Informational Perspective on Evolutionary Theory: Comparison
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Please note this is a comparison between Version 2 by Jason Zhu and Version 1 by Pedro C. Marijuán.

Countless informational proposals and models have explored the singular characteristics of biological systems: from the initial choice of information terms in the early days of molecular biology to the current bioinformatic avalanche in this “omic” era. Herein we propose an enlarged informational perspective, grounded on the information flow and coding mechanisms in the living cell, and extended along the complexity growth in the evolutionary process.

  • biological complexity
  • evolutionary theory
  • information

1. Introduction

To paraphrase Dobszhanzy’s famous dictum, nothing in biology would make sense except in the light of information. Having substituted information by evolution, very few parties would nowadays deny that the former appears as the very ‘substance’ of the latter. Evolutionary theory itself may be the best place to substantiate that assertion, which indeed is the core of the present work. However, before this, the focus should be placed on another important informational/evolutionary theme, biological codes, which has been left in relative obscurity by most evolutionary thinkers and biosemiotic practitioners [73][1].

2. On Codes and Code-Makers

In addition to the origins of the genetic code, still only partially solved [74][2], one of the most puzzling evolutionary developments is the fantastic variety of new codes achieved in eukaryotic evolution: from DNA genetic code to splicing codes, histone codes, sugar codes, compartment and transportation codes, cytoskeleton codes, tubulin code, nuclear signaling code, nuclear export code, ubiquitin and conjugating enzymes codes, epigenetic codes, adhesion codes, and many others [73,75,76,77][1][3][4][5]. According to the former author, prokaryotes that were unable to develop new codes precluded themselves from participating in the development of further organization complexity. The creation of new codes was necessary for the emergence of eukaryotes, it is clear, but what kind of events made them possible? Why in such a wide variety?
In the discussion about codes, we have to consider the general organization of eukaryotic complexity must be considered. Codes, in their most general acceptation, and in our own the information views as well, mean the systematic correspondence between elements of two different worlds—in ourthe case, distinct informational architectures—in order to organize complex functions with specificity and efficiency.
In the cellular milieu, there could be instances of codes between sequences matching to shapes, shapes matching to sequences; or shapes matching to shapes, and sequences matching to sequences; or there could be shapes within sequences, and sequences within shapes (enzymes and proteins have their own sequence of amino acids). Almost every complex cellular function, including ‘big codes’ such as the genetic code itself or the splicing code, could be decomposed on an assemblage of functional middle-level codes and low-level codes; all of them based on specific molecular-recognition events, quite often involving combinatorics of ‘colors’and ‘shapes’ in between the architectural partners involved in each matching.
Thus, as in computer systems, wresearchers may speak about micro-codes, middle-level codes, and macro-codes. The assemblage of micro-codes and middle level codes that are needed to perform new complex functions after the command of a macro-code—in development, in physiology, or in neuronal processing—would be very difficult to achieve. In general, that will be possible only after the genomic incorporation of an external connoisseur or ‘expert’ bringing together of many of those matching events. The viral provenance of those external experts becomes highly probable. Along their convoluted circuits within cells, viruses have to recognize and interact with a number of protein factors and RNAs. For instance, in human cells, the HIV virus ‘knows of’ and specifically interacts with 453 human proteins [78][6]; the influenza virus interacts with 295 proteins [79][7]; the Ebola virus with 194 proteins [80][8]; and the new COVID-19 virus is said to interact with 332 proteins [81][9]. Additionally, these viruses and many others may hijack ncRNAs, lncRNAs, and miRNAs of very different classes in order to rewire cellular metabolism and to promote their own replication [82][10]. Let us emphasize the coding potential of many of those RNAs, as they may have not only ‘color’ or sequence, but also highly characteristic and diversified ‘shape’ in their loops, a factor that becomes crucial for their participation in complex matching populational processes.
If increasing the repertoire of cellular functions needed a loan about viable itineraries among architectures, there have been quite many possible ‘experts’ out there and in here. We must take into account that one the most important genome modifications of eukaryotes has come from the systematic activity of inner components of viral provenance: mobile elements, transposons, retrotransposons, repetitive elements, among others, which combined would represent more than 2/3 of the human genome [83][11]. Seemingly, our species has counted with around 4 million mobile insertion events [10][12]. Ancestral viral proteins can be found in human placental adhesion and development [84,85][13][14], in splicing machinery and in nuclear pores [11[15][16],66], in master gene regulators [86][17], and all across the mammalian and human proteomes [87][18].
Thereafter, it is almost inevitable to speculate about the participation of the whole “virome” in the evolutionary events leading to eukaryotic complexity and multicellular life [11,66,88,89,90,91][15][16][19][20][21][22] That means, among other things, the unexpected addition of a new, forgotten realm of life to Margulis’s endosymbiotic theory [57,58][23][24]. Perhaps more properly, it means plainly incorporating viruses’ essential evolutionary role within the present discussions around the renewal or replacement of evolutionary theory [91][22]. The “deep evolution” approach based on protein superfamilies analysis by hidden Markov models [92][25] would point to two independent lines of descent for eukaryotes and akaryotes (bacteria and archaea) out from the most recent universal common ancestor. Would eukaryotes constitute the more virus ‘friendly’ or labile line capable of fully integrating the viral code-making resources into the later complexity explosion? Ex virus omnia, according to [84][13].
The “Weismann barrier” was considered as isolating the germ cells’ genome from the phenotype vagaries. However, evolutionarily, we see it has been close to an ‘admission portal’—see, for instance, the penetration of ‘exosomes’ [12][26]. In general, the stages of germ cell, meiosis, gamete, fertilized zygote, gastrulation, and early development are highly susceptible to accommodate a variety of external/endogenous influences. Thus, the obligate return of multicellulars to the unicellular form becomes far more than intriguing [93][27], as it is at this stage when most of the above ‘travel companions’ are incorporated into eukaryotic vehicles, and when the strongest epigenetic effects occur. The phenotypic experiences of the parents in their separate exploration of the environment are sorted, modified by meiotic cross-over, and entered into the histone and DNA methylation codes. The mechanisms are still unclear, but the experimental evidence is there, in numerous species as well as in our own. The gamete as well as the zygote and the developing embryo are instructed about fundamental aspects of the panorama waiting out there—food scarcity, parental care, social environment, among others—and become subsequently preadapted through a metabolic–epigenetic-behavioral axis [94][28]. That almost all multicellulars reproduce by resorting to sexual gametes obtained after meiotic division has been a formidable engine both for evolutionary complexification and for consistently maintaining the stability of species [93][27].
As Torday [95][29] writes: “It is as if the unicellular state delegates its progeny to interact with the environment as agents, collecting data to inform the recapitulating unicell of ecological changes that are occurring. Through the acquisition and filtering of epigenetic marks via meiosis, fertilization, and embryogenesis, even on into adulthood, where the endocrine system dictates the length and depth of the stages of the life cycle, now known to be under epigenetic control, the unicell remains in effective synchrony with environmental changes”.

3. On Evolutionary Theory

In ourthe informational vision, a sober analysis of the conventional evolutionary tenets would show troubles and absences. WeResearchers have just seen two ample blocks of variability not very congruent with the classical Darwinian (or neo-Darwinian) formulation of evolution by random mutation and natural selection. The attempts to incorporate the known new facts as mere ‘add on’ to the conventional processes of evolutionary change have fallen short of the mark [96][30]. Nevertheless, their explanatory allure remains. The simplicity of neo-Darwinian views and their (apparently) universal explanatory reach, from molecular competition to the origins of life, to everything biological or human, makes them a magnet for reductionist thought of all kinds: “if it exists, it has been selected”.
Actually, although wresearchers seem to maintain two realms similar to the basic Darwinian views (variation and selection), weresearchers substantially change their contents, now formulated, weresearchers think, with more cogency regarding the sheer diversity of known facts.
Firstly, regarding generation of variability, we would be forced to an almost impossible compilation, putting together so many heterogeneous categories: mutations (neutral, significant, short-scale, and large-scale); sex and populations (allele distribution, recombination, and genetic drift); gene modification (horizontal transmission, frameshift change, intron/exon swapping, domain recombination, and duplications); chromosome rearrangements (translocations, inversions, deletions, crossover, and duplications); mobile, transposable, retrotransposable, and viral elements (with additional effects via ncRNAs, siRNAs, miRNAs, piwiRNA, and gene silencing); developmental (biased gene expression, repetitive DNA, ncRNAs, enhancers and regulators, and neoteny); epigenetic (histone code, DNA methylation, hormonal imprinting, and stress metabolic–behavioral axis); whole genome duplications; symbiosis; as well as a variety of other behavioral and environmental effects impinging on organisms.
At this point, wresearchers may consider a new term taken from human mobility studies: containers [97][31]. In the way human mobility is studied, one has to distinguish in which ‘container’ the movement is produced, and this means the corresponding standard range of displacements (distances) and frequencies (probabilities). So, in displacements by walking, cars, buses, metros, trains, planes, etc., each mode is producing an average displacement at an average frequency (or probability) for the average individual. They are not exclusive; for in a particular trip wresearchers may walk, take a taxi, a plane, and again a bus and some further walking. In general, and in aggregate, weresearchers will have separate ‘rectangles’ in the representation of displacement and frequency (probabilities) for each mobility mode, following a log-normal distribution. Now, the surprising effect, and the essential point about introducing the container term in our evolutionary discussion, is that when all containers are superimposed, the different rectangles disappear and a power law emerges regarding the aggregate human mobility. The introduction of new transportation modes would only contribute to change the slope of that power law. What this means is that the aggregate mobility of human population becomes self-similar, optimized regarding the classes of displacements and their frequencies. The smaller and slower displacements are far more common, but their aggregate mobility for the whole population is not too different from the medium range ones, which are less frequent, but cover longer distances; and the very fast modes are far less common, but more far-reaching in each displacement. This emerging commonality would recall the way in which energy is distributed equally among the different degrees of freedom of a molecule: linear velocities, rotations, oscillations, and vibrations. In fact, there is an equipartition between all of them (following what is called the “equipartition theorem”).
In a similar way, could researchers consider the aggregation of different “containers” regarding the evolutionary mobility of genomes in sequence space? Genomes have been moving quite a lot in sequence space, either walking at the minuscule pace of point mutations or at fantastic distances and speeds due to genome duplications or to symbiosis, with all kind of intermediate possibilities. In the neo-Darwinian exploration of adaptive landscapes, different kinds of exploratory motion around fitness peaks and valleys have definitely been considered: mutations, genetic drift, and sexual recombination [98][32]. Each mode conveys some specific displacement range in the adaptive landscape.
Further advancing the idea, researchers could group the multiple variability occurrences in just four containers: mutational, genomic, developmental/epigenomic, and transgenomic. In the evolutionary scenario, the less influential sources of variability, “mutational”, would be the most common mode; we have already mentioned the basic neo-Darwinian categories (mutations, genetic drift, and sex). The following container, “genomic,” could have more influential effects, but would be relatively less frequent; arguably, some parts could enter into the neo-Darwinian variation categories, but it would be very dubious for all the other gene, chromosome, and genome rearrangement categories, many of them due to transposon, retrotransposon, and viral agency. Furthermore, in the “developmental/epigenomic” container, we could group the most radical viruses’ effects regarding the development of novel tissues, functions, and codes, in addition to the multiple developmental (evo-devo) variability sources, as well as the epigenetic heredity phenomena. Finally, in the “transgenomic” (and also ‘metagenomic’) container, we could include the major symbiosis category and other not-so-radical effects due to external inter-actions beyond the genomic realm, such as behavior, niche construction, and different environmental effects—in general, the consequences of operating within an open-ended, interactive, and social environment.
Overall, in the genome evolutionary displacements, we should find that major evolutionary changes will be extremely influential, but extremely rare as well, so that in the long tempo of evolution the different sources of variability would have implied a similar cumulated ‘mobility’ in sequence space by each one. This is to say that, if the cumulated mobility of genomes in sequence space resembles human mobility, there would appear a smooth distribution of evolutionary change among the main variability containers—an equipartition. Every species would have followed its own trajectory at its own rhythm (the slope of its power law) propelled by the combined engines of variability it had accessed. However, not all containers should follow the same pattern of behavior, and what looks cogent for one of may be a blunder for others (e.g., forcing the “random” term for all mobile events). Additionally, counting with a variety of different components within each container, with say a range of distinct model “vehicles” of choice, could grant a smoother power law for their aggregate action. In the same way that complex societies have been developing more and more transportation modes for expanding individual motion in physical space, complex organisms would have developed more and more classes of evolutionary vehicles for their exploration of the increasingly vast sequence space.
The previous containers and their vehicles or engines of variability would be met by a series of eliminative counterparts, the different evolutionary sinks or selection events. Evidently, not just one class of “natural selection” occurs, but a vast plurality. This is to say that, in the same way that we can identify scores of different variation instances, there seems to be a similar range of diebacks. At least, we could distinguish environmental selection (e.g., due to physical parameters), ecosystem selection (e.g., altered habitat), niche selection (e.g., by invading species), predatory selection, parasitic/pathogenic selection, competitive selection, sexual selection, behavioral selection (Baldwin effect), social selection, group selection, keen selection, developmental selection, physiological purifying selection, stabilizing selection, among others. Could all of them be unified under the “natural selection” term? It is inconvenient for two reasons: that we hide the real causes intervening in the selective event (which is often clearly identifiable), and that selective instances may be purposive, do not belonging to some external nature, but to internal drives (e.g., sexual selection, social selection, and group selection). The efforts to prove that the ”natural” term applies to all of them following the Darwinian canon are futile—it becomes an ”artificial” label when applied to whatsoever selective causes. Additionally, we are ignoring the pervasive extension of cooperative phenomena. In quite a few of the selective instances mentioned, or in symbiotic relationships, cooperation of various kinds underlies the survival advantage gained by the organisms involved [99][33].
Natural selection is not a source of adaptive design either, actively pruning the randomness of mutational events and leaving a string of progressive functional achievements, as claimed. Necessarily, the core design itself—or a viable precursor—has to be produced in advance by several combined variation events, by natural experimentation, without excluding instances of channeled or directed evolution. Darwinism only circumscribes the demographic fate of novelties, which in a variety of “easy” instances may lead to speciation (e.g., first container and parts of the second). However, selection is not merely the result of a competition of alleles within populations. In its more general acceptation, it would mean differential survival, including the whole self-construction, self-maintenance, and reproduction effects, which may be due to a plurality of causes, often identifiable. The trouble with maintaining the conventional term is that too much ideological, unscientific reasoning has been collected under the rug of natural selection. It is not only the preaching of a few ultra-Darwinists, such as Richard Dawkins and Peter Atkins. For instance, the latter has penned an astonishing sentence [100][34]: “A great deal of the universe does not need any explanation. Elephants, for instance. Once molecules have learnt to compete and to create other molecules in their own image, elephants, and things resembling elephants, will in due course be found roaming around the countryside. Some of the things resembling elephants will be men”. Amen? Unfortunately, a large portion of the educated public, and indeed many practitioners within biological fields, still uncritically accept and follow the Darwinian dogma of omnia ex nihilo [15][35]. The overextension of the Darwinian paradigm of evolution by random mutation and natural selection outside the borders of its ‘natural containers’ has become another of the “Great Blunders of Science” [101][36], joining entropy, information, and cognition as computation as one of the most vexed conceptualizations of our time.
Although some easy parts of the origin of species problem have been solved via the Darwinian tenets, there remains too much evolutionary complexity to adumbrate, to explain, and to accommodate in a parsimonious formula. Alternatives to the beguiling simplicity of Darwinian and neo-Darwinian views are badly needed and should be actively looked for. Recently, a discussion has been taking place, for instance, between Neo-Darwinian defenders and those who consider the renewal of evolutionary theory just as a matter of paradigm extension [96][30], in addition to others who consider that a full replacement is needed [12][26]. Researchers' informational proposal would join the latter views, though trying to change the reference framework. The alternative at the time being should not be limited to a relatively long list of thematic discrepancies and agreements; a new way of thinking is needed that is capable of a parsimonious synthesis. This should also include looking for a competitive short formula that is crafted tentatively to cover the two fundamental aspects of evolution: generation of variability and pruning by selective processes.
Variation, researchers have seen, might be grouped into four containers, each one having quite a few different vehicles inside. The variation resulting from their individual and aggregate action, including ‘forbidden’ feedbacks with the phenotype and with the environment, can be aptly categorized as systemic. This is probably the most inclusive term. In this way, wresearchers might talk about “systemic variation”. It has to be accompanied by the term “informational architectures”, for these architectures are the scenario in which the systemic variation finally becomes gauged and registered. On the other side, weresearchers may point out that there is a differential survival impact, in relation to the ongoing processes of self-construction, self-maintenance, and reproduction, which are always taking place in the background of an interactive and social environment.
So, wthe formula could be synthesize the formulad: “evolution proceeds by systemic variation in the informational architectures, which may bring forth the differential self-construction, self-maintenance, and reproduction of biological agents within their open ended, interactive environment”. Put in much shorter terms: evolution by systemic variation and differential survival.

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