns his attention to the role of natural genetic engineering in evolution:

All the preceding whole-genome sequence discoveries implicate cut-and-paste type DNA rearrangements as basic evolutionary processes. What do we know about the capacity of cells to carry out such natural genetic engineering? An important clue is the discovery that our own genomes are at least 43% composed of DNA segments that can transpose from one location to another (International Human Genome Consortium, 2001). Two classes of transposable or mobile genetic elements have been recognized from the work of Barbara McClintock and her molecular followers (McClintock, 1987; Bukhari et al., 1977; Shapiro, 1983; Berg and Howe, 1989; Craig et al., 2002; Deininger et al., 2003): DNA transposons move exclusively at the level of DNA molecules while retrotransposons and other retroelements move by means of an RNA intermediate that can be reverse-transcribed into genomic DNA (Coffin et al., 1997; Kazazian, 2000).

Cellular Computation

Shapiro next turns his attention to the manner in which the genome interacts with the rest of the cell to carry out computations. He uses the classic example of the lac operon to draw out several general principles:

• Weak interactions, specific binding and cooperativity are essential aspects of molecular computations in cells.

• Repetition in DNA and proteins means that specific logical operations arise through combinations of basic circuit elements (e.g. complex regulatory regions in
• DNA, intra- and intermolecular interactions between protein domains).

• Allostery, the fact that binding of one ligand affects binding a distinct ligand, confers communication and processing capabilities on individual molecules so that cellular network nodes act as complex microprocessors.

• Layering of weak and bfuzzyQ interactions provides overall sharpness to integrated cellular responses (i.e.cells operate by Fuzzy Logic principles; Zadeh, 1975).

• Cells use chemical symbols to represent physiological information.

• No separation exists between control molecules and execution molecules, telling us we cannot apply Cartesian dualism models to the E. coli cell, or any other cell.

• Participation of DNA directly in formation of repression and transcription nucleoprotein complexes suggests that it may also not be useful to apply Turing’s concepts of separate “machine” and “tape” (Turing, 1950) to cellular computations.

Genomes and Systems Architecture

In order to better appreciate the teleological echoes of some recent research on the REST protein and its blinding sites, let’s first take some time to summarize the main points from James Shapiro’s review paper, “A 21st century view of evolution: genome system architecture, repetitive DNA, and natural genetic engineering” (Gene 345 (2005) 91–100).

Shapiro begins by outlining the perspective of “DNA as a data storage medium” and then an informatic metaphor that explores the genome:

Our current understanding of how coding sequence expression (data file access) and all these other processes operate is based upon the definition of cis-acting signals as part of the operon and replicon theories in the early 1960s (Jacob and Monod, 1961; Jacob et al., 1963). These cisacting signals are fundamentally different from any classical definition of a gene. They serve to format coding sequences and genome architecture in the same way that generic bit strings format the encoded information in electronic data storage media and guide the computational hardware to the right data files and indicate the appropriate routines to apply. Cis-acting signals in the genome similarly direct cellular hardware to form functional nucleoprotein complexes to carry out tasks such as transcription, replication, DNA distribution to daughter cells, and homology-dependent and homology-independent recombination (Shapiro, 2002a). Since they are generic and work at many locations, cis-acting signals belong to the repetitive component of the genome (Shapiro and Sternberg, 2005).

By applying an informatic perspective, we can appreciate the functional relevance and interconnections of genome features which have proved difficult to understand within the linear conceptual framework of classical genetics. Extending the informatic metaphor, it is possible to argue that genomes each have a characteric “system architecture,” in much the same way that different computer systems do (Shapiro, 1999; Shapiro and Sternberg, 2005).