Abstract
Talk of a “genetic program” has become almost as common in cell and evolutionary biology as talk of “genetic information”. But what is a genetic program? I understand the claim that an organism’s genome contains a program to mean that its genes not only carry information about which proteins to make, but also about the conditions in which to make them. I argue that the program description, while accurate in some respects, is ultimately misleading and should be abandoned. After that, I sketch an alternative framework which is better suited to capturing the full informational nature of genes. This framework is centered on the notion of a signaling game, as originally developed by David Lewis, but expanded upon considerably by Brian Skyrms in more recent years. On the view I develop, genes turn out to be the producers and consumers of regulatory or developmental information, rather than entities encoding such information. This finding has consequences that link up with a broader debate in the philosophy of biology concerning inheritance systems. I take this to be one form of theoretical payoff that results from applying the signaling games framework to genes.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
To be sure, many different proposals have been offered through the years regarding what genes are. In this paper, I make the by no means uncommon assumption that a gene includes not only a protein-template but also the proximal DNA region adjacent to the protein-template, the protein-template's promoter region. On this view, genes are not merely coding stretches of DNA, but rather have “parts”. It is quite standard I think to now use the term ‘gene' to cover at least the protein-template and its promoter region. Here, for example, is the definition of ‘gene' cited by Pearson (2006) as having emerged from a recently held genetics symposium: “A locatable region of genomic sequence… which is associated with regulatory regions, transcribed regions and/or other functional sequence regions” (p. 401).
Subscripted ‘P's stand for proteins. I am here setting aside the complication that some protein-templates can give rise to several or more proteins due to alternative RNA splicing. Nothing hangs on this simplification.
There may be other ways of formulating the genetic program idea, however. One possibility, which I will not consider here, is that the “division of labor” we observe in the genome, with some genes encoding transcription factors and others encoding “worker proteins”, might warrant extending the stored program concept to the genome. The stored program concept is really a name for a particular kind of computational architecture in which both the data symbols and the instructions for manipulating the data symbols are explicitly represented for the machine and stored in the same memory mechanism. This proposal faces its own set of challenges, but my arguments in this paper should be understood as applying only to the formulation of the genetic program idea given above. The two are really quite different.
Something like this is true even of multi-threaded programs, whose parts may be executed in parallel by different processors. Although different parts of the program are executed in parallel, it's still the case that the instructions making up those parts are executed in a particular order, and that changing the order of the instructions in those parts would almost certainly alter the outcome of the entire process.
The promoter region of the Endo16 gene, for example, is about 2,300 base pairs.
Think w as in state of the world.
Although not in this simple game, there will often be intermediate cases between these two extremes (pure information vs. no information) where the probabilities of some states will be raised but none will go to 1. One way to gloss information content in such cases is to see it as the set of states left with a probability greater than 0. Matters grow more complicated when no state is left with probability 0. See Godfrey-Smith (2012a) for a discussion of these issues. Such details are not of immediate relevance for present purposes, however.
Earlier I said that there is an element of idealization to these hierarchies owing to the fact that regulation of gene expression often involves some post-transcriptional processes, e.g., allosteric changes to transcription factors. I don't think this fact undermines the present line of argument; if anything, it actually strengthens it in the majority of cases. Transcription factors that must be “activated” by signal-dependent changes to their shape by other enzymes, for example, serve to integrate two distinct sources of information, namely, the information initially carried by the inactive form of the factor (that the promoter of the gene coding for it is “activated”) and the additional information implied by the factor's assuming the modified form (that some other signal-dependent enzyme has made contact with it, say).
See Gallistel and King (2009) for a discussion of sub-cellular representation and computation.
References
Gallistel CR, King P (2009) Memory and the computational brain. Blackwell Publishing, Malden
Godfrey-Smith P (2000) Information, arbitrariness and selection: comments on Maynard Smith. Philos Sci 67(2):202–207
Godfrey-Smith P (2007) Innateness and genetic information. In: Carruthers P, Laurence S, Stich S (eds) The innate mind: foundations and the future. Oxford University Press, Oxford, pp 55–68
Godfrey-Smith P (2011) Senders, receivers, and genetic information. Biol Philos 26(2):177–181
Godfrey-Smith P (2012a) Signals: evolution, learning, and information, by Brian Skyrms. Mind 120:1288–1297
Godfrey-Smith P (2012b) Sender–receiver systems within and between organisms. Presented at PSA 2012, San Diego, as part of a symposium on “Signaling Within the Organism.” Available online: www.petergodfreysmith.com/SRWithinOrgs_PGS_PSA_2012_G.pdf
Hamilton WD (1964a) The genetical evolution of social behaviour. Part I. J Theor Biol 7:1–16
Hamilton WD (1964b) The genetical evolution of social behaviour: Part II. J Theor Biol 7:17–52
Istrail S, De-Leon S, Davison E (2007) The regulatory genome and the computer. Dev Biol 310:187–195
Jablonka E, Lamb MJ (2006) Evolution in four dimensions. MIT Press, Cambridge
Jablonka E, Lamb MJ (2007) Précis of evolution in four dimensions. Behav Brain Sci 30:353–392
Laudet L (2011) The origins and evolution of vertebrate metamorphosis. Curr Biol 21:726–737
Lewis D (1969) Convention: a philosophical study. Harvard University Press, Cambridge
Marcus G (2004) The birth of the mind. Basic Books, New York
Maynard Smith J, Szathmáry E (1995) The major transitions in evolution. Oxford University Press, Oxford
Pearson H (2006) Genetics: What is a gene? Nature 441:398–401
Shea N (2007) Representation in the genome and in other inheritance systems. Biol Philos 22:313–331
Shea N (2013) Inherited representations are read in development. Br J Philos Sci 64:1–31
Shea N (forthcoming) Two modes of transgenerational information transmission. In: Calcott B, Fraser B, Joyce R, Sterelny K (eds) Signaling, commitment, and emotion. MIT Press, Cambridge
Skyrms B (1996) Evolution of the social contract. Cambridge University Press, Cambridge
Skyrms B (2003) The stag hunt and the evolution of social structure. Cambridge University Press, Cambridge
Skyrms B (2009) Evolution of signaling systems with multiple senders and receivers. Phil Trans R Soc B 364:771–779
Skyrms B (2010) Signals: evolution, learning, & information. Oxford University Press, Oxford
Yuh C, Bolouri H, Davidson E (2001) Cis-regulatory logic in the endo 16 gene. Development 128:617–629
Acknowledgments
I am grateful to Peter Godfrey-Smith for discussion and comments on this work. I would also like to thank Kim Sterelny and two anonymous reviewers for helpful advice.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Planer, R.J. Replacement of the “genetic program” program. Biol Philos 29, 33–53 (2014). https://doi.org/10.1007/s10539-013-9388-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10539-013-9388-9