Rise (and fall?) of the atom.

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The truth has fallen.

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The dragon as merchant.

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Physics can rehabilitate OOL science?

Origin of Life Is Not Reducible to Physics

Evolution News @DiscoveryCSC

 

 

Yesterday, we critiqued a proposal by Eugene V. Koonin and three colleagues who presented an expanded theory of evolution as “multilevel learning.” (See, “Evolution Is Not Like Physics.”) The proposal commits the fallacy of equating the properties of biological “laws of evolution” with those of physics, and borders on vitalism, which undermines their goal of naturalizing evolution. The proposal was published in two papers in PNAS last month. This time, we look at the second paper that takes their proposal to the special case of the origin of life. Their attempt to incorporate thermodynamics into a highly negentropic process is sure to provoke interest.

From Vanchurin, Wolf, Koonin, and Katsnelson, “Thermodynamics of evolution and the origin of life”:

We employ the conceptual apparatus of thermodynamics to develop a phenomenological theory of evolution and of the origin of life that incorporates both equilibrium and nonequilibrium evolutionary processes within a mathematical framework of the theory of learning. The threefold correspondence is traced between the fundamental quantities of thermodynamics, the theory of learning, and the theory of evolution. Under this theory, major transitions in evolution, including the origin of life, represent specific types of physical phase transitions. [Emphasis added.]

How Can Nature Learn?

Perceptive readers will want to know how they deal with several well-known issues: (1) probability, (2) entropy increase, and (3) harmful byproducts. The authors have already presented their view of the universe as a “neural network” in which natural selection operates at multiple levels, not just in biology. The only neural networks that any human has observed coming into existence were designed by a mind. How, then, can physical nature learn things?

Under this perspective, all systems that evolve complexity, from atoms to molecules to organisms to galaxies, learn how to predict changes in their environment with increasing accuracy, and those that succeed in such prediction are selected for their stability, ability to persist and, in some cases, to propagate. During this dynamics, learning systems that evolve multiple levels of trainable variables that substantially differ in their rates of change outcompete those without such scale separation.

The vitalistic tendencies in this proposal become evident where they claim that nonliving entities are able to predict, train, and compete. They are further evident when the environment can select them according to specific criteria. How do Koonin and his colleagues know this happens? Just look around: there are atoms, stars, and brains that survived the competition by natural selection. Their existence confirms the theory. This is like the anthropic principle supporter who says, “If the universe weren’t this way, we wouldn’t be here to talk about it.”  

To deal with the entropy problem, the authors say that learning decreases entropy. They add a second variable Q to the entropy equation that allows them to overcome the problem. “Q is the learning/generalized force for the trainable/external variables q.”

In the context of evolution, the first term in Eq. 3.1 represents the stochastic aspects of the dynamics, whereas the second term represents adaptation (learning, work). If the state of the entire learning system is such that the learning dynamics is subdominant to the stochastic dynamics, then the total entropy will increase (as is the case in regular, closed physical systems, under the second law of thermodynamics), but if learning dominates, then entropy will decrease as is the case in learning systems, under the second law of learning: The total entropy of a thermodynamic system does not decrease and remains constant in the thermodynamic equilibrium, but the total entropy of a learning system does not increase and remains constant in the learning equilibrium.

Very clever; introduce a magic variable that allows the theory to avoid the consequences of the second law. Entropy increases overall (which must happen) but can stabilize or decrease locally in an evolving system, like a warm little pond.

The maximum entropy principle states that the probability distribution in a large ensemble of variables must be such that the Shannon (or Boltzmann) entropy is maximized subject to the relevant constraints. This principle is applicable to an extremely broad variety of processes, but as shown below is insufficient for an adequate description of learning and evolutionary dynamics and should be combined with the opposite principle of minimization of entropy due to the learning process, or the second law of learning (see Thermodynamics of Learning and ref. 17). Our presentation in this section could appear oversimplified, but we find this approach essential to formulate as explicitly and as generally as possible all the basic assumptions underlying thermodynamics of learning and evolution.

Special Pleading with Handwaving 

If this sounds like special pleading with handwaving, watch how they take a wrong turn prior to this by ascribing vitalistic properties to matter:

The crucial step in treating evolution as learning is the separation of variables into trainable and nontrainable ones. The trainable variables are subject to evolution by natural selection and, therefore, should be related, directly or indirectly, to the replication processes, whereas nontrainable variables initially characterize the environment, which determines the criteria of selection.

Assume a replication process. It’s like a can opener. It allows them to visualize endless things most beautiful emerging from the can if they had the opener. Theoretically, trainable variables q overcome the increasing entropy generated by the nontrainable variables x if the probability distribution p(x|q) favors q. “We postulate that a system under consideration obeys the maximum entropy principle but is also learning or evolving by minimizing the average loss function U(q),” they say. Natural selection, or learning, does that. Therefore, life can emerge naturally. 

Convinced? They derive their conclusions with some whiz-bang calculus, but clearly if a magic variable q is inserted, the derivation becomes unreliable even if the operations are sound. For instance, if you define q as “a miracle occurs,” then of course you can prove that life is an emergent property of matter. At that point, further sub-definitions of q into different categories of miracles fail to provide convincing models of reality. Watch them define learning as a decrease in entropy:

If the stochastic entropy production and the decrease in entropy due to learning cancel out each other, then the overall entropy of the system remains constant and the system is in the state of learning equilibrium… This second law, when applied to biological processes, specifies and formalizes Schrödinger’s idea of life as a “negentropic” phenomenon. Indeed, learning equilibrium is the fundamental stationary state of biological systems. It should be emphasized that the evolving systems we examine here are open within the context of classical thermodynamics, but they turn into closed systems that reach equilibrium when thermodynamics of learning is incorporated into the model.

Further handwaving is seen in their definition of “evolutionary temperature” as “stochasticity in the evolutionary process” and “evolutionary potential” as “a measure of adaptability.” Does anyone really want to proceed hearing them compare a population of organisms to an ideal gas?

The origin of life can be identified with a phase transition from an ideal gas of molecules that is often considered in the analysis of physical systems to an ideal gas of organisms that is discussed in the previous section.

A Cameo by Malthus

Reality left the station long ago. Malthus makes a cameo appearance: “Under the statistical description of evolution, Malthusian fitness is naturally defined as the negative exponent of the average loss function, establishing the direct connection between the processes of evolution and learning.” Learning solves every problem in evolution: even thermodynamics! Tweaking Dobzhansky, they say, “[n]othing in the world is comprehensible except in the light of learning.”

The key idea of our theoretical construction is the interplay between the entropy increase in the environment dictated by the second law of thermodynamics and the entropy decrease in evolving systems (such as organisms or populations) dictated by the second law of learning.

What is this “second law of learning”? It’s Vanchurin’s idea that variables can be defined as ones that “adjust their values to minimize entropy.” A miracle happens! Minds can do this; but matter? Sure. It’s bound to happen.

The origin of life scenario within the encompassing framework of the present evolution theory, even if formulated in most general terms, implies that emergence of complexity commensurate with life is a general trend in the evolution of complex systems. At face value, this conclusion might seem to be at odds with the magnitude of complexification involved in the origin of life [suffice it to consider the complexity of the translation system] and the uniqueness of this event, at least on Earth and probably, on a much greater cosmic scale.Nevertheless, the origin of life appears to be an expected outcome of learning subject to the relevant constraints, such as the presence of the required chemicals in sufficient concentrations. Such constraints would make life a rare phenomenon but likely far from unique on the scale of the universe. The universe is sometimes claimed to be fine-tuned for the existence of life. What we posit here is that the universe is self-tuned for life emergence.

We’re Here, Aren’t We?

Koonin’s colleagues never get around to solving the extreme improbabilities for getting the simplest building blocks of life by chance. They never discuss harmful cross-reactions, which are certain to occur due to known chemical laws. And they wave the entropy problem away by inserting magic variables that they define as systems that “adjust their values to minimize entropy.” These systems also magically possess memories! How do they know that? Well, neural networks have them, and life has them. Genes must have evolved to be the carriers of long-term memory. After all, we’re here, aren’t we?

Evidently, the analysis presented here and in the accompanying paper is only an outline of a theory of evolution as learning. The details and implications, including directly testable ones, remain to be worked out.

Indeed.

 

On mapping the boundaries of evolutions.

How Much Can Evolution Really Accomplish?

Eric H. Anderson

 

 

Editor’s note: In 2020, Michael Behe published A Mousetrap for Darwin, a collection of his essays and responses to critics. Professor of biochemistry Laurence Moran argued that Behe had misinterpreted evidence and had misunderstood the significance of chloroquine resistance. This is the first in a two-part response.

In 2007, biochemist Michael Behe had the temerity to ask a question — a question that should have been asked with repeated and urgent sincerity by all biologists since the ink from Darwin’s quill first dried on his manuscript: What can evolution actually accomplish?

The question is at once reasonable and utterly crucial to the evolutionary story. Yet, for the most part it has been ignored in the history of evolutionary thought. The deeply held assumption of nearly all evolutionists is that evolution can do everything. After all, we’re here aren’t we! So there is little point in even asking the question. To be sure, occasional lip service has been paid to this inquiry over the decades, but such efforts typically descend into a question-begging exercise that simply assumes evolution must have this great creative power. Again, we’re here, and so even if we don’t understand the precise mechanisms of evolution, even if we’re still trying to fill in the details, even if there is some as-yet-undiscovered evolutionary mechanism, evolution simply must have this great creative power.

Paleontologist Stephen Jay Gould famously used this tactic, arguing that even if we don’t understand exactly how evolution works, we must still regard evolution as a fact, because, well, things have evolved. Phillip Johnson rightly called out Gould for this self-serving circular attempt to prop up evolution, with Johnson’s careful analysis revealing that Gould’s “fact” of evolution turned out to mean nothing more than the theory.

Unsatisfied with circular evolutionary arguments and lazy reasoning, Behe decided to pose his question to the real-world data. What does the actual evidence show about what evolution can do? Behe approached the problem from a number of angles, the most well-known being his analysis of the appearance of chloroquine resistance in the unicellular malaria parasite Plasmodium falciparum.

Lots and Lots of Cells

In brief, Behe noted that the anti-malarial drug chloroquine had been far more successful against the parasite than many other drugs, with resistance to chloroquine arising only in one out of approximately 10^20 parasite cells, as estimated by immunologist Nicholas White, a well-known expert in malaria research. It’s hard for us to grasp such a number, but for comparison’s sake, astronomers estimate there are only between 10^11 and 10^12 stars in our Milky Way galaxy.

Although the molecular details of chloroquine resistance remained fuzzy at the time of Behe’s 2007 book, The Edge of Evolution, based on the malaria data then available Behe suggested that chloroquine resistance might well require two coordinated mutations. A single point mutation (as had been seen with some other drugs) or a series of individually beneficial mutations should have arisen much more frequently than White’s 10^20 estimate. The data, Behe noted, simply did not fit with such approaches, so a more parsimonious explanation was that two coordinated mutations were required.

Evolutionists, predictably, were upset. Jerry Coyne and Sean Carroll asserted that Behe had to be wrong, just on the principle of the thing. In essence, they argued that oh, yes, chloroquine resistance can too come about by a series of single beneficial step-by-step point mutations. That such a claim flatly contradicted the data was beside the point.

Not lost on careful observers was the irony that Behe had proposed that Plasmodium could in fact acquire two coordinated mutations via evolutionary means. Yet intent on maintaining the lore of “one small step at a time for evolution,” Coyne and Carroll eschewed Behe’s offer of two coordinated mutations. In a creative albeit bizarre kind of reverse-gamble, they wagered, “We’ll see your two mutations and raise it to one!”

Over the next several years, arguments went back and forth, and more ink was spilled by the debaters than by a clumsy apprentice at the print shop. Yet despite the nitpicking of definitions, the fights over math, and the repeated accusations that Behe must not understand how evolution really works, those of us who watched the battle of wits from the sidelines noticed that Behe’s basic question remained awkwardly unanswered by his critics: How much can evolution really accomplish?

Moran and the Luck of the Draw

One of the more engaged critics of Behe’s argument was Dr. Larry Moran, professor of biochemistry at the University of Toronto. Moran seems to be on board with the broader evolutionary narrative, but does not consider himself to be a Darwinist. Not long before Behe published The Edge of Evolution, Moran posted a detailed description of his views on his Sandwalk blog titled “Evolution by Accident.” Moran laid out the case for a non-Darwinian view of evolution, building on Jacques Monod’s argument that “pure chance…is at the very root of the stupendous edifice of evolution,” as well as Gould’s famous replay-the-tape-of-life analogy.

For the most part, I agree with Moran’s assessment of the randomness of evolution, my primary quibble being that Moran doesn’t go far enough in recognizing the role of chance in the evolutionary narrative, specifically in the case of so-called selective events. Upon careful analysis, Darwin’s selection mechanism also collapses to a largely chance-based affair, and so the effort to distance oneself from the shadow of Darwin by embracing random evolution is, to a large extent, a distinction without a difference. Yet that is a nuance and a discussion for another time, should I ever have the honor of the proverbial drink at the pub with Moran.

The key point for readers here is that armed with his chance-centered view of evolution, Moran dove into the debate with Behe over chloroquine resistance. The backs and forths between Moran and Behe (and by their supporters and detractors) throughout the summer of 2014 were too numerous to detail here. Then, following several years of relative peace (at least on this particular front), the battle began anew.

In part to silence the spurious accusation that he doesn’t respond to his critics, in November 2020 Behe published A Mousetrap for Darwin, a collection of his numerous rebuttals to critiques of his three prior books. Included in Mousetrap are several responses to Moran. Moran quickly penned a hurried response on his Sandwalk blog arguing, in essence, that Behe was both wrong about how chloroquine resistance came about and had misinterpreted the mechanisms of evolution.

Behe’s Misunderstanding or Misunderstanding Behe?

Significantly, Moran acknowledges the main thrust of Behe’s argument, noting that:

Behe has correctly indentified [sic] an extremely improbably evolution event; namely, the development of chloroquine resistance in the malaria parasite. This is an event that is close to the edge of evolution, meaning that more complex events of this type are beyond the edge of evolution and cannot occur naturally. [Emphasis added.]

This is a very important acknowledgement, and a reader of The Edge of Evolution might well say to Moran, “Welcome aboard!”

Instead, Moran’s main disagreement (coaxed along at various times by P. Z. Myers, Kenneth Miller, and company) seems to be that Behe has misunderstood how malaria resistance came about. Moran acknowledges that “none of us have a serious problem with this guesstimate [1 in 10^20 malaria-cell replications], but several of us have objected to the way Behe interprets it.”

Flashing back to 2007, we remember Behe had suggested that the simplest explanation for the extreme rarity of resistance to chloroquine was that at least two coordinated mutations were required. This was in stark contrast to the drug atovaquone, for example, which required but a single point mutation, and against which resistance arose faster than the average person could learn to pronounce “Plasmodium falciparum.”

Casey Luskin observed that much indignation was brought to bear by some of Behe’s critics for Behe’s use of the word “simultaneous,” but it was clear to any thoughtful reader of The Edge of Evolution that Behe had never claimed that the two mutations had to arise at the same moment in one fell swoop, such as in the exact same reproduction cycle. His point was simply that the two mutations needed to eventually be together at a particular point in time in a particular cell to confer the needed benefit, regardless of precisely when the mutations arose or which mutation came first. Unlike some of Behe’s critics, Moran, to his credit, granted Behe’s point about the mutations having to be together simultaneously to provide the needed benefit. Moran’s concern was more about the possible routes to chloroquine resistance.

What Guesses Were Reasonable?

It was not at all clear in 2007 — my understanding is that it is still not completely clear — exactly which mutational routes are available to Plasmodium in humans in the wild, nor all the other factors or nuances that might bear on the problem. Moran himself notes that “there are lots of complications and many unknown variables” and that we can “provide estimates” but “can’t give precise calculations.”

The best anyone could do while waiting for more definitive research in 2007 was to make an educated guess as to the exact pathway(s) to resistance. The question is, what guesses were reasonable in light of the malaria data?

Then in 2014, an important paper by Summers et al. shed additional light on the development of chloroquine resistance. Although limited to experiments involving frog oocytes in the lab, this research provided solid experimental evidence detailing the specific mutations involved. The researchers identified two initial routes to chloroquine resistance, with additional mutations leading to “the attainment of full transport activity.” Behe’s critics pounced on this as a possible chink in Behe’s argument, grasping onto the possibility that there might be various ways to achieve chloroquine resistance, including from combinations of more than two mutations.

Behe for his part correctly noted that, if anything, the new research supported his primary argument. Indeed, one of the key takeaways of Summers et al. is that chloroquine resistance is a multi-mutational event, with both of the identified routes to resistance requiring “a minimum of two mutations” to get started. Behe’s 2007 prediction that chloroquine resistance did not result from a series of individually beneficial mutations, but required a multi-mutational event, turned out to be correct. Yet critics still asserted that the key take-home lesson was elsewhere to be found.

In the second part of this response, we’ll examine the data and the implications of chloroquine resistance for the broader evolutionary story.

 

File under "well said" LXXIX

Matthew 19:24KJV"And again I say unto you, It is easier for a camel to go through the eye of a needle, than for a rich man to enter into the kingdom of God." 

     Jesus of Nazareth.

Saving Darwin?

Will Earth BioGenome Project Vindicate Darwin?

Evolution News @DiscoveryCSC

 

Some scientists have a new pet project: sequence everything! They’ve given this idea a name: the Earth BioGenome Project (EGP). Specifically, the goal is to sequence every eukaryotic species that has been taxonomically designated. Mark Blaxter et al. explain in their perspective article in PNAS, “Why sequence all eukaryotes?” that a primary goal of the proposal is to understand evolution.

Life on Earth has evolved from initial simplicity to the astounding complexity we experience today. Bacteria and archaea have largely excelled in metabolic diversification, but eukaryotes additionally display abundant morphological innovation. How have these innovations come about and what constraints are there on the origins of novelty and the continuing maintenance of biodiversity on Earth? The history of life and the code for the working parts of cells and systems are written in the genome. The Earth BioGenome Project has proposed that the genomes of all extant, named eukaryotes — about 2 million species — should be sequenced to high quality to produce a digital library of life on Earth, beginning with strategic phylogenetic, ecological, and high-impact priorities.

The EBG would certainly provide job security for numerous lab workers, but will it really provide the wisdom needed to understand life and evolution? Blaxter and his 25 co-authors think it will. Coming from a Who’s Who of major scientific institutions and government labs from Sweden to China to America, they also claim it will have numerous other practical benefits. Advocates of a proposal like to toss in suggestions that their work might help cure cancer, aid farmers, or mitigate climate change, but clearly the priorities are to solve evolutionary questions. This is evident from the sixty mentions of the word evolution in the essay.

We suggest that many questions of evolutionary and ecological significance will only be addressable when whole-genome data representing divergences at all of the branchings in the tree of life or all species in natural ecosystems are available. We envisage that a genomic tree of life will foster understanding of the ongoing processes of speciation, adaptation, and organismal dependencies within entire ecosystems. These explorations will resolve long-standing problems in phylogenetics, evolution, ecology, conservation, agriculture, bioindustry, and medicine.

Is That Necessarily So? 

Consider a hypothetical proposal to find every fossil on earth. Would it solve evolutionary questions? In Darwin’s Dilemma, Paul Chien argued that enough fossils have been discovered to see the global patterns. One more scallop on the beach is not likely to change the picture, let alone millions of them. Some big data projects, however, can be very instructive, such as the ENCODE project and its spin-offs that found more function in noncoding DNA than expected.

Money for such massive projects can be an issue; remember the Superconducting Supercollider? The paper mentions private funding: “This research was funded in whole, or in part, by Wellcome Trust Grants 206194 and 218328.” The Wellcome Trust is a charitable foundation in the UK with a mission “to fund research to improve human and animal health.” Whether governments will toss in some dollars is not stated, but certainly private foundations can spend their money as they choose. No problem there. The work is certainly conceivable, and with big data projects, storage of the information is not a problem. The question is whether this is the highest and best use of time and equipment by biologists and geneticists. Let the proponents make their case. Their justifications can be summarized:

1. Discovering the Trees of Life
2. Defining the Origin of Eukaryotic Cells
3. Tracking Genomic Changes in Symbiosis
4. Decrypting Chromosome Evolution
5. Revealing the Deep Logic of Eukaryotic Gene Regulation
6. Probing the Diversity of Sexual Systems
7. Exploring Diversity in the Genomics of Speciation
8. Decoding the Genomics of Complex Traits
9. Understanding Ecosystem Function, Stasis, and Change
10. Building Genomics-Informed Conservation
11. Inventing New Tools and Resources
12. Preserve for Posterity the Diversity and History of the Planet’s Biology

Four of these (1, 2, 4, 7) are primarily evolutionary questions; several others (3, 6, 8, 9) overlap with evolution. Evolutionary questions are not necessarily useless pursuits; they might have design implications if the results do not support neo-Darwinism. 

Hidden Assumptions in the Proposal

There are some hidden assumptions in the proposal. One is that all genomes of a particular species are alike. That cannot be true because numerous subspecies inhabit differing environments. Will this require multiple samples from some species? Talk of “The Human Genome” glosses over the diversity of humans, requiring further investigation of haplotypes. Will that be an issue for Canis familiaris, the domestic dog that varies from mastiff to chihuahua? Additionally, will a genome from a male and a female be required to cover the sex chromosomes of each species? Another dubious assumption is that scientists know what a species is. This touches on a vexed philosophical question in taxonomy: whether the current taxonomical system carves nature at its joints. 

Another issue to ponder is whether a massive sequencing project at this scale is the only way to find out the answers to all 12 of the questions. If it is not, the EBG could be a huge boondoggle, a waste of time and money that could be better spent elsewhere. Could a well-chosen selection of genomes serve the purpose just as well? 

More than Big Data Is Needed

The authors welcome opinions about the project:

The big questions we have posed derive from our collective discussions, but we are aware — and indeed hope — that there will be additional major questions that others believe can be answered by sequencing and functionally annotating all eukaryotic genomes. We invite you to add questions to the roster, to widen the debate, and to, ultimately, fully realize the promise of biological understanding based on the complete genome sequence of all of Earth’s remarkable species.

Understanding requires more than big data. If the EBG project takes root, research teams will find themselves neck-deep in arbitrary decisions requiring wisdom to get meaningful results. In their concluding sales pitch, the others make it sound like evolutionary understanding will simply leap out of the data. That rarely happens. Data need interpretation by human beings exercising wisdom and discernment.

Notice the volume of verbiage about evolution, with a few crumbs of societal benefit added to the end like rosy frosting on the Darwin cake:

The genomes will be the core data from which the phylogeny of all life is inferred, including the complex reticulations that endosymbiosis, horizontal transfer, hybridization, and introgression have created. Complete genome assemblies enable a broader and more complete understanding of a species’ biology, contributing to a lessened risk of extinction. Within the unifying model of this phylogenetic network, the genomes and the genes they possess will enable understanding of regulatory networks and trait evolution, the dynamics of coevolutionbetween genes and between species, the impact of changing environments on species and populations, the mechanistic link between genotypes and phenotypes, and the drivers of genome–environment interactions. These analyses, in turn, will enable biologists to better characterize fundamental evolutionary processes, from the nucleotide to the genome level, identifying processes active under different chromosomal architectures and gene interaction networks. These dramatic advances in understanding of both the wide sweep and the local details of genomic and organismal evolution will enable the inference of ancestral genomes and their traits, which will be transformative for understanding how life evolved on Earth, predicting future evolution, and inspiring bioengineering of organisms with beneficial traits using technologies such as CRISPR and whole-genome synthesis. This foundational library of information will change the economic and social growth of the future, fostering sustainable agriculture and new bioeconomies, accessing an expanded medical pharmacopoeia, and promoting societal equity and diversity through the lens of a deeply valued biodiversity.

Let’s leave the value of this proposal as an open question for design advocates, who will likely have differing opinions about it. Would that some of the enthusiasm for such a massive undertaking, though, would be reserved for exploring the biological engineering so evident in life.

on liberty and the middle class.

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The American Communist party: a brief history.

 Communist Party of the United States of America (CPUSA), also called Communist Party USA, left-wing political party in the United States that was, from its founding in 1919 until the latter part of the 1950s, one of the country’s most important leftist organizations. Its membership reached its peak of 85,000 in 1942, just as America entered World War II; the CPUSA had rallied enthusiastically in favour of a Soviet-American war effort against Nazi Germany.

In 1919, inspired by Russia’s October Revolution (1917), two U.S. communist parties emerged from the left wing of the Socialist Party of America (SPA): the Communist Party of America (CPA), composed of the SPA’s foreign-language federations and led by the sizeable and influential Russian Federation, and the Communist Labor Party of America (CLP), the predominantly English-language group. They were established legally but were soon forced underground. Although the two parties feuded and various factions broke away to establish competing communist groups, the Communist International encouraged the unification of those organizations. In 1922 the CPA merged with the United Communist Party (which had been established when the CLP joined a breakaway faction of the CPA) to create the legal and aboveground Workers Party of America (WPA). When the United Toilers of America, a group that adopted the same tactics as the WPA, combined with the latter organization, the party renamed itself the Workers (Communist) Party, finally settling on the name Communist Party of the United States of America in 1929.During the 1920s the CPUSA’s trade-union arm, the Trade Union Educational League, promoted industrial unionism vis-à-vis the craft union-oriented American Federation of Labor (AFL). When that strategy proved unsuccessful, the CPUSA upon orders from Moscow transformed the Trade Union Educational League into the Trade Union Unity League in 1929, which was dedicated to organizing largely unskilled immigrant, African American, and female workers into industrial unions. Although the Trade Union Unity League was not nearly as successful as the AFL, it did provide a training ground for CPUSA organizers when they became active in the Congress of Industrial Organizations (CIO) unions.

During the early years of the Great Depression, the CPUSA emerged as committed militants within the unemployed movement. Later in the 1930s, with approximately 65,000 members and New Deal liberalism sweeping the country, the CPUSA became influential in many aspects of life in the United States. There were also untold numbers of “fellow travelers” who sympathized with the aims of the party though they never became members of it. At that time CPUSA members became national, regional, and community leaders in liberal, cultural, and student organizations. In addition, because of their roles as industrial union organizers during the mid-to-late 1930s, they became a major force in several important CIO unions by the early 1940s. In New York City, a stronghold of party support where communists actively engaged in housing struggles, CPUSA candidates were elected to the city council during its zenith.

After World War II, with the onset of the Cold War and the rise of anti-Soviet sentiment, the CPUSA increasingly came under attack. Deprived of significant influence in the labour movement when the CIO expelled 11 CPUSA-led unions in 1949 and 1950, the CPUSA suffered additional losses of power in many left-liberal organizations when it was subjected to McCarthyism in the early 1950s. In 1956 support for the Soviet invasion of Hungary and the revelation of Joseph Stalin’s crimes in Nikita Khrushchev’s “secret speech” at the 20th Soviet Party Congress led to mass defections from the CPUSA. Although communists held leadership positions in several anti-Vietnam War organizations during the 1960s and ’70s, they exerted little sway in the U.S. labour movement. While the party made many significant contributions to the radical movement, especially during the 1930s and ’40s, the CPUSA’s unswerving support for Stalin and the Soviet Union harmed the party not only in the eyes of broad segments of the population but among other liberal and left-wing activists as well.

Science's place in modern society:idol or instrument?

The Human Cost of Coercive Science

John G. West

 

Did lockdowns during the COVID-19 pandemic actually work? That’s the question a study recently released by a research center at Johns Hopkins University attempted to answer. 

Authored by three economists, the “meta-analysis” sought to evaluate the effectiveness of lockdowns to reduce deaths from COVID-19 deaths. The study defined a lockdown as any “compulsory, non-pharmaceutical intervention,” and it synthesized and analyzed results from two dozen other studies. The economists reached a startling conclusion: “lockdowns have had little to no effect on COVID-19 mortality.” To be more specific, “lockdowns in Europe and the United States only reduced COVID-19 mortality by 0.2% on average” and shelter-in-place orders in particular “were also ineffective, only reducing COVID-19 mortality by 2.9% on average.” 

Following “The Science”

This new study is far from the the final word on the effectiveness of lockdowns. Perhaps these economists are wrong. But at least they are beginning to ask the right questions. If we are serious about following “the science,” it makes sense to ask what the evidence actually shows about what works and what doesn’t.

But there is another question that needs to be asked as well: Even if lockdown policies were shown to have significantly reduced mortality, did their benefits outweigh their costs? 

To answer that question, we need to know not only the impact lockdowns had on COVID-19 mortality, but also their impact on crime rates, unemployment, education, child development, suicides, mental health, and deaths from other causes. We also need to consider the impact on intangible goods such as free speech and religious liberty. This is a point I tried to make in a talk I originally gave in May 2020, later posted on YouTube. It was also a central point of the 2020 book The Price of Panic by Discovery Senior Fellows Douglas Axe and Jay Richards along with William Briggs, one of the first major books to address COVID-19 public policies. 

Calculating the Costs

Unfortunately, we have just begun to scratch the surface of calculating the real costs of lockdowns and related measures. Which brings to me to the nightmare still being experienced by Melissa Henderson in Blairsville, Georgia.

Melissa is a single mom with five kids. To support her family, she needs to work. But when the lockdowns came in 2020, her daycare provider shut down. So she had to find another solution, and she asked her 14-year-old daughter Linley to babysit. One day Melissa’s four-year-old son went out to play with his neighbor friend. It took a few minutes for Linley to notice, because she was doing online schooling. By that time, the neighbor had called 911. 

To be clear, it is legal for youth as young as 13 to babysit in Georgia. That didn’t stop the police from arresting Melissa (handcuffs and all) and putting her in jail. Fortunately, her ex-husband bailed her out. Melissa was eventually charged with a crime that could send her to prison for a year. Her case has been dragging on now for nearly two years. The police and prosecutors seem like characters right out of Les Misérables. 

How Many Melissas?

Of course, the officials who imposed Georgia’s lockdown did not intend to deprive Melissa of her ability to support her family. Nor did they intend for her to be abusively prosecuted. But it happened nonetheless. 

How many other Melissas are there, people hurt in serious ways by the lockdown policies? I don’t know. What I do know is this: Until we have a full accounting of all the Melissas there are, we won’t really know how effective — or costly — the lockdowns were.

Lockdowns were imposed on society in the name of science, although the actual scientific basis of many of the measures employed was unclear at best. But there is nothing scientific in avoiding an honest discussion of their actual results.

American socialism: A case study.

On spaceship earth's forcefield.

 

Solar Activity Reveals a Different Kind of “Privilege”

Daniel Reeves

Did you experience anything unusual a couple of Wednesdays back? Perhaps a feeling of impending doom, or even just a slight change in mood? 

No? Well, then perhaps you are more privileged than you think. 

On Saturday, January 29, the sun — you know, that yellow dwarf star around which we orbit at over 100,000 kilometers per hour — decided to throw a violent tantrum resulting in an eruption of high energy particles and magnetism. The outburst reached earth’s atmosphere on Wednesday, February 2. This coronal mass ejection, and the resulting geomagnetic storm in our atmosphere, likely had indiscernible — if any — impact on your less-than-momentous hump day. Unless I missed something, it didn’t even merit a mention in the weather forecast. 

A “Milquetoast Outburst”

According to Hugh Lewis, a space debris expert at the University of Southampton cited in a New York Times article, this solar incident was actually mild compared to what we can expect approaching the year 2025. “As the sun gets more active, it releases an increasing amount of extreme ultraviolet, which gets absorbed into our atmosphere,” Lewis explains. “The expectation is that the atmospheric density is going to increase by one or two orders of magnitude. That’s a way bigger change compared to what we’ve just seen with this particular event.” Or, as Robin George Andrews writes for the Times, this was a “milquetoast outburst” compared to “a more potent solar scream [that] has the potential to inflict greater harm.” 

So…does this mean that the world is coming to an end? Should you drop out of school or quit your job, and enjoy your last few toasty years on this doomed planet?

Not so fast. As Andrews points out, we are simply ramping up to the peak of an 11-year-long cycle in which the sun undulates between hyperactive and quiescent states. This solar cycle, coinciding with the reversal of the sun’s magnetic field, has already reached a violent peak one or more times in your lifetime and, just like Wednesday’s incident, that has had negligible — if any — impact on your daily life.

Perhaps, like me, you’ve taken this fact for granted — that a fierce coronal mass ejection from the sun has little effect on life at the surface of the planet. In fact, it is one of many privileges that humanity accepts as a given, regardless of our ethnicity, gender, or socioeconomic standing: the privilege of living on a planet that is astonishingly protected in the midst of an otherwise inhospitable cosmos.

Blissfully Unaware of Bombardment

Like you, I was blissfully unaware that our atmosphere was being bombarded, and only stumbled upon the fact a few days ago in the Times. The article, “Solar Storm Destroys 40 New SpaceX Satellites in Orbit,” focuses on the impact of the solar ejection on the latest satellites launched into space as part of Elon Musk’s high speed Internet project. The reporter concludes that “the incident highlights the hazards faced by numerous companies planning to put tens of thousands of small satellites in orbit to provide Internet service from space.” 

True, the fact that 40 of the 49 new satellites launched into the lower atmosphere on February 3 could be knocked out by a routine solar outburst is a reminder of the incredible challenges facing aerospace technology. That’s a $100 million loss in hardware and launch costs incurred by SpaceX, as estimated by Dr. Lewis in the article. 

But there’s far more at stake. Without the combined protective effect of our unique atmosphere and geomagnetic field — a relatively rare phenomenon in the observable universe — even a “milquetoast outburst” from the sun would be sufficient to destroy all life on earth.

Yet this brief article was the only mention of the occurrence that I could find either in the New York Times or a handful of other major news sites. It goes to show how most of us take our privileged planet for granted. Perhaps an occasional demonstration of our cosmic entitlements could also remind us of the privileges that we all share as a human species — privileges that are considerably greater than those that threaten to divide us.

And still yet even more on the patron saint of the master race.

 

Racism Serves Darwinism, Darwinism Serves Racism

Richard Weikart

 

Editor’s note: The following is excerpted from Chapter 1 of Richard Weikart’s new book, How Darwinism Influenced Hitler, Nazism, and White Nationalism.

When Darwin began compiling evidence for biological evolution in his notebooks in the late 1830s, he included human evolution in his ruminations. He indicated that when human races confront each other, they fight and struggle with each other for supremacy. He wrote that differences in intelligence usually settle this conflict, though in the case of black Africans, their “organization” (presumably meaning their immunity to diseases that ravaged Europeans who moved to Africa) gave them an advantage in their homelands. His comments here imply that he thought not only that some races are more intelligent than others, but also that blacks were inferior in their mental abilities.¹

Scientific Justification for Racism

Darwin’s racist and imperialist attitudes were conventional for his time, but his use of racism to defend his theory of human evolution buttressed those attitudes in the decades to follow by providing scientific justification for racism among many of Darwin’s followers. Racism was not just an incidental part of Darwin’s evolutionary theory. Rather Darwin considered racial inequality crucial evidence for his theory. In order to convince his contemporaries of his theory of evolution, he knew he needed to demonstrate the great variety within any given species, while minimizing the gap between different species. When applied to human evolution, this meant that Darwin had to stress human inequality on the one hand, and human proximity to apes on the other. Racism provided fodder for this argument, because Darwin placed the black Africans and Australian aborigines close to the apes in his racial hierarchy, while deeming the white Europeans far superior.

To be sure, when Darwin first published On the Origin of Species (1859), he mostly avoided the topic of human evolution. He understood that this was the most controversial part of his theory and that it would likely provoke resistance (as it did). As he explained 12 years later in the introduction to The Descent of Man, he had steered around the issue of human evolution “as I thought that I should thus only add to the prejudices against my views.”² Only in the closing paragraphs of Origin had he briefly mentioned that his theory would likely have ramifications for human origins. Thus, when Darwin mentioned “races” in the full title of his 1859 book, On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, he likely meant primarily varieties or sub-species of animals and plants, rather than human races. However, Darwin later clarified in The Descent of Man that he viewed human races as varieties or sub-species,³ so everything he wrote in Origin did indeed apply to humanity. Darwin confirmed this in The Descent of Man, for one of its stated goals was to show that the evolutionary processes that Darwin had explained in Origin had brought about the origins of humans, too. The Descent of Man, in other words, argues quite explicitly for “the preservation of favoured” human “races in the struggle for life.”

Highly Problematic Features

Darwin’s conception of the struggle for life, or, as he more often called it, the struggle for existence, had highly problematic features when applied to humans. Darwin’s signature theory of natural selection through the struggle for existence was based on Thomas Robert Malthus’s population principle, which stated that humans (and other organisms) tend to reproduce faster than their food supply can increase. This implies that humans (and other species) are destined for mass death, since the food supply can never keep up with the ever-growing population. Darwin argued that because most organisms perish in their quest for limited resources, they are locked in an inescapable competition for those resources. This competition is most intense among members of the same species because they are competing for the same niche.

Despite the huge death toll resulting from the struggle for existence, Darwin considered it a positive force nonetheless, because it produced evolutionary progress. It weeded out the weak, sickly, and less capable — the “unfit” — while the “fit” survived and reproduced. In the last sentence of his chapter on “Struggle for Existence” in The Origin of Species, Darwin stated, “When we reflect on this struggle, we may console ourselves with the full belief, that the war of nature is not incessant, that no fear is felt, that death is generally prompt, and that the vigorous, the healthy, and the happy survive and multiply.” Then, in the next-to-the-last sentence of the book, he stated, “Thus, from the war of nature, from famine and death, the most exalted object which we are capable of conceiving, namely, the production of the higher animals, directly follows.”⁴ When applied to humans, this would mean that humans are contending with their fellow humans for scarce resources in a competition-to-the-death. The fittest humans will survive and reproduce, while the less fit will die.

Three Main Objectives of the Work

In The Descent of Man Darwin confirmed that he thought race played a central role in this struggle, so racism is not an incidental element of the book. Darwin explained from the outset the three main objectives of the work: 1) investigate whether humans are descended from some other animals; 2) explain the process of human evolution; and 3) describe “the value of the differences between the so-called races of man.”⁵ Of the seven chapters covering human evolution, one is entitled, “On the Races of Man,” and racial themes also emerge in many of the other chapters. 

Toward the beginning of the book’s second chapter, “Comparison of the Mental Powers of Man and the Lower Animals,” Darwin insisted that certain races were mentally inferior to others:

Nor is the difference slight in moral disposition between a barbarian, such as the man described by the old navigator Byron, who dashed his child on the rocks for dropping a basket of sea-urchins, and a Howard or Clarkson; and in intellect, between a savage who does not use any abstract terms, and a Newton or Shakspeare [sic]. Differences of this kind between the highest men of the highest races and the lowest savages, are connected by the finest gradations. Therefore it is possible that they might pass and be developed into each other.⁶

Howard and Clarkson, incidentally, were leaders in the British abolitionist movement, and Darwin considered them the epitome of moral goodness. They were, of course, Europeans, as were Newton and Shakespeare, and clearly Darwin was identifying them as “the highest men of the highest races,” in contrast to the “lowest savages.” Thus, Darwin buttressed his theory of human evolution by asserting that Europeans were not only intellectually superior, but also higher on the scale of morality. This is highly ironic, of course, because these allegedly morally superior Europeans were at the time exterminating the supposedly morally inferior natives of the Americas, Australia, and elsewhere. Darwin apparently had no conscience about genocide, since he saw nothing amiss about allegedly morally superior people killing off those they deem inferior.

He considered the intellectual superiority of Europeans so self-evident that he wrote in a later chapter, “The variability or diversity of the mental faculties in men of the same race, not to mention the greater differences between the men of distinct races, is so notorious that not a word need here be said.”⁷ Despite its apparent obviousness (to him), however, later in the same chapter he did write more about it. He trotted out scientific evidence for intellectual disparities among races that he (and many other European scientists) considered compelling: the difference in their cranial capacities. 

According to the data cited by Darwin, the Europeans have the largest cranial capacities at 92.3 cubic inches, while Asians have 87.1 cubic inches, and Australians have only 81.9 cubic inches.⁸ The lesson appeared unarguable: Europeans have greater intellectual abilities than do other races. Darwin used this same line of evidence to argue that women are intellectually inferior to men. (It should be noted that cranial capacity measurements cited above turned out to be inaccurate and misleading, and the relationship between cranial capacity and intelligence has been found to be neither straightforward nor well correlated.⁹) Later, when discussing the gap between present-day humans and simians, Darwin mentioned that the gap would only increase as the “savage races” were exterminated, because the black Africans or Australian aborigines were currently the closest races to the gorilla, which he considered the highest of the ape species.¹⁰

A Racial Struggle for Existence

In a four-page section “On the Extinction of the Races of Man,” Darwin explained that the primary cause of the extinction was a racial struggle for existence, which results in the decimation of weaker tribes and races. He claimed that the disappearance of ancient races was not the result of environmental factors or adverse circumstances. Rather, he averred, “Extinction follows chiefly from the competition of tribe with tribe, and race with race.” Though disease may aid some people in these racial competitions, direct killing is also involved, because “when one of two adjoining tribes becomes more numerous and powerful than the other, the contest is soon settled by war, slaughter, cannibalism, slavery, and absorption.” Darwin thought that in most cases the so-called civilized peoples were winning this bloody contest: “When civilised nations come into contact with barbarians the struggle is short, except where a deadly climate gives its aid to the native race.”¹¹

What shouldn’t be overlooked here is that from Darwin’s perspective, this pattern of natural selection by racial extermination was the path to human progress.

Notes

1. Darwin, Charles Darwin’s Notebooks, 537.
2. Darwin, Descent, 1:1.
3. In The Descent of Man chapter “On the Races of Man,” Darwin confirmed his belief that human races differ considerably, not only physically, but also in their mental capacities. For this reason, he considered races to be distinct sub-species. Darwin, Descent, 1:216, 227.
4. Charles Darwin, The Origin of Species [1859] (London: Penguin, 1968), quotes at 129, 459.
5. Darwin, Descent, 1:3.
6. Darwin, Descent, 1:35.
7. Darwin, Descent, 1:109–110
8. Darwin, Descent, 145–146.
9. Daniel Graham, “A Bigger Brain Is Not Better,” Psychology Today, March 9, 2021, https://www.psychologytoday.com/us/blog/your-internet-brain/202103/bigger-brain-is-not-necessarily-better.
10. Darwin, Descent, 1:201.
11. Darwin, Descent, 1:238.

Designed evolution continues its ascent over evolved "design"?

 

New Study in Nature Showing “Non-Random” Mutation Spells Trouble for Neo-Darwinism

Casey Luskin

 

A correspondent asked me about a recent paper in the journal Nature, “Mutation bias reflects natural selection in Arabidopsis thaliana,” aka the commonly studied flowerweed, thale cress. The abstract states, “Since the first half of the twentieth century, evolutionary theory has been dominated by the idea that mutations occur randomly with respect to their consequences. Here we test this assumption with large surveys of de novo mutations in the plant Arabidopsis thaliana.” They show that “epigenome-associated mutation bias reduces the occurrence of deleterious mutations in Arabidopsis, challenging the prevailing paradigm that mutation is a directionless force in evolution.”

That mutation is “directionless” or “random” is a traditional axiom of evolutionary biology. My correspondent wanted to know what it means to consider that some mutations may be “non-random” after all. She supposed that she was asking a “dumb question.”

Exactly the Question to Ask

Actually, it’s not in the least a dumb question — it’s exactly the right question to ask! In the context of this paper, what “non-random” means is that mutations are less likely to occur in gene-coding DNA — especially in what they call “essential genes.” This overturns two standard assumptions of the modern theory of evolution.

In evolutionary biology, it’s generally thought that mutations are “random” in two respects:

1. Mutations occur with equal likelihood across the entire genome. So there’s no part of the genome that is MORE or LESS likely to experience mutations than any other part of the genome. This is supposed to mean mutations are not directed or concentrated, but in a sense are randomly distributed across the genome. 
2. Mutations occur without regard to the needs of the organisms, meaning they are random and not directed for or against what the organisms needs to survive. 

The Nature study found evidence against both (1) and (2). In Arabidopsis, some parts of the genome are LESS likely to experience mutations, and those parts of the genome that experience fewer mutations tend to be the REALLY important parts of the genome that you wouldn’t want to be mutated because in those sections, mutations would most likely break genes that are very important to the organism.

A Look at the Specifics

Now let’s get into more specifics. In the genomes of most higher organisms, only a small percentage of the DNA represents genes that encode proteins. The Nature study found that sections of the Arabidopsis genome that encode genes are LESS likely to experience mutations than the “intergenic” regions — the sections of the genome between genes that don’t encode proteins. They found that “the frequency of mutation was 58% lower in gene bodies than in nearby intergenic space.”

They further found that “essential genes,” such as those basic genes responsible for translation (e.g., converting the information in DNA into proteins), had even LOWER mutation rates compared to other genes that had more specialized functions.

Please also note this important point: The study was able to directly measure mutations after they occurred in the plant but before mutations could have been affected by natural selection, which might “weed out” certain mutations that have deleterious effects. So the authors think they have provided a true and accurate measure of mutations as they occur in the DNA.

Or to put it another way, mutations don’t occur randomly in the sense that some parts of the genome are less likely to experience mutations than other parts of the genome. Instead, mutations DO occur with respect to the needs of the organism. That is, in certain respects life seems to be designed to minimize mutations in the places where they would do the most damage to the organism’s basic functions.

Implications for Evolutionary Biology 

The implications for evolutionary biology are profound. If mutations aren’t equally distributed across the genome, and aren’t random with respect to the needs of the organism, then two basic tenets of the standard neo-Darwinian model are false. This also could spell trouble for neo-Darwinism because it suggests that mutation rates are lowest in areas where mutations would presumably be needed to foster evolution — i.e., they are lowest in the genes.

If mutation rates are low in the gene-coding DNA, then it will take even longer for new complex traits to arise by mutating functional genes. This exacerbates what Darwin-skeptics call the “waiting time” problem, where it takes too long for necessary mutations to arise — far longer than the amount of time allowed by the fossil record. 

Return of the Waiting-Time Problem

Intelligent design proponents have already identified the waiting time problem as a fundamental mathematical obstacle to neo-Darwinian evolution. Our colleagues published a paper in the Journal of Theoretical Biology last year, “On the waiting time until coordinated mutations get fixed in regulatory sequences,” which did mathematical modelling of the waiting time to generate traits requiring N mutations to provide an advantage. The paper found a serious challenge to neo-Darwinism:

[T]he fossil record is often interpreted as having long periods of stasis, interrupted by more abrupt changes and “explosive” origins. These changes include, for instance, the evolution of life, photo-synthesis, multicellularity and the “Avalon Explosion”, animal body plans and the “Cambrian Explosion”, complex eyes, vertebrate jaws and teeth, terrestrialization (e.g., in vascular plants, arthropods, and tetrapods), insect metamorphosis, animal flight and feathers, reproductive systems, including angiosperm flowers, amniote eggs, and the mammalian placenta, echolocation in whales and bats, and even cognitive skills of modern man. Based on radiometric dating of the available windows of time in the fossil record, these genetic changes are believed to have happened very quickly on a macroevolutionary timescale. In order to evaluate the chances for a neo-Darwinian process to bring about such major phenotypic changes, it is important to give rough but reasonable estimates of the time it would take for a population to evolve so that the required multiple genetic changes occur. [Internal citations omitted.]

Following the standards of the field, the study in Journal of Theoretical Biology adopted standard evolutionary assumptions that mutations are random — i.e., equally likely across the entire genome and occurring without respect to the needs of the organism. But the new study in Nature suggests that both these assumptions are false — and false in a way that probably makes it harder for neo-Darwinism to evolve new traits.

Transposons: ugly ducklings no more?

Cinderella Story? Transposons Gain New Respect

Evolution News @DiscoveryCSC

 

 

They’ve been called selfish. They’ve been labeled as parasites. They’ve been demonized as viral interlopers clogging up our chromosomes with useless copies, taking advantage of our replication mechanisms to perpetuate themselves. These characterizations of retrotransposons, retroviruses, and transposable elements (TEs), also called “jumping genes,” fit the Darwinian picture of entities in it for themselves, getting all they can at the expense of others, in a mindless race for fitness and survival. Recent studies indicate a changing attitude toward one of design. Though it’s too early to tell, TEs may turn out to be a Cinderella story — in line for restoration to the status of essential parts of our genomes, our health, and our lives.

“Myelin Is a Gift from Retroviruses”

Michael Denton has written about the big advantage myelin gives to neurons. “This design allows for what is termed ‘saltatory conduction,” he writes, “where the nerve impulse, instead of travelling sedately and continuously down the axon, jumps from node to node, vastly increasing the speed of transmission.” 

Now John Hewitt writes at Phys.org that “Myelin is a gift from retroviruses.” It’s not the only gift from these “opportunistic” elements that “make up over half our genome” —

Functional retrotransposons have been progressively implicated in all manner of things neurobiological.The maintenance of stem cell identity and mosaicism, incidence of neurological diseases and fusion of cells in the brain by sundry spike proteins are all now understood to be jobs for transposable elements. Writing in the bioRxiv preprint server, researchers have now discovered that vertebrate myelin likely originated when retrovirally derived elements inserted in the genome at key positions to trigger massive expression of their signature protein, Mbp (myelin basic protein). [Emphasis added.]

Hewitt continues to cast these TEs into evolutionary roles, but a design interpretation becomes possible when we compare his story with the fate of the junk DNA story. First there were a few examples found of function in the junk. Those numbers grew, to where now some believe all noncoding DNA is functional. In a previous article at Phys.org, Hewitt had admitted that the ENCODE results startled scientists into reconsidering the role of TEs. That project along with earlier studies showed that TEs were being translated, and appeared to be active in somatic cells, not just in germline cells.

Alongside these prodigious announcements was a parallel observation that much more of the genome is actually transcribed than had formerly been appreciated. Rather than just a few genes being expressed here or there, studies revealed that upwards of 80 percent of our entire genome is likely translated into some kind of RNA. With half a genome’s worth of retroviral additions, many of these transcriptions are undoubtedly retrotransposons one sort or another.

TEs: Enemies, Frenemies, or Friends?

More intimations of a change in attitude about transposons appeared this year. At The Scientist, Christie Wilcox wrote about “Adapting with a little help from jumping genes.” 

TEs, also called transposons or jumping genes, are often cast in a negative evolutionary light. And there is a reason for that: when these sequences insert themselves into new places in the genome, they can mess up genes or alter their expression. They’re sometimes called junk DNA, or worse, genomic parasites, the idea being that they would mutate their host genomes into oblivion if they weren’t almost always silenced by epigenetic modifications such as methylation. But recent research is illuminating the intricacies of TE function and adding texture to this simplistic model.

Wilcox quotes scientists who relate their changes in thinking. The trend these days is to see transposons less as “parasites” and more as “symbionts” that can cause benefit or harm, depending on where they land in the genome. For instance, by regulating genes near to their insertion points, they can “preadapt” an organism to changes in the environment. Here’s an interesting case involving one of evolution’s favorite icons, the peppered moth:

Arguably the most immediate and dramatic impacts TEs have on genomes occur when they insert into active genes. They can jump into coding regions, altering protein sequences, or they can insert into noncoding regions and alter gene splicing or expression. This is what happened in peppered moths, when a 22-kb TE inserted into the cortex gene and led to overproduction of melanin, turning dark the normally lightly bespeckled moths and improving their survival in polluted environments.

Notice the wholesale change in the story. (This is assuming that the dark moths land on blackened tree trunks, which as Jonathan Wells has documented, is factually incorrect; we’re just using Wilcox’s opinion as an indication of a change in attitude.) Instead of positing a random single-nucleotide mutation being selected blindly in the old neo-Darwinian way of thinking, a sequence of coded information is now used in the explanation. A Darwinist would have to argue that code able to help the moth just “happened” to pre-exist and landed in the right spot of a gene to turn it dark. It’s possible to imagine that, but more difficult to support as a blind process. Wilcox shares another case of preadaptation by a transposon:

Unlike point mutations, some TEs come preloaded with genetic motifs that may affect the expression of nearby genes. Certain populations of Drosophila carry the TE insertion FBti0019386, for example, which contains transcription factor binding sites that are activated during a bacterial infection and that increase expression of the immune-related gene Bin1. Flies carrying FBti0019386 are more likely to survive inoculation with a pathogenic strain of Pseudomonas.

One other example is that TEs may become activated by stress. This could indicate that they stand ready to assist the organism in hard times by regulating gene expression.

An Evolving Picture

Like Hewitt, Wilcox fits the new findings into an evolutionary narrative, but that slant may be difficult to maintain at the rate discoveries are coming in. Readers should recall how similar attempts were made to cast junk DNA and vestigial organs in Darwinian terms. In the end, it was function that won out, and design explanations were vindicated. Design theorists may be once again ahead of the curve in explaining these mysterious pieces of mobile code — mysterious, because questions remain that will continue to challenge both approaches:

“You can find transposable elements in virtually all the organisms that have been studied [genetically], from bacteria to eukaryotes,” notes evolutionary biologist Josefa González of the Spanish Research Council (CSIC). But while TEs are nearly universal throughout living organisms, their prevalence varies widely. In some organisms, TEs dominate, accounting for up to 90 percent of the genome, while in others, transposable elements make up only a fraction of the entire genetic code. When abundant, TEs can grow the size of the genome to enormous, unwieldy proportions that continue to baffle scientists.

The picture of TEs is changing from “selfish opportunists” to “occasional partners in regulation.” Basically, TEs are being described as larger versions of random mutations occasionally found to persist by natural selection. But can any Darwinian narrative be sustained, when the point of Darwinism is to imagine adaptation by sheer dumb luck? Why would a stretch of code many kilobases long, existing simply for its own replication, just happen to be useful to another organism? 

“If Something Works”

Recall Paul Nelson’s maxim, “If something works, it’s not happening by accident.” Humans have been reproducing since their appearance on earth. And yet still today, many healthy babies are born, with all their parts in working order, and many of those grow to be strong and athletic adults. If TEs making up half the human genome were so selfish and parasitic, how could that continue for many hundreds or thousands of generations with genomes filled with parasites? 

For over a decade, contributing authors at Evolution News have hinted that endogenous retroviruses and other mobile elements might have functions (McLatchie 2012, Luskin 2015, Hunter 2017, Luskin 2019). Yet questions remain about their quantities, distributions, and effects in organisms. Are the targets where TEs insert themselves random or purposeful? What happens when they cause disease — could those cases be due to broken processes? Why do proportions of TEs vary so widely between organisms? Is there a pattern in the distribution somewhere? The subject of gut biota has undergone a major rethink over the years; now, scientists understand that we have a profoundly necessary and complex relationship with our bacterial partners; sometimes they cause problems, but usually the relationship works. Could there be an analogous relationship with our TEs? 

The easy way out is to call it random. Now that pro-Darwin establishment scientists and reporters are increasingly admitting that TEs are not useless or selfish after all, design theorists can take a strong lead in proposing testable hypotheses that consider foresight and software engineering principles. Code that can jump around is code nonetheless.