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In a seeming attempt to do for the study of genetics what Edelman did for neuroscience (see my earlier reviews of Neural Darwinism (1990), and Edelman & Tononi (2000)), Sansom's thesis in Ingenious Genes argues that multiple transcription factors combine to regulate 'simple genes', acting in a qualitatively consistent way – similar to that which auto-regulates the brain's neural networks according to functional efficiency. The emphasis throughout his current thinking, is thus placed upon the most ontological features of an individual organism (person's) organic, adaptive, complexity. As such, Sansom proposes that such insight be gained from one's observing gene regulation networks as the "controller of development", the ingenuity of genes (hence the volume's title) being explained by the way(s) in which gene regulation networks evolve to control development.
Following a brief yet informative introductory and historical review of evolutionary thinking re the mechanisms of heredity (from the orthogenesis of Erasmus Darwin and Lamark, through Mendel, Bateson and Fisher (the latter forming the basis of evolutionary population genetics), to Dawkins), Sansom attempts to then take his reader "one step beyond the evolution of genes towards the evolution of organisms by offering a general theory of the first level of development beyond the gene: gene regulation networks" (p.18). As the arch nemesis of his own theory, Sansom spends the majority of the first half of the book discussing the shortcomings of Stuart Kauffman's (1985, 1995) claim that natural selection cannot effectively design the regulatory connections between genes, whist also denigrating the details of Kauffman's model for its lack of system dynamic sensitivity (reliant as at is upon its purely discrete Boolean expressionisms, and low-K nodal inclusion), and lack of empirical case defense support. Much of this criticism is valid and agreeable as stated, but by so doing, Sansom is setting up his reader (and indeed the field as a whole) for great expectations in awaiting his alternative view. The question thus arises as to whether his 'new view' will now inform us about the detail of the 'distribution of adaptivity of gene regulatory relationships' which are to be thought so critically important? (and missing from Kauffman's account), together with an eagerness to learn what form Sansom's own empirical evidence for his alternative explanation will take ? With respect to the development of organisms, either the connections themselves are not particularly important, but some other emergent property(ies) of gene regulation is/are (as Kauffman believes), or, the connections themselves are important and gene regulation is a source of random noise in development.
Given Ransom's acceptance of an estimated 5-15 transcription factors for each gene (~1800 of the human genome's 20k-25k now thought to be transcription factors), the cycles of such qualitatively consistent 'balanced' networks are sufficiently long that they affectively exhibit "no order at all" (if individual cell activity cycles show gene switching on the order of 1-10 minutes, and thus operate within the range of 5-50 hrs, for several hundreds of potential final attractor states). Again rejecting Kauffman's view that the order of gene regulation has at its focus the order of repeated cycling through an attractor, Ransom argues instead that any given cell will show an activity consistent with its adaptively responding to changes in their microenvironment – this observation providing the crux of his central selective pressure for the systems' inherent 'evolvability'.
The latter half of the book presents Ransom's alternative model, a connectionist view of gene regulation networks, which is proposed to explain the adaptive reactivity of gene expression of a cell to its microenvironment. In this sense, it is 'gene regulation networks' (and not individual genes) which are the controllers of development, and as such, are instantiated in what Ransom calls "design control" (p.98), which includes the historical properties of the control system's component parts. Ransom's view is unusual in that it concentrates upon the small networks of transcription factors that directly regulates a particular structural gene (i.e., any gene that does NOT produce a transcription factor),.... However, its 'accuracy' is about the transcription factor regulation network itself, also! The true value of this connectionist model, although intrinsically appealing to this reviewer, remain to be empirically demonstrated (sight of at least some testable known transcription gene/cellular network emulations if not simulations would have been welcome), and in this sense are also wonting in the same regard the author himself attacks the feasibility of Kauffman's model. A further caution missing from the text, is any discussion of the difference in kind (if not real substrate) in the component parts included in neural network models of connectionism (together with its back-propagation of recurrent collaterals), when characterizing gene network activities in the same way. Indeed, having dismissed Maynard-Smith's (1993) view as suggesting that "gene's only carry information" (here the author is looking for 'knowledge' instead ?), Ransom is perhaps ignoring the significant difference between the functional output of genetic regulation network activity (3-D protein synthesis), and neuronal network activity (chemical and electrical signal release at the synapse) – an even newer, and possibly more revolutionary theory still being required to truly explain the functional, adaptive mechanisms active in the ontological development of biologically complex evolving systems.
Whether 'Ingenious Genes' will attract new readers to this still open field of enquiry, or persuade its opponents to shift models, only time will tell. But for now, it is good that the main thesis (if not it's empirically-determined biological support) is set out in a single monograph, its rationale and agenda clearly stated (and dated) for both computational and wetware researchers in the lab to now test and verify. Waddington's questions with regards the auto-regulatory control of organic development along each individual's ontogenetic landscape, however, remain to be answered, this volume setting out another novel and putative focus for exploration. In his attempt to determine a gene's 'gene expression profile' (i.e. the when, whether, how and why a gene may or may not be expressed), Ransom does not fully answer this question, but his focus of attention may yet be proven correct. Although we cannot at present 'know' whether gene regulation networks (and not genes) are really the controller of development, we have every reason to believe that they ARE at least phylogenetically evolved by natural selection, involved in the earliest stages of development, and continue to be crucial throughout ontological development – the minimum trilogy of inclusive factors for candidate inclusion. A must read for all interested in the physical nature of what is nurtured.
© 2013 Tony Dickinson
Tony Dickinson, Beijing Genomics Institute (BGI, China). December, 2012.