Need reviewers for Common Design theory to be submitted to Science journal

Faith & Science Conversation
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According to Darwin’s model, the various hypotheses about viral origins—such as virus-first, escape, and reduction—are generally seen as mutually exclusive. In contrast, Owen’s theory integrates these hypotheses, forming a cohesive framework. Additionally, an expert reviewer noted that our …

References to scientific theories (e.g., the role of pi electron resonance, the formation of viroids, the evolution of unicellular to multicellular organisms) are generally aligned with current scientific understanding

The virus-first hypothesis, for instance, provides insights that should not be disregarded. Darwin’s model, on the other hand, mainly accounts for processes that occur post-origin of life, which seems to limit its applicability to virus origins. This distinction highlights a potential limitation in applying Darwinian theory fully to viral origins.

Actually, the concept of a common archetype is not entirely new; it precedes Darwin’s theory and indeed was foundational in his development of common descent. Concepts like homology originated with Owen’s framework. So, while there are new terminologies and models today, they are based on longstanding scientific foundations and are adapted to modern contexts.

For instance, Richard Owen’s archetype concept parallels and enriches modern scientific findings:

  1. Homology and Developmental Biology
  2. Genetic and Morphological Convergence
  3. Biochemical Constraints in Molecular Biology
  4. Conserved Non-Coding DNA as Archetypes
  5. Pattern-Based Systematics in Phylogenetics

Owen’s archetype theory thus remains relevant by suggesting inherent structural templates or “blueprints” that persist across species, offering an additional lens alongside Darwinian models to understand biological diversity. If you want me to provide detailed examples, just ask.

Our approach does not rely on a single definition of function. Rather, we apply functional definitions to support the common designer theory in this context. For your preferred definition, we would use it to support the common design theory, as I will explain in further comments below. Furthermore, as noted by researchers like Manolis Kellis, there is no universally agreed-upon definition of function. Different scientific disciplines approach function from varying perspectives:

“…there is no universal definition of what constitutes function, nor is there agreement on what sets the boundaries of an element. Both scientists and nonscientists have an intuitive definition of function, but each scientific discipline relies primarily on different lines of evidence indicative of function. Geneticists, evolutionary biologists, and molecular biologists apply distinct approaches, evaluating different and complementary lines of evidence.”

Sure, but keep in mind, I see this as a shift to your criteria now as you never explained why it was not a shift given your initial statement (e.g. “At a minimum” )

The disparity between Owen’s and Darwin’s theories lies in their treatment of discontinuity. Owen’s perspective posits distinct and separate vertebrate groups of organisms, emphasizing their disconnected nature from one another. This contrasts with the predictions of evolutionary theory, which typically emphasizes continuity in the diversity of life. However, delineating species poses challenges for evolutionary biologists, paleontologists, ecologists, and molecular biologists due to the limitations of traditional Linnaean classification methods [56].

Phylogenetic systematics and evolutionary taxonomy often assume continuity, leading to conclusions that life exhibits a characteristic pattern of continuity [56]. Methods such as phenetics and transformed cladistics produce data structures like phenograms and cladograms, positioning life forms at the tips of tree-like diagrams. Addressing these challenges requires a holistic approach, drawing from various studies on family-level taxa, such as those of red and giant pandas [17,23,74]. A comprehensive method for identifying discontinuity would aid scientists in studying this crucial aspect of life’s pattern. Moreover, it would facilitate clearer communication between proponents of both theories by providing a common framework [56]. The existing literature offers numerous examples of convergent evolution, underscoring the necessity for rigorous methodology in addressing these complexities [49,62].

Our methodology is rooted in the understanding that to discern discontinuity, one must possess the capacity to perceive continuity among groups of species because continuity and discontinuity are inherently intertwined. One cannot be observed without acknowledging the presence of the other. Moreover, group membership hinges on tracing continuity through common descent; therefore, the criteria for membership aim to delineate both the extent and limits of this continuity. These criteria have served as reliable tools for consistently identifying both continuity and discontinuity for researchers [96], which we will discuss in the subsequent sections.

I understand your concern. However, the question remains whether our separated creation model can be considered a variant of common descent from the perspective of its advocates. If the concept of nested hierarchies between programs is an essential point, then, as far as I’m concerned, our model provides a basis for discussing hierarchies without necessarily aligning with common descent.

For example, our methodology dismisses cladograms and phenograms as inconclusive evidence of evolutionary continuity. While these diagrams mimic the appearance of phylogenetic trees, they fall short in establishing genuine ancestor-descendant relationships within the data. Instead, we advocate for additional phylogenomic analysis to determine whether specific taxonomical groups should be classified separately and the gaps in the fossil record between these taxonomical groups are considered real, which diverges from evolutionary theory [109].

For instance, the common descent model lumps various taxa into only two broad categories, such as reptiles and mammals, which diverges from our model. Phylogenomic analysis can shed light on the accuracy of such groupings by examining potential conflicts between anatomically-based family trees and those inferred from molecular similarities across taxonomic groups [58].

Confirming this prediction would suggest that the nested patterns observed in anatomically-based family trees, particularly among diverse taxa such as birds, fish, reptiles, and mammals, may be better explained through a common design perspective rather than solely through the lens of Darwinian evolution.

The conflicts between anatomical classifications and molecular similarities challenge the traditional notion of common descent, which often categorizes taxa into broad groups based on shared anatomical features. Instead, it suggests that genetic evidence may reveal more complex relationships among taxa, potentially reflecting a common design rather than a linear evolutionary lineage. Confirming this prediction requires empirical testing through comparative analysis of anatomically-based family trees and molecular similarities among taxonomic groups.

Identifying morpho-molecular dissimilarities and/or lack of fossil intermediates among order- and family-level taxa

We can discern potential discontinuities between orders and families through the Baraminic Distance Correlation (BDC) method, which categorizes organisms based on their design features [77]. If a chain of positive and significant BDCs links all taxa, they are considered part of the same basic type [77]. Conversely, if negative correlations occur outside the group, with gaps significantly larger than intra-group differences, this indicates discontinuity [77].

Classical Multidimensional Scaling (CMDS) is another valuable tool in this process, visualizing and analyzing similarities and dissimilarities between object groups [77]. In baraminology, CMDS helps compare morphological features of various organisms to identify potential “basic types” based on shared design features [77]. Should these methods fail to reveal significant negative correlations, alternative approaches can uncover dissimilarities between orders and families [17,96]. However, Senter [77] identified several limitations and challenges with using baraminological methods to determine basic types:

Subjectivity in defining basic types: Criteria like anatomical similarity lead to varied interpretations.

Lack of consensus on criteria: Different researchers use diverse features, yielding inconsistent results.

Difficulty with transitional forms: Identifying transitional fossils or distinct kinds can be subjective.

Incomplete fossil record: Gaps hinder accurate assessment of morphological continuity.

Variation within baramins: Morphological diversity complicates distinguishing intra- and inter-basic types differences.

Lack of independent confirmation: Reliance solely on morphology may raise validity concerns without additional evidence.

In the case of pandas, k-mer signature analysis distinguished between the two species [17]. However, it did not show discontinuity between pandas and certain outgroup taxa, suggesting no common ancestor with those taxa. Consequently, they are not presumed to be basic types but are considered separate families. Nonetheless, separate families do not inherently equate to basic types or “suspected” basic types. To clarify, a basic type undergoes analysis thrice using the BDC and CMDS methods, while a suspected basic type is analyzed only once. These other analyses should help us overcome the challenges associated with these methods, which will be discussed in more detail.

Identifying functional differences among order- and family-level taxa in relation to their environment

If significant dissimilarities emerge between orders and families, the next step involves identifying functional disparities in relation to their respective environments. Comparative anatomical analysis serves as a crucial tool here, offering insights into the evolution and function of physiological structures [74]. Should this prove insufficient, we advocate for the inclusion of comparative physiology to elucidate the underlying mechanisms and adaptations governing these functions.

This represents a pivotal second stage in the process of determining basic types, as it enables the differentiation between homologous and analogous phenotypic traits [74]. Additionally, it offers a means to address any shortcomings or limitations inherent in the BDC and CMDS methods utilized for basic type determination [77].

In the case of pandas, comparative anatomical analysis alone sufficed to discern the structural and functional distinctions between the two species within the context of their ecological niches [74].

Make and test predictions related to the functional differences among order- and family-level taxa

Our model predicts that functional disparities between different orders and families, especially in relation to environmental adaptations, would be associated with convergent genetic mechanisms underlying phenotypic convergence traits, as seen in examples like the convergence observed between pandas (Reference [23]). This hypothesis can be tested using comparative genomics, and we anticipate identifying at least one adaptive gene and one positively selected gene in each basic vertebrate taxa (Reference [96]).

Adaptive genes would be validated through functional assays linking them to adaptive traits, while positively selected genes would be identified based on population genetic analyses that show signs of positive selection. To ensure accuracy, we will use stringent statistical controls, such as false discovery rate adjustments, and corroborate findings with independent datasets. The goal is to provide comprehensive sampling across taxa in orders and families, thus representing genetic diversity among vertebrate lineages. If this prediction holds, it suggests that some groups may have originated from separate “created kinds.”

Such findings could challenge traditional expectations within Darwinian evolution, which posits that taxa within vertebrate groups share a single common ancestor. Instead, the presence of adaptive and positively selected genes within separate groups suggests a potentially unique genetic adaptation within each group, supporting a more complex scenario than linear branching alone.

Examples of design trade-offs in nature are expected from our theory. Cancer would fall into this category because it reflects a trade-off between DNA repair and cell survival. This is our model of this:

After taxonomical vertebrate groups and a human were created, conserved structural features, such as the precise positioning of amino acid residues and metal cofactors, along with specific protein folding patterns, facilitated electron delocalization and quantum tunneling [57]. Over evolutionary time, non-random mutations, insertions, deletions, and HGT led to variations in the amino acid sequences of proteins involved in electron transfer reactions through quantum tunneling.

Subsequent changes in protein sequences resulted in corresponding alterations in protein structures, where even minor modifications in amino acid sequences could impact protein folding, stability, and interactions with other molecules [57]. These structural changes influenced the efficiency and specificity of electron transfer within the protein, with modifications enhancing electron transfer rates in one context potentially reducing specificity or stability in another context leading to design trade-offs.

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Darwin died before viruses were discovered. Owen died after viruses were discovered, but only by a few months, long before anything other than a brief article was published by a Russian.

So neither Darwin’s model nor Owen’s theory say anything at all about the origin of viruses.

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True, Darwin and Owen may not have specifically addressed viruses since they were discovered only after their time. However, this doesn’t negate my point, as the broader question of life’s origins—central to both of their theories—was indeed a topic of interest during their lifetimes. Although the specific details of viruses and their role in life’s origins were clarified later, the foundational concepts regarding the emergence and organization of life were very much present and relevant to their work.

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As mentioned above, Darwin never wrote about viruses. Also, nothing you wrote addresses the critique.

There is absolutely no reason why a designer would be forced to fit archetypes into a nested hierarchy.

And that definition is nonsense.

It’s my review of the paper, which you requested.

None of this addresses the critique.

That point needs evidence. You don’t supply any.

The correlation between morphological and sequenced based phylogenies is real and a fact. You need to address it.

You need positive evidence, not lack of evidence. There is absolutely no reason to believe the fossils we have in our collections are representative of all species that ever lived. All you have done is give excuses as to why you won’t accept any fossil as transitional. You have given no reasoning why standard evolutionary wouldn’t also produce discontinuities in living species, nor how you will measure discontinuities. It seems completely subjective. You can’t even give any criteria for determining what your groups are.

That doesn’t address the critique. Why is ~90% of the human genome accumulating mutations at a rate consistent with neutral drift?

It seems like you are just regurgitating what is in the paper with no understanding of the critiques nor the material in the paper, much less the biology behind all of it.

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It does until you rephrase your point so that it isn’t based on what their theories said about the origins of viruses.

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True, as I mentioned in response to @Roy, Darwin and Owen may not have specifically addressed viruses, since they were discovered only after their time. However, this doesn’t negate my point, as the broader question of life’s origins—central to both theories—was indeed a relevant topic during their lifetimes. While details about viruses emerged later, the foundational concepts regarding life’s origin and organization were still present in their work. More importantly, as I mentioned earlier, the virus-first hypothesis offers insights that Darwin’s model, which primarily accounts for processes post-origin of life, may not fully encompass. This limitation, in my view, reinforces the relevance of alternative models that can integrate these early stages.

I agree, but I don’t see how this refutes our overall argument. As I mentioned before, nested patterns can arise through convergent co-option and horizontal gene transfer (HGT). In synthetic biology, for example, viruses are used to design organisms, paralleling patterns seen in nature. However, viruses can also disrupt hierarchical patterns, such as RNA viruses that don’t fit within the Tree of Life due to their lack of cellular structure and polyphyletic origins. Additionally, HGT can complicate phylogenetic relationships by introducing genes from diverse sources into a single genome, supporting our view that Owen’s theory better accommodates both nested patterns and their exceptions.

I requested an endorsement on our preprint server, rather than a formal review. Initially, you mentioned that endorsement might follow if I addressed the criteria you outlined. As I believe I’ve met these original criteria, I’m hopeful for an endorsement based on our discussion, even if some new criteria remain unsatisfied in your view.

I intended to provide context for the specific points I planned to address in the following responses.

Here is the evidence supporting a common design perspective in phylogenetic analysis, particularly relevant to the debate on species-level versus broader taxonomic comparisons:

C. Parins-Fukuchi, G.W. Stull, S.A. Smith, Phylogenomic conflict coincides with rapid morphological innovation. Proc. Natl Acad. Sci. U. S. A. 118 (2021).

I agree, and this is why we propose a holistic approach. Our criteria are as follows:

  1. Identify morpho-molecular dissimilarities or absence of fossil intermediates among order- and family-level taxa.
  2. Determine functional differences among these taxa, especially in relation to environmental adaptations.
  3. Test predictions related to these functional differences in a systematic, comparative approach.

This structured methodology aims to reduce subjectivity by establishing clear criteria for assessing discontinuities.

I apologize for any misunderstanding. My previous response was focused on addressing a specific part of your objection, particularly regarding the potential for deleterious mutations. You mentioned, “there needs to be an explanation of why changing the sequence can never be deleterious.” Our theory does not claim that every sequence change is non-deleterious; we recognize that environmental shifts and other factors can render certain mutations harmful, and that some deleterious mutations might still provide an adaptive benefit under specific conditions. Our model also acknowledges that definitions of function vary across contexts, which influences how mutations are interpreted.

Regarding the neutral drift observed in approximately 90% of the human genome, we see this as potentially compatible with our model in a few ways. For example, we propose that some genomic regions may be selectively neutral or have low functional constraint, allowing mutations to accumulate without deleterious effects. Such regions may contribute to genetic diversity and adaptability within a designed framework, where flexibility in certain sequences supports population-level resilience over time.

I recognize that additional work is needed to directly test and refine these ideas within our model, particularly to better understand how neutral drift data might inform or align with a common design perspective. Thank you for highlighting this as an area to explore further.

I believe the issue may stem from assuming that all three viral origin models are mutually exclusive, which I was not implying. Owen’s framework does not restrict the origin of life and species into entirely separate domains, unlike Darwin’s. By clarifying rather than rephrasing, I hope to convey that this integration of origins is foundational in Owen’s model, unlike Darwin’s approach.

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As a reviewer, I am telling you that your view is wrong.

The fact that you don’t understand how you are contradicting yourself is another worrisome trend.

What’s the title of the thread?

How does rapid evolution from common ancestors support your perspective?

That’s not positive evidence. It should just be removed.

Evolution produces functional differences.

If they contributed to adaptation then there would be selection against deleterious mutations in those regions, and they wouldn’t accumulate mutations neutrally.

What you need to explain is how a sequence can have function and yet no changes to that sequence are deleterious. Remember, you are saying that 80% of the genome has function. As Graur put it:

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I appreciate your direct feedback. Could you provide specific details on how and why you find my view incorrect? That would help me make targeted improvements. What, specifically, do you see as the main flaws in my argument?

I understand that it may seem contradictory. However, viruses can serve diverse roles, as demonstrated by human-engineered viruses used for multiple functions. Similarly, in nature, horizontal gene transfer (HGT) can disrupt nested hierarchies, especially when it occurs above the family level. Unlike non-random mutations or convergent co-option, HGT introduces genetic material across different lineages, which can create patterns that conflict with strictly nested hierarchies.

In post 78 on this forum, I said…

I’m happy to summarize the core concepts from the article here. However, for the depth and nuance that may answer your specific questions, I would recommend reading the sections I previously mentioned. Alternatively, I’d appreciate an endorsement on the preprint server if you want me to put the extra effort in our discussion and give into your demands of copying and pasting large excerpts repeatedly. You can learn more about endorsements here: Endorse a Preprint - OSF Support

Well, it helps in directing research by providing a starting point.

While both evolutionary and design models account for convergence, the models differ in frequency and mechanisms. For instance, a study found that evolution at the molecular level is often unpredictable and irreversible (Reference [111]). This study examined purifying selection, a form of evolution favoring mutations with minimal effects in a stable environment. This contrasts with adaptive evolution, where mutations increase an organism’s fitness in changing conditions. Since purifying selection is more common than adaptive selection, this distinction may have implications for the extent of functional convergence we would expect under each model.
This leads me to address another related point next…

Identifying adaptive and positively selected genes within separate taxa suggests that distinct genetic adaptations could be evolving independently within each group. This supports a more complex scenario than common descent, where taxa diverge through gradual, linear modifications. It implies that evolutionary patterns may be shaped by independent genetic responses to specific environmental pressures rather than only through a singular ancestral lineage.

To address this, could you clarify which definition of function you are using? This will help me provide a more accurate explanation, as functional definitions vary across disciplines and influence how we interpret genetic sequences and their roles.

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  1. Forget Darwin. He died a long time ago. You need to be looking at the modern theory of evolution.
  2. Any explanation needs to stand on its own, not simply be there if you think another explanation is lacking.
  3. There are obviously attempts to explain the origin of viruses in the modern theory of evolution, so I can’t see how you can jump to the conclusion that it is impossible for viruses to have evolved.

HGT is random mutation because the mechanisms that transfer DNA are not capable of determining if the transferred DNA will be beneficial. Viral insertion is random with respect to fitness. Also, I wouldn’t even consider viral integration to be HGT. I reserve that for “normal” genes.

In the very first post you said:

“We have decided to submit our article to a preprint server and Peer Community In (PCI) for consideration and review, following the advice of the Royal Society Open Science journal:”

  1. That doesn’t address what I said.
  2. You don’t show how the mechanisms and frequency differs between the two models.
  3. Purifying selection removes deleterious mutations.
  4. You don’t show how purifying selection being more common than adaptive selection impacts functional convergence.

All of it is either irrelevant or wrong.

Common descent is not gradual evolution. They are two separate things. Common ancestry is sharing an ancestor. How evolution took place between the ancestor and descendant populations is a separate issue.

A DNA sequence has function if it impacts the fitness of the organism.

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Here is our proposed synthesis, which we invite critique on to disprove or provide specific counter-evidence against:

  • Viruses as Ancient Entities and Continuous Contributors to Evolution:
    We propose that viruses could represent ancient replicators (virus-first) as well as simplified cellular forms (reduction) that evolved alongside cellular life. Over time, cellular organisms may have shed cellular machinery, evolving into viruses, while escaped genetic material from cellular genomes (escape model) continually adds to the viral pool. Together, these pathways contribute to a diverse and ancient viral lineage.
  • Horizontal Gene Transfer and Genetic Diversity:
    Viral-mediated horizontal gene transfer (HGT) facilitates genetic exchange across unrelated lineages, which plays a significant role in nutrient-limited ecosystems. By functioning as genetic carriers, viruses enhance ecosystem health and genetic diversity, enabling prokaryotic biomass production and supporting biogeochemical cycles. This viral “genetic shunt” bolsters diversity and resilience across life forms.
  • Viruses as Modular Entities in Evolutionary Processes:
    Acting as genetic reservoirs, viruses recombine and transfer beneficial genes, thereby supporting adaptability among organisms across ecosystems. Studies, such as those from the University of Connecticut, indicate that HGT introduces genetic “signatures” resembling those of common ancestry, blurring traditional descent lines. This supports a synthesis of virus-first, reduction, and escape models, emphasizing viruses’ evolutionary roles and design contributions across biological systems.

This model suggests that viruses do not fit neatly into a single origin narrative but instead play overlapping roles in the evolution and ecology of life. Integrating all three origin models allows for a broader understanding of viruses’ roles across evolutionary time.

I have not yet found a Darwinian evolutionary model that fully explains virus origins, particularly from the virus-first perspective, as this typically involves prebiotic conditions and the early stages of life’s origins. Darwinian frameworks mainly address viral diversification but do not account for the origin of viruses before cellular life. Could you provide a reference or model that demonstrates this, as I would be interested in understanding how current theory accounts for virus-first origins?

While some forms of HGT may resemble random mutation, other types, such as horizontal regulatory transfer (HRT) and biased gene transfer, do show signs of non-random mutation with respect to fitness, even within your preferred definition of function. Studies demonstrate these forms of HGT can introduce regulatory rewiring in bacteria and other organisms, which has measurable fitness impacts. Therefore, treating HGT and random mutation as strictly equivalent might oversimplify the mechanisms by which genetic material is exchanged across lineages.

Transfer of noncoding DNA drives regulatory rewiring in bacteria | PNAS

Biased gene transfer mimics patterns created through shared ancestry | PNAS

This specifically refers to PCI, which requires authors to first post on a preprint server before submitting for review. I just wanted to clarify this as part of our submission process to ensure transparency.

I guess I don’t understand your previous objection then. How about you elaborate on your point on evolution producing functional differences.

I understand the distinction between common descent and gradual evolution, and I appreciate your clarification. My reference to phylogenetic conflicts, however, was intended to highlight how these conflicts may support a common design model over a universal common ancestry model and thus support nested patterns between species from a design and creationist perspective.

The study’s findings are challenging to explain under the assumption that all life evolved from a single common ancestor through numerous small, random mutations over millions of years. While Darwinian evolution effectively accounts for modest differences among closely related species, the broader similarities and differences observed across diverse plant and animal types may align more naturally with a model where a common designer reuses genetic information for shared functions, while introducing unique sequences for novel adaptations.

In this view, the persistent difficulties in resolving a single, cohesive tree of life suggest that such a tree may not exist as expected by common descent models. Instead, these patterns could be more consistent with a common design model, where genetic similarities arise from intentional reuse rather than a shared evolutionary origin.

We have discussed this previously. We did not assert that every functional element impacts fitness in a strict sense. Our model aligns with findings from the ENCODE project, which identified biochemical activity in about 80% of the human genome. This exceeds the 51% threshold proposed by advocates of Owen’s theory, suggesting that a significant portion of noncoding DNA has regulatory or context-dependent functions rather than strict selection-based utility.

We anticipate that a substantial portion of ERVs and other noncoding elements have roles beyond traditional definitions of function as well. As such, we maintain an inclusive view of function to accommodate findings across evolutionary biology and genomic studies.

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All of this is governed by evolutionary mechanisms, so I’m not sure how you are relating this to design.

I would also point out that only a small fraction of adaptations involve viral sequence.

You are saying it is impossible for viruses to have evolved. Not having a full explanation doesn’t lead to that conclusion.

HGT and HRT can transfer deleterious changes that are then selected against. I see nothing in these mechanisms that can determine which genes an organism needs and then transfer only those genes. For example:

Mutations change function and are then passed through selection. It’s standard evolutionary theory.

The reference you cite states that these conflicts are “the result of coincident population processes (e.g., changes in population size, rapid speciation, and incomplete lineage sorting)”. We expect noise in phylogenetics because of these processes, and others. That is why I spoke of a correlation between phylogenies, something like this:

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Not all dots fall on the line of best fit, the correlation line. There is noise, but there is a very obvious relationship between factors. What you would need to explain is the correlation, the signal. Pointing to just the noise is an incomplete interpretation of the data.

This is yet another argument from incredulity, a logical fallacy.

Your model doesn’t align with the ENCODE project. You have just adopted its findings and its nonsense definition of function. There’s nothing in your model that predicts a certain percentage of a genome should be functional.

Only if you use a nonsense definition of function.

Only when using a nonsense definition of function.

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Natural selection alone cannot fully explain the origin of life or the virus-first hypothesis because it presupposes the existence of self-replicating entities, which apparently did not exist under prebiotic conditions. Natural selection relies on variation and differential survival among replicators, yet prebiotic chemistry lacks populations of such entities capable of replication and competition. This absence undermines the application of Darwinian mechanisms in the context of life’s origin.

In contrast, design provides a plausible explanation for the origin of functional structures like viruses. As humans demonstrate, intelligent agents are capable of creating viruses and other complex molecular structures. This observable causation supports a design-based interpretation of complex adaptations. Additionally, the presence of viral sequences in a small fraction of adaptations does not preclude their relevance to the discussion; rather, it highlights the need for a more comprehensive framework, such as Owen’s theory, to explain both functional innovation and broader patterns of life.

I am not claiming that viruses cannot evolve but rather that their origins cannot be explained by unguided processes alone. Prebiotic environments, as understood, lacked complex biological machinery such as enzymes, which are critical for replication and cellular function. Molecules in these environments would have to form spontaneously and assemble into highly specific structures, such as nucleotide sequences or functional proteins, without guidance.

This is where Owen’s natural law theory provides a better explanation. Unlike natural selection, which applies only after self-replicating systems are established, Owen’s theory offers a mechanism that operates both before and after life’s emergence. It accounts for the observed complexity in viral origins and integrates them within a broader design framework.

Allow me to clarify my argument further now:

  • Premise 1: Effects observed in past events should be explained by causes known from uniform experience to produce similar effects, per Lyell’s principle of causation, supported by Darwin.
  • Supporting Evidence: Humans can design and create viruses, showing that intelligent agents are capable of producing complex viral structures through direct design.
  • Premise 2: Design frameworks more directly mirror the processes we observe in human creations of complex structures, making them a more probable method than guided evolutionary frameworks for a universal designer.
  • Conclusion (Inductive): It is therefore reasonable to expect that a universal common designer would develop life and species through a direct design framework rather than a guided evolutionary framework, as this approach aligns with causation principles based on observable, direct design effects.

The study I referenced found that the greatest instances of gene-tree conflict corresponded with high rates of morphological innovation and occurred episodically throughout Earth’s history. The researchers concluded that both phenomena likely share the same causal processes. During periods of high gene-tree conflict, rapid population changes (e.g., growth or collapse) are often inferred.

This aligns with a common design framework, which predicts episodic bursts of innovation rather than slow, continuous changes. Such patterns align with the predictions of discrete design events or stasis punctuated by sudden appearances, as opposed to gradual changes predicted by traditional Darwinian models.

For instance, while Darwinian evolution effectively accounts for modest differences among closely related species, the broader similarities and differences observed across diverse plant and animal types may align more naturally with a model where a common designer reuses genetic information for shared functions, while introducing unique sequences for novel adaptations.

Regarding phylogenetic noise, a design model can both anticipate and explain these patterns. Design can accommodate nested hierarchies, creating observed correlations in phylogenetic relationships, while also accounting for exceptions due to convergent co-option and horizontal gene transfer (HGT). For instance, RNA viruses, which lack cellular structure and have polyphyletic origins, disrupt the Tree of Life, while HGT can introduce genes from diverse sources into a single genome. This pattern aligns with Owen’s theory, as it suggests that a designer may reuse functional genetic structures across unrelated lineages, creating both nested patterns and their exceptions.

To clarify, this argument is not based on incredulity but rather on observed data that indicate episodic, high-intensity changes in gene trees and morphology that align with design-based predictions.

While Darwinian evolution predicts functional differences and convergence, these predictions differ significantly when applied to higher taxonomic levels such as orders and families. Darwinian models typically treat these taxa as clades derived from shared ancestors, whereas Owen’s theory identifies and expects them to be basic types or created kinds.

For example, the red panda was historically grouped with the giant panda based on morphological similarities, such as their shared “false thumb” and dietary preferences. However, genetic analysis revealed that they are not closely related, supporting their classification as distinct families. This divergence between morphological and genetic evidence is consistent with Owen’s predictions of independent creation at the family or order level.

The key distinction is that Owen’s model predicts functional convergence within separate taxa, such as orders and families, as evidence of design rather than shared ancestry. Confirmation of this prediction comes from common descent examples that were later discovered and reclassified cases of convergence between the order and family levels.

The ENCODE project found biochemical activity in roughly 80% of the human genome, challenging the traditional view of non-coding regions as “junk DNA.” While Owen’s theory does not predict a specific percentage of functional genome content, it anticipates that much of the genome, including elements like ERVs, serves regulatory or context-dependent functions.

ENCODE’s broader definition of function is scientifically valid because it identifies biochemical activity as a marker of potential utility, irrespective of evolutionary history. This approach aligns with Owen’s theory, which focuses on identifying design through observable biochemical functionality rather than inferring utility strictly from selection processes.

Mattick and Dinger have noted that debates over functionality in the genome often reflect underlying philosophical disagreements between design-based and Darwinian perspectives. They highlight that increasing evidence for functionality in non-coding regions, as shown by ENCODE, undermines the “junk DNA” narrative and supports the notion of intentional design. This perspective is consistent with Owen’s theory, which anticipates functional roles for non-coding DNA as part of a designed framework.

Furthermore, ENCODE’s findings support our mechanisms—convergent co-option, HGT, and non-random mutations—by demonstrating how biochemical activity contributes to genomic complexity. These processes challenge the sufficiency of random, unguided mechanisms and point to an integrated system consistent with design. While evolutionary frameworks emphasize fitness-based utility, Owen’s model integrates causal necessity, highlighting that constants like the fine-structure constant enable the stability necessary for both life and consciousness to function.

In summary, ENCODE’s definition of function is relevant to design because it emphasizes observable biochemical activity, a key marker of intentionality in Owen’s framework. While fitness impact remains significant in evaluating common descent predictions, the causal definition aligns better with design models by focusing on direct biochemical evidence of functionality. This distinction is central to understanding the model’s implications and reinforces the validity of ENCODE’s findings in supporting a design-based perspective.

John S. Mattick and Marcel E. Dinger, “The Extent of Functionality in the Human Genome,” The HUGO Journal 7, no. 2 (2013): doi:10.1186/1877-6566-7-2.

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… so I gather that a lot of your ‘challenge’ to what you anachronistically keep labeling as “Darwinian” models is over the issue of abiogenesis - not common ancestry or evolution of any kind. And yet even Darwin was not (to my knowledge) attempting to address anything like the process of abiogenesis as we recognize it today. Shoot, Darwin didn’t even know about genetics or DNA yet! That isn’t to say that there hasn’t been significant progress on the entirely separate front of abiogenesis - I guess there probably has been, though if I’m not mistaken, it could hardly be called any sort of settled consensus to nearly the extent that evolution has been settled.

Now … I’m not pretending to follow the suspiciously large volume of all your responses - liklihoods of copy/paste and AI filler aren’t helping to motivate me overmuch in that direction. But in order to help you avoid those sorts of suspicions, I have a challenge for you, @RTBsupporter. And it is this. Do you see how a lot of what @T_aquaticus writes is a concise, highly readable response to specific things you’ve claimed? Which make his posts seem very readable / understandable to the lay person here who likely doesn’t have the background in genetics to delve into these things. So when I see lots of long wordy response, it automatically triggers a reactionary suspicion that weak and unsupported ideas are needing to be disguised and hidden behind a fog of impenitrable verbiage (to recall a recent C&H cartoon I was reminded of). The challenge is this: is there a sufficiently good germ of an idea, and are you a good enough non-AI communicator to communicate that idea well? Not that you can’t appeal briefly to longer stuff for those who do wish to delve a lot deeper (you’ve done plenty of that) - but can you give good summary responses like T does?

Obviously this already got way to wordy in my own turn here - so … maybe to follow my own advice … 'nuff said.

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I recommend starting at the beginning of this forum’s discussion, focusing on my exchange with T up to at least post 80. This will provide the context for why I’ve been copying and pasting large excerpts here. It’s important to review that part of the discussion to fully understand the reasoning behind it.

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Super ironic explanation, given an earlier explanation of why copy and pasting wouldn’t have been… what’s the word… helpful?

The coincidence of technological and philosophical singularities… alongside of understanding what ‘creation’ as a non-local singularity looks like… is going to be something

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Based on the content of the paper and how much it brings up theological content, you are probably better off submitting it to a theology journal or philosophy journal rather than a scientific journal. There are some academic theological journals that focus on the intersection of science, faith, and metaphysics that would probably find this topic very compelling.

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That’s an argument from incredulity and ignorance, two logical fallacies. You also fail to explain how design is a plausible origin for viruses.

It’s an explanation without any evidence.

It seems that common design predicts anything and everything, including what we would expect from evolutionary mechanisms. This prediction comes from nowhere, and is not supported by any evidence.

A nested hierarchy is exactly what we would expect from common ancestry and evolutionary mechanisms. Sorry, but you have it completely backwards. We would not expect a nested hierarchy from common design because parts can be reused in ways that violate a nested hierarchy, just as happens in human designs.

The problem for the design model is that it can accommodate anything which is what makes it an unscientific model.

Yes, there are species that are hard to put into a phylogeny because of convergence and different features. However, this should be the norm if the design model is true, but it isn’t. Again, you focus on the noise while ignoring the signal.

You are claiming these stretches of DNA are functional, not just potentially functional. You need more evidence than what ENCODE has provided.

That would require you to present this evidence, which you haven’t done.

That’s word salad.

How?

It’s relevant because it emphasizes something you want to be true in your framework? Bias much?

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By the way, this thread is a perfect demonstration of the wisdom of editors saying that they can’t find any reviewers for this kind of paper. Telling authors that their paper is pseudoscience just invites endless argument.

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DeadHorse

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If want a more detailed explanation that avoids logical fallacies, just read this review article:

M. W B, R. A S, M. P, B. F, Cellular and Natural Viral Engineering in Cognition-Based Evolution. Commun. Integr. Biol. 16, 2196145 (2023).

If the design goals, particularly in the context of viruses, are to optimize complex organisms for survival, reproduction, and integration into their environments, then nested hierarchies would naturally emerge as a byproduct of intentional design. This structured complexity reflects the efficiency and adaptability seen in human-engineered systems, where components are often organized hierarchically to maximize functionality and integration. Therefore, the observed nested hierarchies in biological systems align with the expectations of a design framework rather than contradicting it.

However, this is just a hypothesis at this stage.

Owen attributed nested patterns to an inherent structural order driven by his concept of the polarizing force, with variations and adaptations occurring within this framework due to an adaptive force. The law of entropy exemplifies this polarizing and adaptive force in action, as it explains how evolution emerges with functional, self-organizational order through energy dispersal by gradient reduction, serving as the motive force behind hierarchical organization [1]. This universal law transcends the boundary between animate and inanimate systems, as both evolve through energy flows toward stationary states relative to their surroundings [1].

[1] A. Annila, E. Kuismanen, Natural hierarchy emerges from energy dispersal. Biosystems 95, 227–233 (2009). [Epub 2008 November 6]. PMID: 19038306.

The proposed model of non-local self-collapse (SC) of quantum wave functions within microtubules and convergent co-option provides a mechanistic explanation for the development of vertebrate created kinds from stem metazoans. This design framework predicts specific events in evolutionary history, such as the emergence of vertebrate Hox clusters, while accommodating patterns like stasis and sudden appearances in the fossil record.

1. Unique Predictions of the Design Model

Unlike evolutionary mechanisms, the design framework predicts the following:

  1. Quantum Coherence in Hox Clusters: Vertebrate Hox clusters should exhibit patterns of quantum coherence within microtubules, observable using advanced imaging or spectroscopy techniques. Such coherence would facilitate efficient quantum computation and self-collapse, a process absent in non-vertebrates.
  2. Bias in Genetic Reuse: Comparative analyses of reused genetic elements across vertebrate groups should reveal a functional bias toward optimizing specific adaptations, inconsistent with stochastic evolutionary mechanisms.

These predictions distinguish the design framework from evolutionary models, providing falsifiable criteria for empirical testing.

2. Evidence from the Fossil Record

The fossil record supports the design model through patterns of stasis and sudden appearances:

  • Stasis: Once design objectives are achieved, further modifications are unnecessary, leading to prolonged periods of stability.
  • Sudden Appearances: Discrete design events result in the rapid emergence of novel taxa, as seen in the fossil record, challenging the gradualism expected from Darwinian evolution.

For example, the sudden appearance of vertebrate body plans and the rapid rebound of ecosystems after extinction events align with discrete, goal-oriented design processes rather than continuous evolutionary change.

3. Addressing the Falsifiability Concern

The design model is not unfalsifiable, as it does not accommodate “anything and everything.” Specific tests could challenge the framework:

  • Test 1: If transitional forms are found with partial, non-functional Hox gene duplications, this would contradict the prediction that design produces fully functional systems at every stage.
  • Test 2: If quantum coherence patterns are absent in vertebrate Hox clusters, the proposed SC mechanism would be invalidated.

These falsifiable predictions ensure the model adheres to scientific standards of testability and empirical validation.

4. Conclusion

The design model predicts specific, testable outcomes, such as the role of quantum coherence in vertebrate evolution and the functional reuse of genetic elements. By aligning with patterns observed in the fossil record and providing mechanisms for key evolutionary events, this framework offers a robust alternative to traditional evolutionary models.

If we lacked any background knowledge of the designer, your point would hold. However, Owen’s theory addresses this by providing insights into the mechanisms, motives, and identity of the designer. This sets it apart from other design theories, such as those advocated by the Discovery Institute, which lack this specificity. By grounding the theory in established scientific principles and historical context, Owen’s approach is more rigorous and avoids the pitfalls of unfalsifiability.

1. Mechanism: How Does the Model Work?

The proposed model integrates quantum biology, findings on noncoding DNA, and experimental evidence to suggest that consciousness actively guides genome functionality:

  • Mechanism: Consciousness interacts with quantum biological mechanisms, such as microtubule self-assembly, to influence genomic functionality. This interaction may occur through quantum coherence patterns that regulate non-random mutations and gene expression.
  • Experimental Support: Studies have shown that microtubules assemble under electromagnetic signals, demonstrating their sensitivity to external influences. This provides a basis for exploring how consciousness may influence these structures.

Testable Prediction: Quantum coherence patterns in microtubules should correlate with specific genome regulatory functions. This can be tested using advanced imaging and spectroscopy techniques during cellular processes.

2. Evidence for Functional Noncoding DNA

Evidence for noncoding DNA functionality extends beyond ENCODE, including:

  • Long Noncoding RNAs (lncRNAs): Studies have identified thousands of functional lncRNAs involved in transcriptional regulation, cellular differentiation, and disease processes (e.g., the RIKEN atlas identified 19,200 functional lncRNAs).
  • Pseudogenes: The ceRNA hypothesis demonstrates that pseudogenes regulate gene expression by acting as molecular sponges for microRNAs, providing clear functional roles.
  • Independent Findings: Mechanisms that minimize nonfunctional interactions in the genome, as demonstrated by Qian and Kussell, further support the genome’s organized complexity.

By distinguishing between biochemical activity and biological function, these studies validate the claim that significant portions of noncoding DNA have essential roles.

3. Addressing Claims of Bias

This model is not biased toward supporting the design framework but instead relies on falsifiable predictions and independent evidence:

  • Engagement with Conflicting Data: Some studies argue that much of the genome is nonfunctional. However, this interpretation often depends on definitions of “function.” The causal role definition used here focuses on experimentally verified relationships, such as those demonstrated in the ceRNA hypothesis.
  • Falsifiability: If ERVs are found to lack regulatory or context-dependent functions in over 50% of cases, this would challenge the model’s prediction.
  • Relevance of the Fine-Structure Constant: The fine-structure constant underpins the stability necessary for life and consciousness, supporting the idea that constants facilitating existence also influence evolutionary processes.