[Frontiers in Bioscience 14, 2959-2969, January 1, 2009]

The GS (genetic selection) Principle

David L. Abel

The Gene Emergence Project, The Origin-of-Life Foundation, Inc., 113 Hedgewood Dr. Greenbelt, MD 20770-1610 USA


1. Abstract
2. Introduction
3. Where selection must occur
4. The requirements of selection
5. The instantiation of formalism into physicality
6. The GS (Genetic Selection) Principle
7. The capabilities of natural selection
8. The limits of physics and chemistry
9. The genetic code is conceptually ideal 10. Perspective 11. Acknowledgement 12. References


The GS (Genetic Selection) Principle states that biological selection must occur at the nucleotide-sequencing molecular-genetic level of 3'5' phosphodiester bond formation. After-the-fact differential survival and reproduction of already-living phenotypic organisms (ordinary natural selection) does not explain polynucleotide prescription and coding. All life depends upon literal genetic algorithms. Even epigenetic and "genomic" factors such as regulation by DNA methylation, histone proteins and microRNAs are ultimately instructed by prior linear digital programming. Biological control requires selection of particular configurable switch-settings to achieve potential function. This occurs largely at the level of nucleotide selection, prior to the realization of any integrated biofunction. Each selection of a nucleotide corresponds to the setting of two formal binary logic gates. The setting of these switches only later determines folding and binding function through minimum-free-energy sinks. These sinks are determined by the primary structure of both the protein itself and the independently prescribed sequencing of chaperones. The GS Principle distinguishes selection of existing function (natural selection) from selection for potential function (formal selection at decision nodes, logic gates and configurable switch-settings).


All known organisms are prescribed and largely controlled by information (1-22). Most biological prescriptive information presents as linear digital programming (23-26). Living organisms arise only from computational halting.  Fittest living organisms cannot be favored until they are first computed. Von Neumann, Turing and Wiener all got their computer design and engineering ideas from the linear digital genetic programming employed by life itself (27-32). All known life is cybernetic (33-35). Regulatory proteins, microRNAs and most epigenetic factors are digitally prescribed (3). MicroRNAs can serve as master regulators of gene expression (36-38). One microRNA can control multiple genes. One gene can be controlled by multiple microRNAs.

Nucleotides function as physical symbol vehicles in a material symbol system (MSS) (39-41). Each selection of a nucleotide corresponds to pushing a quaternary (four-way) switch knob in one of four possible directions. Formal logic gates must be set that will only later determine folding and binding function through minimum-free-energy sinks. The most perplexing problem for evolutionary biology is to provide a natural mechanism for setting functional configurable switch-settings at the genetic level. These logic gates must be locked in open or closed positions with strong covalent bonds prior to folding of biopolymers. At the point of polymerization of informational positive single strands, no selectable three-dimensional shape exists for the environment to favor.  In addition, the environment does not select for isolated function. The environment only selects for fittest already-living organisms.

The challenge of finding a natural mechanism for linear digital programming extends from primordial genetics into the much larger realm of semantics and semiotics in general. Says Barham: "The main challenge for information science is to naturalize the semantic content of information. This can only be achieved in the context of a naturalized teleology (by 'teleology' is meant the coherence and the coordination of the physical forces which constitute the living state)." (42) The alternative term "teleonomy" has been used to attribute to natural process "the appearance of teleology" (43-45). Either way, the bottom line of such phenomena is selection for higher function at the logic gate programming level.


Linear digital prescription requires selection of monomers at the point of polymerization of the initial positive informational strand. Primary structure (sequencing) instructs secondary and tertiary structure (three-dimensional shape). While chaperones and other factors affect folding, the sequencing of the polyamino acid itself is by far the biggest determinant of shape, electrostatic charge, grooves, knobs, tunnels, hydrophobicities, and lock-and-key binding of the globular protein molecular machine or enzyme to its substrate. Folding proceeds according to minimum Gibbs free-energy sinks (46-54). But rigidly-bounded monomeric sequencing largely determines what these thermodynamic and kinetic tendencies will be.

It is not sufficient for the environment to select the fittest living organisms. Organisms do not exist until after cooperative computational haltings occur on many different levels. None of these computational haltings will occur without selection of appropriate symbols so as to generate formally efficacious programming sequences. In addition, all these programming sequences must be integrated into a holistic operating system in order to organize even the simplest protometabolism. Organization, too, is mediated using multiple layers of material symbol systems. Physical symbol vehicles (nucleotide "tokens") are used to represent formal quaternary (four-way) switch-setting "choices." These in turn determine higher order levels of transcriptional regulatory networks, multilayer hierarchical structures, transcript turnover regulation, and three-dimensional information retention in genomes (55-57).

Self-replication tends to "get all the press" in life-origin literature. But the real issue of life origin lies in answering how the initial single positive strands of RNA instructions got sequenced so as to prescribe microRNA regulation, amino acid sequencing and eventual folding function. No new information is generated in base-pairing replications. Base-pairing has nothing to do with the generation of genetic information or coding. Base-pairing is purely physicodynamic, and quite secondary to the already-programmed, formal, linear digital instructions of the single positive strand.


Selection first requires categorization. A clear differentiation of real options must exist. Second, one category must be preferential or superior in its functionality compared to the others for selection to be worthwhile. Third, a means of selection has to exist. Last, impetus is needed to drive the selection process.

Does natural selection meet all of these criteria? The fittest organisms are clearly categorized from less fit organisms independent of human knowledge and description. Differential survival and reproduction were quite real ontologically before Homo sapiens ever appeared on the scene to ponder them. Superior fitness also readily meets the criterion of functional superiority. What about the third requirement: means? The means of selection is provided by gradual extinction of less successful competing organisms. Finally, the impetus to select is automatic. Differential survival and reproduction indirectly drives the selection process to its endpoint of maximum utility through time with no requirement of any external unnatural or supernatural force. No non-physical formal component is required for environmental selection of superior organisms to occur.

Problems arise, however, in explaining how any organism, fit or unfit, came into existence in the first place.

Let us now subject genetic programming at the molecular level to the same four essential criteria of selection referred to above. All four nucleotides polymerize with similar difficulty. Can single-stranded polynucleotide primary structures be distinguished and categorized by physicodynamics alone, prior to folding? Probably. Physicochemical, steric, electrostatic, and structural differences do exist between various stochastic ensembles of polynucleotides even before folding. But do any physicodynamic differences relating to nucleotide sequence matter to nature at the point of primary structure formation? In a prebiotic environment, would the environment prefer one stochastic ensemble over another? Although ribozymes and DNA enzymes exist, they contribute needed function only in a holistic metabolic context. No reason exists for nature to prefer a catalytic DNA over a non catalytic one. Nature has no goals, preferences or motives, evolution included. At the programming level of gene formation, function in an integrated metabolic scheme does not yet exist. No living phenotypic superiority exists for the environment to favor. Apart from a polynucleotide's participation in the instructional symbol system of an already living organism, any single strand of RNA or DNA is just as good as any other. A self-replicating RNA could theoretically form spontaneously. But as we will discuss later, it is not at all clear what such a self-replicating RNA would contribute to any potential metabolic scheme. It would also consume so many resources few would be left for thousands of other needed metabolites to form out of a severely depleted sequence space. Thus functional superiority of one sequence option (primary structure) over another is completely lacking in an abiotic environment. Natural selection fails the first two essential criteria of selection at the genetic programming level. The environment cannot adequately categorize options. In addition, functional superiority of some options over others does not yet exist for the environment to prefer.

What about the 3rd criterion of selection: means? With natural selection, the means is differential survival and reproduction of already living organisms. But at the genetic programming level in a prebiotic world, no life or differential survival exist yet. Means is totally lacking for evolution to occur at the programming level.

What about the fourth essential criterion of selection: impetus? In environmental selection, differential survival and reproduction of small populations drives the selection process. The impetus is automatic. But at the positive strand formation level, what is the natural-process impetus for selection of one nucleotide selection or one sequence over another? Phenotypic fitness does not yet exist. Life does not yet exist. Differential survivability cannot be a factor to drive the selection process. While a self-replicating polynucleotide might differentially "survive," a sequence optimized for self-replication would not have the ideal sequencing for almost any other metabolic function. The self-replicating strand would merely consume all the resources mass-producing itself. But with respect to prescribing all of the metabolic functions needed for life, the mass-produced strand would be gibberish.

Environmental selection can play no role whatever in the selection of nucleotides or codons. Yet these selections constitute the setting of critical logic gates. Nucleotide selections clearly constitute the programming of configurable switches. If the switches are not set properly, no life will come into existence to be favored. Yet at the point of polymerization of any certain sequence, no physicochemical superiority exists for the environment to favor.

So a purely physicalistic nucleotide polymerization of single positive strands in solution fails to manifest all four of the essential criteria of any selection process. No natural-process basis exists for programming the covalently-bound strand to be formally computational. Under these conditions, linear digital programming by environmental selection is impossible. Natural selection cannot occur at the programming level of configurable switch-setting (the choice of which nucleotide to polymerize next). Thus environmental selection cannot program computational linear digital programs. Yet environmental selection is the only kind of selection known to natural process.

Programming selections at successive decision nodes requires anticipation of what selections and what sequences would be functional. Selection must be for potential function. Nature cannot anticipate, let alone plan or pursue formal function. Natural selection can only preserve the fittest already-existing holistic life.


Non physical formalism can be instantiated into a material symbol system. Physical symbol vehicles (nucleotide tokens) can be used to record and transmit prescriptions of biochemical function. But both linear digital prescription and coding bijection (translation) are fundamentally formal, not physical. The field of applied genetic algorithms was modeled after the genetic control of living organisms. The applied model begins with a pool of potential formal solutions. This pool of potential formal solutions is presupposed, not explained materialistically. No such pool of potential formal solutions exists in the inanimate physical world.

Genetics is a representational Material Symbol System (MSS) (39-41, 58, 59). Instructions are instantiated into the selection of each of four possible alternative nucleotides, and into a particular sequence of those alternative nucleotides. From physicochemical standpoint, any of the four nucleotides can be polymerized next onto a single positive informational string with similar difficulty. Polymerization of the informational positive strand is therefore considered to be dynamically inert (physicochemically decoupled or incoherent) (41, 60). This detachment from physicodynamic determinism is essential for instantiation of prescription information into a physical matrix. Dynamic inertness is also necessary for random mutation and evolutionary transition (61-64). Without a freely resortable material symbol system, evolution is impossible (41).

As we saw above, environmental selection flunks all four essential criteria of selection at the genetic level. Natural selection is utterly blind to specific nucleotide needs at each locus in a forming single-stranded polynucleotide strand. Primordial soup models of life-origin are limited to either true stochastic ensembles, or to very low informational redundant sequences forced by law (e.g., adsorption onto clay surfaces). Of course purely physicodynamic base-pairing to already-existent highly informational strands can occur. But where did the already-existing highly-informational strands come from? If they are stochastic ensembles, by what mechanism did they acquire their linear digital prescription of eventual folding, lock-and-key binding, highly sophisticated formal biofunction, and holistic organization of metabolism? Coin flips cannot program linear digital cybernetics and symbol system coding. Random variation does not program sophisticated formal integration. No basis for formal selection of functional nucleotide sequencing exists in inanimate nature.


The GS Principle states that biological selection must occur at the nucleotide-sequencing molecular-genetic level of 3'5' phosphodiester bond formation. After-the-fact differential survival and reproduction of already-living phenotypic organisms (ordinary natural selection) does not explain polynucleotide prescription, noise-reducing "block coding" using 3 to 1 symbol bijection, and life itself. Each nucleotide must be selected at the point of polymerization with strong covalent bonds. Other non controlled constraints (e.g., environmental stresses), semi-controlled constraints (e.g., the corrupted information of prion misfoldings), and controlled constraints (e.g., programmed chaperone proteins) also affect protein and nucleic acid functional conformation. But by far the main determinant of conformational structure and function is the primary structure of polyamino acid chain itself. The determinant of amino acid sequencing is in turn post-edited ribonucleotide and polycodon sequencing.

The specific selection of one ribonucleotide from among four real options functions as a quaternary (four-way) configurable switch-setting. Configurable switches control and prescribe, not merely describe, translated metabolic utility. Covalently-bound selection commitments are rigid by comparison to weaker H-bonded secondary folding. Primary structure is the primary determinant of what H-bonding and van der Waals forces can accomplish. Configurable switch-settings in the form of specific nucleotide selections constrain minimum-free-energy folding space. Both ribonucleotide polymerization reactions and folding are subject to the laws of motion and to dynamic constraints. But the cybernetic function of the genetic material symbol system controls those constraints. The sequencing of nucleotides as physical symbol vehicles is not determined by physicodynamics. It is dynamically inert (physicodynamically incoherent; decoupled from physical determinism) (41, 60). Once instantiated into a Material Symbol System, however, this dynamically-inert programming physically constrains dynamic folding space. The GS Principle attributes the main control of folding constraints to nucleotide sequencing selections. All life depends upon literal genetic algorithms, including most epigenetic factors. Fittest organisms cannot be favored until they are first computed.  The GS Principle elucidates the source of messenger molecules' representational prescription of biofunction, a phenomenon unique in nature to life (26). The GS Principle distinguishes selection of existing function (natural selection) from selection for potential function (formal selection at decision nodes, logic gates and configurable switch-settings).

Symbol systems employ alphabetical characters, signs, and physical symbol vehicles (tokens such as nucleotide options) to represent meaning or function. Selections must be made from an option space of real, uncoerced alternatives. Each selection represents the setting of a logic gate or configurable switch that computes or integrates a circuit. The purposeful selection of letters alone constructs words, sentences and paragraphs. Any denial of "choice with intent" reduces language to gibberish. Any attempt to replace arbitrary rules of convention with fixed law destroys information potential. Rules are voluntarily followed, not forced. Only when the destination voluntarily applies the same free and arbitrary rules of the source can the destination successfully interpret the source's intended meaning. By arbitrary, we do not mean random. We mean, "could have been otherwise" within the constraints of nature. But abiding by arbitrary rules also embodies selection in accordance with those rules at the decision-node level. The programming of polynucleotide prescription of biofunction cannot be reduced to mere linguistic and computer science metaphor (20). Indeed, if any analogy exists, it is in the reverse direction. Life's linear digital cybernetics predates humans, their languages and their computers.


Only existing genetic algorithms can be optimized. Prior to an algorithm having computational function, no basis exists for selection in nature. So the question becomes, "How did any computational program arise in nature? Computation is formal, not physical. Natural selection cannot generate formalisms. It can only prefer the results of formal computations-already living organisms. What would be the basis of natural selection for a half-written program that does not yet compute? Even if a formal computational program were to somehow spontaneously arise, why would an inanimate environment value and preserve it? The only basis for natural selection from the start was survival of the fittest already-living organisms. But no organism exists without hundreds of cooperating formal algorithms all organized into one holistic scheme. The more computational steps that are required to achieve integrated halting, the harder it becomes for an inanimate environment to explain optimization. And the more algorithms that must be simultaneously optimized and integrated, the harder it is to explain metabolism.

Natural selection resembles public consumption of the best available software. The programming details and methodology of production are of no interest to the purchasers of software. Pre-programmed, bug-free, superior utility is the only criterion of public selection. The consumer plays no role whatever in the writing or refinement of the program's computational efficiency. The finished product with the best reputation, availability, and lowest cost becomes "the fittest species." Just as consumers are oblivious to how the best software was produced, natural selection is oblivious to how the fittest species was produced. Natural selection offers no explanation whatever for programming at the genetic level. Similarly, natural selection does not explain the derivation of the many cooperative computational processes leading up to the origin of life.

Stunningly, information has been shown not to increase in the coding regions of DNA with evolution. Mutations do not produce increased information. Mira et al (65) showed that the amount of coding in DNA actually decreases with evolution of bacterial genomes, not increases. This paper parallels Petrov's papers starting with (66) showing a net DNA loss with Drosophila evolution (67). Konopka (68) found strong evidence against the contention of Subba Rao et al (69, 70) that information increases with mutations. The information content of the coding regions in DNA does not tend to increase with evolution as hypothesized. Konopka also found Shannon complexity not to be a suitable indicator of evolutionary progress over a wide range of evolving genes. Konopka's work applies Shannon theory to known functional text. Kok et al. (71) also found that information does not increase in DNA with evolution. As with Konopka, this finding is in the context of the change in mere Shannon uncertainty. The latter is a far more forgiving definition of information than that required for prescriptive information (PI) (21, 22, 33, 72). It is all the more significant that mutations do not program increased PI. Prescriptive information either instructs or directly produces formal function. No increase in Shannon or Prescriptive information occurs in duplication. What the above papers show is that not even variation of the duplication produces new information, not even Shannon "information."

All of the above work correlates well with Weiss et al (73) finding only 1% deviation from randomness in coding regions. One cannot increase "information" (really "uncertainty") very much when starting from only 1% deviation from randomness in the coding regions. Only 1% deviation from randomness is already nearly maxed out in uncertainty. How did a text that deviates only slightly from seeming randomness get so instructional and biofunctional? Clearly, mere combinatorial uncertainty is not going to explain the phenomenon of cybernetic genetic prescription. No empirical evidence exists of mere variation ever having generated sophisticated PI, computational halting, or cybernetic integration of large numbers of pathways and cycles, or the achievement of metabolic goals.


No physicochemical factors determine monomeric sequencing of genes. Physicodynamic determinism would severely reduce the uncertainty required for information retention in any physical matrix. Sequencing is physicodynamically inert (dynamically incoherent) (41, 60). Sequencing is decoupled from physicodynamic causation. It is independent of cause-and-effect physical determinism. This freedom is the very key to carbon chemistry being ideal for instantiation of large amounts of genetic prescriptive information into a physical matrix.

Attempts to explain the origin of formal programming from chance and necessity, thermodynamics and kinetics (74-84), have been unconvincing. Brillouin and others have attempted to equate Shannon's "informational" uncertainty with Maxwell-Boltzmann-Gibbs entropy. Notions of negentropy abound despite Boltzmann's prohibition of a negative constant in his famous equation: S = k log W (85). Neither the number of microstates (W) nor Boltzmann's constant (k = 1.38065 x 10-23 joule/Kelvin) can be negative. In addition, every probability distribution is unique. Yockey showed that the probability distribution phase space of Boltzmann's physical entropy (S) cannot be equated or synthesized with Shannon's probability distribution of "informational" uncertainty (H) despite seemingly identical S and H equations (apart from the disallowed sign reversal of S) (23). Information theory also lacks the integral of motion inherent in thermodynamics.

Schneider (86) and Adami (87, 88) are correct that uncertainty is not information. But mere subtractions of "after uncertainty" from "before uncertainty" do not measure up to the formal cybernetic proficiency of genetic control. Even archaeal genomes positively program thousands of integrated computations. These cybernetic processes are not just decreasing measurements of combinatorial probabilism. Even if they were, inanimate nature cannot measure (89-92). Human knowledge and measurement of the change in uncertainty inserts a human mental factor into the definition of even Shannon "information" that did not exist for most of the presumed 3.8 billion years of genetic prescription. Genetic instructions stand alone in their proficiency at making life happen.

Adami is also correct that bona fide information must be about something (87, 88). But no source of formal "aboutness" has ever been provided from physics, chemistry and the physical environment alone. Yes, the environment provides a context. But the environment does not program the meaningful (cybernetically functional) configurable switch-settings that enable living organisms to overcome environmental insults and challenges that will occur only in the future. Aboutness will not be found in the environment itself. Aboutness requires choice contingency. Aboutness is generated by the particular settings of configurable switches that program computational halting and that organize integrated circuits to meet future challenges. Meaning is formal, not physical. The environment cannot exercise choice contingency at genetic logic gates. The environment cannot program configurable switches. It can only favor the best already-computed living organisms.

A long string of Nobel laureates including Niels Bohr (93) and Jacques Monod (94) have argued that chance and necessity cannot generate non trivial linear digital biological instructions. Bohr argued that "Life is consistent with, but undecidable from physics and chemistry." (93). Many additional first-rate biologists such as Ernst Mayr (95, 96) and Bernd-Olaf Küppers (97, pg 166) have argued that physics and chemistry do not explain life. Says Hubert Yockey, "More than any other characteristic, computational linear digital algorithms distinguish life from non life" (98).

Clay surface adsorption is also purely physicodynamic with highly redundant order. Nucleotide adsorption results in homopolymers such as poly (A) and poly (G) onto montmorillonite and kaolinite clay surfaces (99-102). Such homopolymerizations do not even contain Shannon information, let alone semantic information. Such homopolymers offer no potential for prescription of formal function. Inflexible laws cannot select nucleotides and codon "block codes" (many-to-one symbol assignments used to reduce noise pollution in the Shannon channel) to achieve formal programming function. Life is the most highly informational phenomenon known to humans. Physicochemical propensities only preclude the generation of new information. New information generation requires uncertainty, not forced physical causation according to fixed laws. Laws are compression algorithms of reams of data made possible because the information content of all that data is so reducible. Functional sequencing, therefore, will never be explained by law. This includes hoped-for, as-of-yet undiscovered imaginary laws. Laws are too low-informational. They describe redundant, monotonous, highly ordered behavior with a probability approaching 1.0. Such behavior has almost no uncertainty. Law-like behavior precludes highly informational uncertainty required for linear digital prescription of formal function.

Another major problem for life-origin science is that untemplated single-stranded oligoribonucleotides do not exceed 8 to 10 mers in length in aqueous solution. Biological prescription requires extremely long positive prescriptive strands. Base-pairing or templating of some kind (as on montmorillonite) is required to expedite polymerization. Base-pairing, of course, merely duplicates the strand's sequence in reverse direction. Templating on clay typically produces polyadenosines of no more than 50 mers (100). To achieve that length requires the intervention of highly intelligent chemists. Such highly ordered, short sequences contain little or no information. The high probability of adenosine's occurrence at each "decision node" in clay adsorption strings approaches 1.0. The uncertainty of such an RNA strand is close to the summation of 0 bits at each locus in the string times the number of ribonucleotides (- log2 p = - log2 1.0 = O bits of uncertainty times n loci = 0 additive bits). Physicodynamics cannot generate nontrivial Prescriptive Information (PI). The generation of programming instructions requires freedom of selection at each logic gate. More importantly, it requires selection for potential function at each decision node. This is the very reason that sequencing is able to become a control function, not just a physical constraint. And the sequencing is not stochastic either. The control function manifests too much computational utility. No empirical evidence, predictive success, or rationality exists in the history of human experience to justify believing that unaided Markov processes can generate sophisticated algorithmic programming apart from hidden investigator involvement. Although the experiment is begun with a random pool, selections of particular iterations are usually employed behind the scenes to achieve the desired potential function.

The pre RNA and RNA World models of life origin provide simplification and ideal reductionism for the study of the birth of biocybernetics and biosemiotics. Small RNA's provide a multitude of controlling (regulatory) functions even in current life. But spontaneous RNA generation is a biochemical vertical cliff (103-107). In addition, ribose and RNA are too unstable for the long highly informational strands needed for life to have slowly developed by small increments (104, 108). As a result, many life-origin specialists have been forced to return to Peptide First and Metabolism First models advocated by Gánti (109), Shapiro (110, 111), Dyson (112), Kauffman (113), Wachtershauser (114), Morowitz (115), Deamer (116), Lindhal (117), Russell (118), and many others.

Yet a Metabolism First origin of life is far from a foregone conclusion (119, 120). Few life-origin scientists have been more respected than Leslie Orgel. Wrote Orgel, "In my opinion, there is no basis in known chemistry for the belief that long sequences of reactions can organize spontaneously---and every reason to believe that they cannot." (121) Indeed, organization should never be confused with mere self-ordering phenomena in nature (22, 33, 35).


The source of genetic programming lies in the selections of nucleotides, and in the sequencing of those particular nucleotide selections. Says Fontana and Schuster, "Understanding which phenotypes are accessible from which genotypes is fundamental for understanding the evolutionary process." (50) The sequencing of DNA nucleotides has no meaning or function independent of an overarching formal system of arbitrary (could have been otherwise) symbol assignments to each amino acid.

A representational symbol system is clearly employed in the triplet codon table of amino acid prescription. Codons are a form of Hamming "block code" wherein consistent groups of three symbols are used to represent each single amino acid prescription. Block coding is a form of redundancy coding used to reduce noise pollution in the transmission channel. These arbitrary assignments have been shown to be conceptually ideal (122) (123). Despite wobbles and point mutations, codons are often still able to prescribe the correct amino acid because of this extraordinary redundancy coding.

Life-origin models cannot reduce these phenomena to human epistemology. They are objective phenomena, not merely heuristic tools of human mental construction. Biosemiosis and biocybernetic management was integrating and engineering life's processes long before Homo sapiens appeared on the scene to ascribe their linguistic and cybernetic analogies to molecular biology. How would chance and necessity have conceived such an effective, formal, noise-reducing scheme?


Additional layers of coding sophistication also exist. Independent coding overlays the genetic code in DNA (124). A separate set of rules controls the binding of transcription factors and histone proteins to DNA. These additional rules control messenger RNA splicing and folding. The later contribute to regulating protein manufacture. The two coding systems are independent, but they are also coordinated. The two codes jointly control metabolism (124). The genomic code is far more vast than the genetic code, as if we weren't already burdened trying to explain the genetic code alone through natural process. The genomic code includes the three-dimensional structure of DNA and many additional overlaid codings in molecular biology (123).

All of these formally integrated systems require selection contingency, not chance contingency or fixed law, to organize (125). Selection must take place at the genetic level of nucleotide selection for any phenotype to come into existence, let alone the fittest phenotype. This fact of reality constitutes the GS Principle.


The GS Principle states that selection must occur at the molecular/genetic level, not just at the fittest phenotypic/organismic level, to explain the generation of polynucleotide and polycodon linear digital prescription. Organismic/phenotypic selection (natural selection) cannot prescribe the linear digital programming of coded genetic instructions. Environmental selection cannot set configurable switches so as to achieve potential integrated circuits. Selection pressure is after the fact of computational halting. No fittest organisms exist for the environment to favor without prior computational haltings on many cooperative levels. Nucleotides must be selected and rigidly bound in a certain sequence to prescribe and integrate metabolism. Sequencing (primary structure) is the major determinant of three-dimensional molecular-machine shape (tertiary structure) and biofunction. Nucleotide sequencing is covalently (rigidly) bound into a linear digital string long before that string can fold into a ribozyme or can digitally prescribe polyamino acid sequencing. Metabolism depends on holistic integration of thousands of individual protein prescriptions, including epigenetic regulatory proteins and microRNAs. Ultimately even most epigenetic factors such as methylations are prescribed and tightly controlled by liner digital genetic instructions. Such symbol systems are fundamentally formal, not physical.

Ribonucleotides and oligoribonucleotides are physical. Their polymerization reactions are fully subject to the laws of motion and to dynamic constraints. But their specific sequencing is dynamically inert. Their cybernetic function consists of instantiations of formal selections for potential function, not already-existing physicodynamic necessity. Selection pressure plays no role in determining potential function at the formal programming level of configurable switch-setting (polymerization of each particular nucleotide).

Genes are linear digital programs. Even their editing is ultimately controlled by other linear digital programs. Genes only function exists in the context of a formal representational material symbol system using physical symbol vehicles. Their configurable switch-settings are dynamically inert. Highly informational metabolic instructions cannot be generated by low-informational laws. The GS Principle defines the kind of selection that is required to set physical configurable switches so as to compute metabolic integration. Environmental selection has never been observed to generate the simplest example of formal computational halting. Worse yet, the latter is a logical impossibility. Physicodynamics is limited to chance and necessity. Formal computation is abstract, conceptual and non physical. Formal computation cannot be generated apart from selection contingency at true decision nodes. Metabolic organization and life have never been observed to exist independent of formally integrated computational haltings.

The specific selection of each nucleotide from among four real options controls, not merely constrains biofunction. The selection of each nucleotide also prescribes, not merely describes, its metabolic contribution. The GS Principle states that natural selection of already optimized genetic algorithms (the fittest already-computed living phenotypes) is inadequate to explain the derivation of a single-stranded polynucleotide's digital programming and computational prowess. Selection for potential function must occur at each decision node-each logic gate-each configurable switch-setting-each nucleotide polymerization onto the programming string.


This work was funded by a grant from the Origin of Life Science Foundation, Inc.


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Abbreviations: GS: Genetic Selection; MSS: Material Symbol Systems; OEE: Open-Ended Evolution.

Key Words: Bifurcation points, Biosemiotics, Biosemiosis, Biocybernetics, Complexity, Configurable switches, Decision nodes, Dynamics, Epigenetic, Formalism, Genetic code origin, Logic gates, Natural selection, Physicodynamics, Selection pressure, Sign Systems, Symbol Systems, Self-replication, Self-organization, Self-assembly, Review

Send correspondence to: David L. Abel, Director, The Gene Emergence Project, The Origin-of-Life Foundation, Inc., 113 Hedgewood Dr. Greenbelt, MD 20770-1610 USA, USA Tel: 301-441-2923 , Fax 301-441-8135, E-mail:life@us.net