Let’s Talk About Sex

I’ve dedicated many blog articles to attempting to make the case that the idea of evolution needs to be updated to include recognition that living things actually systematically design themselves through highly structured mutation.  Despite a lot of fun dancing around the subject the simplest proof of my contention is simply SEX itself.  The PURPOSE of sex is to selectively mutate our genomes.  Let’s start this blog out with one of my favorite questions:  What if everything you think you know is completely wrong?

Here’s a great treatise on the relative advantages and disadvantages of sexual reproduction.


There are several deeply ingrained assumptions about reproduction that I just can’t resist picking at.

  • Asexual reproduction only needs one parent. All the offspring are genetically identical to each other, and their parent. The genes of the original and its copy will be the same, except for rare mutations. They are clones.
  • One way for an asexually reproducing species to get some diversity is through mutations at the DNA level. If there is a mistake in mitosis or the copying of the DNA, then that mistake will be passed down to the offspring, thereby possibly changing its traits.
  • Genetic material is randomly mixed during fertilization.
  • Sexual and asexual reproduction have advantages and disadvantages—which is why some organisms do both!

Okay so asexual reproduction always produces clones except for RARE mutations does it?  Mutation is a “mistake”, genetic material is “randomly” mixed during fertilization and we choose between modes of reproduction because they have different advantages and disadvantages?  There are those human hubris words “mistake” and “random” again that we like to use a lot to cover for ignorance.

Obviously I’m leading a thought process here but let’s step back and take a fresh look at WHY we think living organisms bother to reproduce at all.  Let’s go see what Google says about WHY organisms reproduce shall we?

“Reproduction is important for the survival of all living things. Without a mechanism for reproduction, life would come to an end.”

“Since almost all living things have a finite lifespan, organisms reproduce to maintain the presence of the species.”

Soooo… the purpose of reproduction is to achieve NOT DEATH?  Some rare states of matter WANT to be a species for some reason?  Makes sense…  In my experience inanimate materials tend to behave the way they do with no purpose or intent.  In this sense life must be what is left over when all objects that do not reproduce and adapt to changing environmental conditions are excluded from survival.  Objects that don’t adapt to changing environmental conditions are generally destroyed by them eventually.  Objects that are able to copy themselves and repair themselves are generally more lifelike than objects that don’t have these attributes.  I have previously observed that snowflakes are the most lifelike objects I can think of that we would all agree are not alive.  So life is what is left when all things that don’t replicate and repair themselves have fallen apart for lack of these attributes.

In my previous blog, I observed that life is a byproduct of the quantum properties of water constantly tearing materials apart and putting them back together in random configurations until some of them happen to form machines that self-replicate.  It turns out that there are many different ways to configure matter that produce life, so when water capriciously stumbles across many solutions to the same problem they end up competing with one another for resources.  What resources?  Mainly the energy it takes to resist dissolving.  In the presence of competition for energy the only living systems that survive are the greediest.  Let’s say that life only spontaneously occurred once in Earth’s history and all it did was make exact copies of itself.  It would replicate until it occupied all ecological niches accessible to it and then be forced to compete with itself for survival.  It wouldn’t compete consciously, it would simply have altered its own environmental conditions such that it was forced to replicate at the expense of its clones or die.  Stated that way, what is the opposite of reproduction?  Eating one another for food?

Competitive predation is actually on the same continuum as sex when we think of it as a very efficient means of making a copy of yourself AND making room for that copy at the same time.  Consuming a copy of yourself for parts is more efficient (less energy) than making a new copy entirely from molecular scratch, right?  If the purpose of reproduction is perpetuation of the species… why bother to reproduce when there are too many of the same species?  Perhaps life is just a run-away machine that intrinsically gathers momentum because any life form that doesn’t evolve aggressively gets consumed for parts.  Living organisms are part of the same ecosystem they are forced to adapt to and being successful means that they are constantly altering it.

So life requires self-selective mutation to function at all.  Any life that made perfect copies of itself went extinct from inability to adapt to the environmental changes it imposed on itself.  Competing organisms are engaged in an eternal race to find beneficial mutations faster than their competition or get consumed by the newer better creatures.  Predation+reproduction is the recycling engine of life in a perpetual quest for more efficient self-replicating designs.

So the ACTUAL purpose of reproduction is probably a race to find more efficient means of reproduction.  Organisms that don’t reproduce and innovate aggressively get eaten by their neighbors leaving only those that do.  In a previous blog I described a software program that randomly modifies binary patterns in computer memory and then tries to execute them as code.  Initially most programs produced this way crash and do nothing.  A few do something but eventually get broken in memory by the program that keeps randomizing bits.  Only the random binary pattern that when executed, quickly copies itself before it can be corrupted, has a chance of surviving, but a program that does this is now competing with itself for control of limited computing resources and memory.  If a copy of this self-replicating program gets corrupted by our memory randomizer without breaking it, then there is a tiny chance that this new version of the program is an improvement on itself and goes on to dominate the available computing resources.

In this environment what “intelligent” strategy can a program employ to maximize its chances of producing offspring that have beneficial mutations?  Well, the FASTER it replicates the less corruption risk it experiences between copies and the more similar to a known working solution the mutated program will be.  The slower the replication rate the greater the likelihood that the accumulation of random mutations will be adverse.


“As a consequence of the lack of proofreading activity of RNA virus polymerases, new viral genetic variants are constantly created. RNA viruses readily adapt to changing environmental conditions. Therefore, the high mutation rate of RNA viruses compared with DNA organisms is responsible for their enormous adaptive capacity.”

“Given that most mutations have deleterious fitness effects (), having a too high mutation rate would be prejudicial in the short term simply because (in a first approach) the population equilibrium fitness for a haploid asexual population decreases exponentially with mutation rate ().”

What’s interesting about this paper is that the author doesn’t seem to acknowledge that only HALF the strand involved in RNA replication risks mutation… the parent strand doesn’t change…  If the parent strand in an RNA based organism doesn’t mutate then HALF of all “offspring” are perfect clones of the parent because they ARE the original parent.  RNA based organisms can afford to gamble with their genomes because they always keep a clean backup to reboot from.  

Let’s pretend, for the sake of discussion, that this is an accurate analogy for biological reproduction and evolution.  Water is our memory randomizer and the random configurations of organic molecules that it puts together and pulls apart are our candidates for self-replicating code.  Water doesn’t cease to be a solvent just because a more stable molecule is formed, it just buys the molecule a little more time.  We might agree that slight mutations to a known working pattern are more likely to be successful mutations than large mutations, hence evolution favors faster replication.  Bigger more complex organisms take longer to replicate so evolution must hate them… unless they are somehow better at selecting for beneficial mutations than simple organisms.  Suppose I have a simple organism composed of three important genes which in turn are made of many nucleotides (bits) that evolve to execute in this order.

  1. Consume food
  2. Move away from parent
  3. Replicate self

So this organism, when it pops into existence, possibly eats its parent, then moves away, then makes a copy of itself… which then possibly eats its parent again.  Not your best candidate algorithm for evolutionary success right?  How many random nucleotide mutations would it take for this organism to ever try this sequence of genes?

  1. Replicate self
  2. Move away from parent
  3. Consume food

A little genetic transposon swapping and now we have an organism  that reproduces, gets clear of any near relatives, then feeds, then reproduces again… now we have an organism with a shot at exponential growth rates!  We have the luxury of recognizing that it would take random nucleotide mutations about as close to forever as anything gets to modify this organism to reproduce more efficiently and that none of those random mutations would leverage the abstract insight the organism already contained in it’s genes.  If we only allowed for gene level mutations we would have to wait for one of only 4 possible mutation permutations before we caused a Cambrian explosion!  Now we recognize that a program would have to be bigger and more complex in order to include this new idea of making copies of itself with deliberate gene swapping mutations but the performance gain in enhancing evolutionary speeds is incalculable.  So we have another observation.  Random noise may only be effective for very small simple life forms.  As life forms get bigger they need to copy themselves in genes instead of nucleotides to gain a competitive mutation advantage.  This idea puts sexual reproduction on a smooth continuum of different scales of genetic abstraction and mutation necessary to increasingly faster and more efficient selective evolution.

  1. Random noise –> Simple replicating life (Ribosomes)
  2. Random noise + Simple replicating life –> Life with genes  (Prokaryotes)
  3. Prokaryotes + Predation –> Complex cells composed of primitive cells (Eukaryotes)
  4. Eukaryotes + Sex –> Organisms (Sex was a compromise on eating each other)

This is a gross simplification but think of each of these steps in a higher level fractal granularity of eating stuff more efficiently and replicating with smarter more abstract mutation at each scale.  Each scale not only introduces a new level of mutation but also a more efficient mode of consumption.  Note also that each mode of consumption is itself a form of self-mutation.  The simplest life forms consume energy and randomly available organic molecules.  The invention of genes provides a new more efficient level of evolutionary abstraction.  Instead of eating lots of random nucleotides and spending a ton of energy to construct a gene from scratch I can just eat another organism, tear it apart down to its genes and use those as alternatives to my own.  As I mentioned previously, at this scale “eating” appears to be on the same continuum as reproduction.  Just another way to try some new genetic material that has a proven track record of participating in a working organism.  Why randomly mutate when I can eat genes from another successful organism and try combining those with my own?  Put that way it kind of sounds like sexual reproduction again doesn’t it?

Even metabolism appears to have a fractal order to it.  A large animal can eat another animal and some of that animals bacteria and parasites can take residence in its body.  A cell can eat another cell and incorporate the entire organism symbiotically as a new organelle.  A cell can eat another cell and get its genetic machinery hijacked on behalf of the other organism… a parasite… but when you think about it… who ate whom?  A digested organism can get it’s genes incorporated into the DNA of the host cell or the genes of a digested organism can hijack the host cells genetic machinery to make more of the digested DNA (or RNA), hence a virus.  Again… who ate whom?

*Isn’t it interesting how all of these biology videos always show the tiny molecular components that get used as parts for these genetic structures just streaming into their target destinations as if they have a will of their own?  What’s propelling them there? (Molecular noise?)

Finally a consumed organism can be digested right down to it’s sugars, proteins and nucleotides and used for fuel and parts.

In this view, eating and being eaten appear to be two sides of the same coin and sexual reproduction and eating another organism to incorporate its genome look the same as well.  The entire exercise looks like a continuum of increasingly sophisticated techniques for efficiently systematically searching for better self-designs by selectively cutting and pasting increasingly higher levels of abstract reproductive functionality.  When I’m trying to solve a complex coding problem I usually resort to Google to see if somebody else has solved it first before I resort to trying to build it myself.  If I can find the entire problem already solved I may adopt that code completely (get eaten), or I may need to comb through the code for a function that meets my needs.  Maybe I’m just struggling to find the best syntax for a problem so I’m only looking for inspiration from a line of code.  I seldom reach the conclusion that I need to write something in assembly language from scratch anymore.  Consequently the rate at which software systems have grown in size and lines of code have accelerated over time as more and more working code gets “consumed” by increasingly bigger more powerful software solutions.

Damn it, did I just sneak up on another metaphor for explaining sentience?  I just described a hierarchical (fractal) system of highly structured and systematic biological evolution that seems directly analogous to human coding… so how do I code again?  Is my brain a new level of abstraction that enables me to harness my internal ability to self-design, by cutting and pasting internal genetic patterns, and externalizing it into the world by designing tools?  It takes a lot less energy to hunt food if I can figure out how to grow it on a farm and breed it not to run away.  Reproduction is a lot easier and more efficient when I can use the internet to find new mates.  Finding better genetic designs is a lot faster when I can use my brain to design genes and try them on other animals without risking my own genome.  It sure does FEEL important to find that cure to cancer, now doesn’t it?

In order to code at an abstract level, say by swapping whole genes around instead of random nucleotides, I need to understand the concept of a gene at some level.  My brain needs to favor selecting random ideas that leverage higher levels of abstraction in favor of lower level ones.  My first instinct when I’m hungry is to order a pizza not to drink primordial soup.    If Domino’s isn’t open I may resort to spending more energy to construct a pizza for myself out of components and if I’m really desperate I might hunt and garden my own pizza components.  How does my brain understand the abstract idea of making complex things out of simpler parts and making simpler parts out of simpler steps?  I know that somebody who hasn’t read my other blogs will point out that a neural network can model that!  A neural network was NOT present when our cells relied on these abstract relationships and rules to construct us, our organs and our brains WITHOUT a brain to help them.

Amborella trichopoda (3173820625)-2.jpgSo we have a crazy new view of sex that equates reproduction and eating. Let’s see if we can map these odd notions to physical evidence?  Suppose we have a new theory of reproduction in which its purpose is systematic reproductive acceleration and efficiency through increasingly selective mutation and we have put eating and reproduction on the same logical continuum.  Sexually reproducing is essentially similar to ingesting another cell and incorporating its DNA.  When genetic incorporation is at the nucleotide level we call it eating and replication, at the gene level we call it infection and when it’s at the chromosome level we call it sex.  Let’s see if we can find an example of a creature that doesn’t distinguish a difference between lunch and sex?

The new research has shown that approximately 6,000 of the tardigrade’s genes come from foreign species, which equates to around 17.5 percent.  We had no idea that an animal genome could be composed of so much foreign DNA,” said study co-author Bob Goldstein, from the University of North Carolina at Chapel Hill. “We knew many animals acquire foreign genes, but we had no idea that it happens to this degree.”

So where is the Tardigrade getting all its genes from?

“The foreign DNA comes primarily from bacteria, but also from plants, fungi, and Archaea. And it’s this incredible variety of genes that researchers suggest has allowed the water bear to survive in such extreme conditions”

On the right we have a plant that appears to hoard DNA from many different organisms.

“They discovered the near complete genome of a moss mitochondrion broken into four pieces scattered throughout the genome. The Amborella mitochondrial genome also contained the remains of whole genomes from three different species of green algae that are known to form lichens and small amounts of DNA from at least one more algal donor as well. There were also about two extra sets’ worth of mitochondrial genes from what appear to be parasitic flowering plants. The vast collection has swelled Amborella’s mitochondrial genome to the size of a free-living bacterial genome.”

What’s interesting is that in both articles the scientists, who are of course “shocked” to discover lots of foreign DNA incorporated into the genomes of these very different creatures, twist themselves into pretzels trying to explain the phenomena.  In the case of the Tardigrade they propose that when the animal is desiccated, its genome just falls apart such that when it is re-hydrated it gets reassembled jumbled together with lots of foreign DNA that just happens to work fine.  Amborella on the other hand just happens to get wounded occasionally and merges DNA with other species accidentally which it never uses for anything.  Sounds plausible right?

What’s probably really going on here is that these organisms are having inter-species sex to capture new genetic material which may help it survive later under adverse conditions.  It’s far easier to copy a working gene from another organism that has proven it’s usefulness than it is to try to re-evolve the same functionality under environmental duress.  In many examples of species that engage in this behavior you also find scientists are completely mystified that the captured genetic material is not used for anything.

“This could be interpreted as evidence that extra DNA is a neutral force in evolution, which would support the longstanding orthodoxy—questioned by recent research from the ENCODE (Encyclopedia of DNA Elements) Consortium—that the vast majority of the non-gene coding DNA in our own genome is also “junk” that serves no purpose but also carries little or no price.

Some of this stuff is painful to read.  Of course biologists can’t discern a purpose for genomes to contain huge collections of apparently useless DNA, they’ve never had to write a program before.  When you consider the vast amount of evolutionary work that was invested in inventing new useful genes, it’s painfully obvious that it’s easier to keep a collection handy for emergencies in case you need them.  Cells don’t have access to Google to search for code samples for solutions to new environmental threats.  It’s vastly faster and more efficient to keep a library of old or borrowed genes around for a rainy day in case the cell has to evolve rapidly in response to a threat and needs a source of new ideas to try out IMMEDIATELY.

At the end they get so close to a coherent explanation…

“Maybe Amborella is not so different,” Sloan says. “Maybe this actually happens a lot—the insertion of these large genomes into plant mitochondria. But because it’s more stable in its evolution, we can actually observe it better and it doesn’t erase the footprints of those insertions as fast.”

This confusion stems from the persistent misconception that mutations are entirely random errors that are mostly destructive to an organisms chances of survival and that evolution proceeds in a completely undirected way.  They can’t see that biological machinery is optimized to select for mutations that accelerate and improve on themselves.  Organisms don’t actually care about their own survival or the perpetuation of a species, those are human motives, their only motive is reproducing and optimizing their ability to adapt as fast as possible.

Let’s return to the subject of sex.  At the beginning of this article we encountered this statement about RNA replication;

As a consequence of the lack of proofreading activity of RNA virus polymerases, new viral genetic variants are constantly created.”

Image result for amino acid codon encodingsIn the example of a virus, a high uncontrolled mutation rate is a feature, but our own proteins are also synthesized from mRNA strands.  In advanced organisms, which have evolved more abstract means of self-evolving, truly random nucleotide level genetic mutations are a real nuisance.  So our advanced genome has suppressed them… but not completely.  As we learned in high-school, all proteins are made out of 21 basic amino acids.  A codon is a six bit sequence of three 2-bit nucleotide pairs which can encode 64 different amino acids.  Why does our genome use six bits to encode a 5 bit number?  Mutation error correction!  All of the most dangerous single nucleotide mutations redundantly encode for the correct amino acids!  But if mutations are bad and evolution KNEW to use extra bits for error correction… why not use more bits to prevent mutation altogether?

Look up (Pro)line in the left hand chart and we see that all of the possible third nucleotide mutations redundantly code for the same acid.  In the right hand column we see that Arginine, one of the most complex amino acids has six encodings dedicated to it.  It must be a real disaster to get a base pair mutation for this acid especially since the most similar codons encode for STOP or Tryptophan!  Looking along the bottom row of the table on the right, we find that the family of related amino acids with hydrophobic side chains tend to share all the common single nucleotide mutations for one another, suggesting that nature doesn’t mind those acids getting mixed up with one another as much.  Valine is separated by one nucleotide mutation from Isoleucine, Alanine, Leucine, Tyrosine, Phenylolunine, and Methionine.

We are looking at the inner machinery of selective evolution at work.  If all possible base-pair mutations were equally likely, the table on the left would tell us a great deal about what mutations the cell considers acceptable and what mutations it really wants to avoid.  This is an example of our proverbial quantum change sorter at work.  Something causes a mutation in an RNA strand and this table decides whether the mutation should be fixed, incorrectly transcribed or cause the transcription to emergency terminate (Stop).  Take a look in the upper right hand corner of the table.   The stop codon pattern UGA is separated from the other stop codon patterns by two base pair mutations and Tryptophan has a single encoding surrounded by stop bits.  You do NOT want to mess up the encoding of Tryptophan for some reason!  Let’s look up Tryptophan’s function and see why it’s such a big deal not to allow mutations anywhere near it and to immediately abort an RNA transcription that messes it up.


” Biochemically derived from tryptophan,[9] serotonin is primarily found in the gastrointestinal tract (GI tract), blood platelets, and the central nervous system (CNS) of animals, including humans. It is popularly thought to be a contributor to feelings of well-being and happiness.[10]

Approximately 90% of the human body‘s total serotonin is located in the enterochromaffin cells in the GI tract, where it is used to regulate intestinal movements.[11][12] The serotonin is secreted luminally and basolaterally which leads to increased serotonin uptake by circulating platelets and activation after stimulation, which gives increased stimulation of myenteric neurons and gastrointestinal motility.[13] The remainder is synthesized in serotonergic neurons of the CNS, where it has various functions. These include the regulation of moodappetite, and sleep. Serotonin also has some cognitive functions, including memory and learning. Modulation of serotonin at synapses is thought to be a major action of several classes of pharmacological antidepressants.”

Whoa!  That looks like pretty essential stuff not to be playing creative mutation games with.  It seems pretty likely that a mutation in that codon will kill you!  So this table is the primal Rosetta Stone of  selective base pair mutations and it CLEARLY exhibits strong biases about what theoretically random mutations it will and will not accommodate.  This table encourages us to mess around creatively with the Hydrophobic amino acids, probably because they all subtly influence protein folding and most mutations to them will produce a harmless result.  Methionine has a single encoding planted right in the middle of all the common Hyrdophobic mutations.  God does not give a damn about mutations to this acid… look it up and it’s the common START codon for all RNA transcription… so if you mess it up, the RNA will be a dud and not get transcribed by the Ribosome at all, so no harm no foul!  It’s the single most harmless mutation imaginable just as the table suggests it should be.

It’s amazing how much the complex distribution of mutation error correction codes tells us about the importance of the various properties of amino acids to life.  But how do we KNOW that selective mutation is a DELIBERATE function of RNA transcription?  Easy… there is no chemical reason that codons could not be longer (encode more error correction bits) to nearly completely eliminate the possibility of all base pair mutations.  If mutations are undesirable errors… nature could have prevented them altogether.  This table TELLS us that the purpose of reproduction is NOT to perpetuate the organism or the species but to search for better species.  If the purpose of life were otherwise, it wouldn’t gamble the parents survival by tolerating mutations it could easily and obviously prevent.  To take the point a step further, if the probability distribution and error correction of this table were not extremely important to life we would see a great deal more variation in it across organisms given that it would be quite easy for it to mutate.  For some reason making slight changes to the entries in this table must kill you.  Perhaps it is because this table provides the standard RNA interface that enables wildly different and unrelated organisms to freely swap and transcribe one another’s RNA?  This table is what enables unrelated species to share/swap RNA, it’s a primitive form of gene-level sexual reproduction!  If RNA swapping were not an essential feature of living organisms there would be no evolutionary reason for the ribosomes that implement this table to be highly genetically conserved between wildly different organisms.   It would be a powerful immunological advantage for organisms to evolve ribosomes that make their machinery incompatible with invasive viruses and bacteria.  Furthermore if gene swapping between unrelated organisms were not common and vital to life, the structure of ribosomes could easily have diverged dramatically between isolated species… yet it does not???

Fact Sheet: rRNA in Evolutionary Studies and Environmental Sampling

“The ribosome is an ancient and essential component of cellular organisms, and its form and function is consistent across the spectrum of living things. A key aspect of ribosomes and ribosomal RNAs is that their function is very highly “conserved”, or maintained by natural selection, between and among species. “

To summarize:  From the ribosomal level down most organisms are effectively members of the same “species” and sharing a common means of RNA transcription across species makes inter-species sexual reproduction at the gene level possible and common.  At this level eating and sex are pretty interchangeable. Selective mutation is highly apparent when the function of the ribosomes error correction table is closely examined.

I’m not a biologist or a geneticist, I’m a computer scientist who specializes in computational physics simulation.  Where biologists see error, randomness, mistakes, and mutation, I see purpose.  To me the inside of living systems look like machines that write their own code.   I know that this view is well outside the established doctrine, but I’ve done my best to make a really sound case that our genetic machinery spells out it’s purpose and function in black and white for anybody sufficiently educated in mathematics and computer science to read. It TELLS us how it invents and tests new code.  So, I know  that what I’m going to observe next will sound like a huge leap, but watch this…

“The ribosome is an ancient and essential component of cellular organisms, and its form and function is consistent across the spectrum of living things. A key aspect of ribosomes and ribosomal RNAs is that their function is very highly “conserved”, or maintained by natural selection, between and among species. “

Think about WHAT this sentence is saying.   Among highly isolated unrelated species separated by massive evolutionary gulfs… the structure of ribosomes may change but their function has remained the same… they stay compatible with the RNA of wildly unrelated organisms despite massive evolutionary separation.  Why?  The prevailing view is that life is so fragile that the way ribosomes operate is the only stable formula for life.  Any tiny, evolutionary, mutagenic change to the function of a ribosome kills life.   I have another view… we’re never separated from other species and organisms which is why the ribosomes across completely unrelated species remain compatible.   Our genomes are constantly engaging in gene level sex with other species.  Our immune system doesn’t just fight off infections, it is constantly raiding other organisms for genetic samples and adding them to our DNA!

Every year we get several new flu strains, where do they come from?  The flu virus spreads via birds, pigs, people, you name it.  All of our collective immune systems attempt to kill the virus but it keeps mutating until it discovers a new improved design that nothing can stop, it finds a new way to bypass all of our biological defenses, then it reaches us again and retrains our immune system to be immune to the new improved virus for another year.   How does our immune system “learn” to be immune to the new virus?  It sends killer T cells to cites of infection and the killer T cells EAT the virus and then bring it’s partially digested corpse back to our Thymus gland which promptly GENETICALLY MODIFIES our immune cells to produce B cells that recognize and attack the virus in our bloodstream before it can infect cells directly.

The process is called somatic hypermutation…


Experimental evidence supports the view that the mechanism of SHM involves deamination of cytosine to uracil in DNA by an enzyme called Activation-Induced (Cytidine) Deaminase, or AID.[14][15] A cytosine:guanine pair is thus directly mutated to a uracil:guanine mismatch. Uracil residues are not normally found in DNA, therefore, to maintain the integrity of the genome, most of these mutations must be repaired by high-fidelity Base excision repair enzymes. The uracil bases are removed by the repair enzyme, uracil-DNA glycosylase.[15] Error-prone DNA polymerases are then recruited to fill in the gap and create mutations.[14][16]

The synthesis of this new DNA involves error-prone DNA polymerases, which often introduce mutations at the position of the deaminated cytosine itself or neighboring base pairs. During B cell division the immunoglobulin variable region DNA is transcribed and translated. The introduction of mutations in the rapidly proliferating population of B cells ultimately culminates in the production of thousands of B cells, possessing slightly different receptors and varying specificity for the antigen, from which the B cell with highest affinities for the antigen can be selected. The B cells with the greatest affinity will then be selected to differentiate into plasma cells producing antibody and long-lived memory B cells contributing to enhanced immune responses upon reinfection.[2]

The hypermutation process also utilizes cells that auto-select against the ‘signature’ of an organism’s own cells. It is hypothesized that failures of this auto-selection process may also lead to the development of an auto-immune response.[17]

Allow me to spell that out in clear terms… the thymus gland incorporates the DNA/RNA of attacking viruses and bacterium into the DNA of our immune cells and then deliberately runs a systematic mutation driven search for an antigen that optimally recognizes the disease… then it mass produces the vaccine it just invented.  *The bottom sentence is telling us that this process is the source of our allergies as well.  A few things should jump out of this observation.

  1. The immune system actively designs new vaccines by DELIBERATELY incorporating foreign DNA and engaging in systematic mutation.  Biologists KNOW it, and still think of mutations as errors.
  2. If our biology thought catching the flu virus was a BAD THING to be avoided… why DON’T we evolve a ribosome that is incompatible with foreign RNA?  Why do we and other species STAY compatible with the FLU!!!!
  3. Because of observation 1… we couldn’t design a vaccine for the bug if our immune system DNA were not compatible with the virus!  But we wouldn’t NEED to do that if we just evolved flu incompatible Ribosomes!  Paradox!!!!
  4. Unless we are catching the virus on purpose for some reason!

Why would we be catching viruses on purpose???  We have an immune system that is intelligent enough to deliberately harness mutation to design new vaccines.  Why would that be the only kind of mutation it was smart enough to harness?  Viruses and bacterium are disposable mutation laboratories, send them out to get their genome trained by ALL of the world’s immune systems and bring them home to share all of the collective wisdom they have gathered from all the worlds people, birds, pigs, bats, you name it… then incorporate their DNA into our genome?  I know, that sounds crazy right?  The wiki says “somatic” mutations, which means that the immune cells are the only ones that get mutated.  Those mutations don’t actually get passed on to our children.  Because after we spend a lifetime of GENETICALLY re-engineering our immune systems to resist deadly diseases that afflict our current world… why would we bother to pass that essential-to-survival information on to our children?

Unlike germline mutation, SHM affects only an organism’s individual immune cells, and the mutations are not normally transmitted to the organism’s offspring[2] except in those circumstances associated with the antigen-driven somatic and germline evolution of germline V segment arrays, so called soma-to-germline feedback or Lamarckian inheritance effects.

Wait… what’s that about Lamarckian inheritance effects?

soma-to-germline feedback or Lamarckian inheritanc

Image result for fruit

Fruiting: Plants can use seed-bearing fruit to encourage animals to eat the seeds. They will then be spread when the waste is excreted after digestion. This is a process of endozoochory.

Published March 2015… why yes OBVIOUSLY immune information learned by our genomes during adulthood DOES get passed on to our children via SELECTED germ-line mutations…  What kind of moronic divine engineer would design an immune system that dedicated itself to harnessing the entire world’s biome to design superior disease antigens just to throw away the information during reproduction?  We consider the flu to be a debilitating inconvenience but if the purpose of reproduction is to find better code for life, then our personal inconvenience is secondary to life’s primary goal of writing more efficient code using every resource at its disposal.  Think about how much information about the rest of the world’s health and immune state a successfully mutated flu virus teaches our immune system.  If the AVIAN flu virus hasn’t mutated much this year, life must be tough out there for ducks and chickens.  If the pig virus mutated a lot, you must not be living close enough to pigs.  All of their immune systems will have tried nearly the same antigen mutation permutations you tried.  If they’re all immune to the other variations of the virus, then you don’t have to worry about keeping the same antigens around either and can devote your defensive resources elsewhere.  Hell, if your immune system doesn’t do it’s best to prevent disease spreading among pigs and birds… what are you going to eat?

We’re still stuck in a logical paradox… we wouldn’t need to bother with all of this deliberate mutation if we just evolved incompatible ribosomes… but now it appears that I’ve answered my own question.  We would starve to death if we did that.  Our proteins would be incompatible with the proteins of the food we eat.  We would have to construct all of our constituent building blocks of life from first principles requiring great energy if we weren’t already compatible with the genomes of our food!  In other words, we have to agree to risk being eaten if we want to be able to eat.  We’re also cooperating and communicating with all other life forms to invent and distribute better genes via disease.  Perhaps the purpose of viruses is to ensure that our ribosomes REMAIN compatible with those of distantly related species because ALL life benefits from being mutually genetically compatible?

Crazy stuff, I know, but I try to follow the logic where it leads.  So far I think I’ve done a pretty good job of making the case that genetic mutation is highly regulated, deliberate and remarkably intelligent.  The immune system deliberately incorporating invasive DNA, designing vaccines and passing what it has learned on to our children’s genes is just one of many remarkable examples of this phenomena.  I chose to highlight it because it’s just slightly better understood than the many other places we encounter it in our biology that is still mystifying the biologists.


“”Jumping genes” are ubiquitous. Every domain of life hosts these sequences of DNA that can “jump” from one position to another along a chromosome; in fact, nearly half the human genome is made up of jumping genes. Scientists have now observed jumping gene activity in real time within living cells.”

So you’re whole genome is mutating all the time, that includes the neurons in your brain while you are thinking.

“What’s more, we learned that the rates at which these genes jump depend sensitively on how the cells are growing–if there is food available for the cells to grow, for example. In other words, jumping gene activation isn’t entirely random, it’s dependent on environmental feedback.”

It took them until 2016 to “discover” this phenomena.  They should have just been reading my blog.   Wait.. wait… they just discovered that it’s not “random”… let’s see how they try to explain it…

“Goldenfeld’s team developed computer simulations of the growth of bacterial colonies and predicted what the experimental signal would look like in the random case. These calculations showed that the experiments could not simply be interpreted as random transposon activity and even provided clues as to sources of non-randomness, including environmental feedback and heredity.”

The NOT RANDOM thing is HUGE news to these guys.  That’s just blowing their minds out there.  They’re right on the brink of discovering that mutation is deliberate… just give them another 10-20 years.  I like this article from a decade ago when they just realized that brain cells actively genetically mutate.


“There is some evidence, however, that the jumping genes actually target places in the code where they can make a difference.?”

12 years since this was published and they’re STILL mystified by the not-random thing.  In my next blog article we’ll try to take a look deep inside the cell to see EXACTLY how all these tiny floating molecules seem to know exactly where to go in order to work correctly and exactly how tiny base-pair scale mutations take place again… systematically.

Exchange genes with distantly related organisms to train immune system, exchange genetic fragments and ensure that all living things remain edible.   Eat related organisms to get genes, easily recycled calories, proteins and vitamins as well as potentially beneficial microbes.  Mate with closely related “species” to exchange chromosomes and immunities.



  1. I have been following your quest with great interest. The essential question lingers: are you doing something tangible around this? Like a computer simulation using Cuda…

    Personally I am interested in the toolset that would allow to more directly code, run and debug genes without having to each time resort to chemically splitting protein chains. If genomes are “self-coded” via near-magical parameters of water noise, is it even theoretically possible to write functional genome code manually, or are there too many parameters for human mind to grasp while coding? What could be a higher level language to describe what kind of “genome” we wish to code? Now we are looking at the assembler level if even that.

    • It’s a lot of work, but yes. My early simulators made me realize that I might not live long enough to have access to the computing power necessary to simulating say, a single cell at the quantum level, unless there are some immediate general changes to computer architecture that get you several orders of magnitude in speed without scaling cost proportionately. I’ve created a technology that increases the compute density on GPU’s several orders of magnitude. Basically we ported the Linux storage architecture to the GPU such that file IO and data processing are the same event now. It massively accelerates the sheer volume of data you can pour through the GPU at maximum IO speeds. We use the GPU to parallelize storage to get storage speeds approaching RAM throughput. Imagine that for data block transactions > 1MB your file-system can look like RAM enabling the GPU to address many petabytes of data. Then you need to build data structures that can sparsely address massive address ranges.

      Just as a worst case, bad example, suppose you need to address trillions of water molecules mutually interacting with plank-length address resolution? Each Hydrogen atom alone would require;
      1H Atom “diameter” ≈ 1.1×10–10–10 m ≈ 6.81×10^24 ℓPP. You might need something on the order of ~2^100 bit addressing.

      Imagine that you need many parallel computers to simultaneously be able to randomly address and cluster thousands of samples of data separated in “memory” by many exabytes. You can’t really begin to tackle the modeling problem without solving data processing and storage on those scales first.

      We’re working on solving the same class of massive scale storage-processing problem for the Square Kilometer Array Precursor. They need to image the entire Universe.

      Once you can address a large enough virtual space with enough concentrated compute power, it’s possible to talk about building practical quantum simulations on that scale.

      Step 1: Make a business out of addressing data volumes at high speeds on massive (sparse) scales.

      • I understand your viewpoint and such data addressing capability is essential for many tasks at hand. But since we can execute the genetic code in vivo right now inside living cells without simulators, I still think there’s something between current chemical genome hacking (basically like cutting pieces of 70’s computer code magnetic tape and gluing them to another tape, without knowing source code) and full-blown quantum mechanics simulator large enough to hold at least one cell in it.

        Engineers always want to throw more processing power to problems that mathematicians solve with clever shortcuts. I am not saying that is necessarily the case here, quite the opposite actually looking back at the neural network hype that was supposed to be a clever shortcut, but…

        If we could decrypt a kind of source code format for genetic code, and create a working linker and disassembler, we could most likely proof/dry run it with current computer power; and then actually execute and maybe even debug it in living cells. Functioning universe would be our raw processing power provider.

        I can’t help wondering what that source code would look like. Because of the execution structure of genetic code, it would be so different from any current computer language that only the basic idea behind the word would remain.

        • The problem is our DNA doesn’t actually work that way as it turns out. They were all wrong about it. The nucleus and cytoplasm appear to contain a vast amount of state information essential to life. Even if we could “execute” our DNA like a program, we would not get a living system. The degree to which we try to think of it as analogous to a digital computer is the degree to which we will continue to be mystified by it.

          We got to modern 3D architectures from the bottom up, not the top down. I studied 3D in the 1980’s because I was interested in the same things I’m interested in now, physics simulation. One of the statements that was made in a class I attended was that we would not see real-time 3D rendering for 30 years given Moore’s Law and the computing requirements associated with doing a physical rendering simulation of light. They were CORRECT… we have real-time 3D today in-part because I got that message and concluded that we would have to find ways to compromise physics to achieve a real-time 3D “Illusion”. The big breakthrough in real-time 3D was the Zbuffer and stencil buffer and later the parallel pixel shader. These data structures were not obvious ideas at the time, if we didn’t understand the initial physics rules deeply, we weren’t in a position to invent ways to break those rules successfully. We have that same problem with AI, climate modeling and physics simulation today. We have no slow but complete working model of physics such that we can explore the trade-offs associated with taking shortcuts as we did with early 3D graphics. We don’t understand the problem we’re trying to solve and therefore… can’t be solving it by just trying random stuff that sounds good but has no deep foundation.

          I agree with you that shortcuts exist, we won’t find them without a bottom up approach… we would have found them by now if that was going to work. I also agree that we’ll build much more powerful computers when we stop trying to design computers that hide natures chaos in favor of designing computers that rely on it.

  2. That is why I tried to emphasize that we lack even the terms to describe what genetic code is. It is obvious it is not in almost any way comparable to digital code. I see it more like enabling parameters that with right kind of interference can execute and self-modify. The interference can certainly not be random but has to be within famorable bounds. Whether these parameters are called “code”, state information or data does not really describe their function, they are all those mixed together in a way difficult for SW people to comprehend. Difficult, but maybe not impossible.

    I am certain the deeper understanding to this will not come from microbiologists, chemists or so called experts of human cell and genome. It will come from genius coders that can step beoynd the box of digital code, and from mathematicians who can step beyong the bounds of true/untrue. There are not very many people alive who can and would do that, and it is most likely they dont stem from current academic circles.

    But let me ask when do you think something tangible (in terms of function of life) could emergy from your big access/big data project?

    • It will take a long time. It will take a lot of new code and infrastructure to make a million GPU’s function as though they are addressing Exabytes of GPU speed RAM. We’ll be able to do it BEFORE we have that much RAM in a single physical address space, but I think that’s the scale we have to get to. Bitcoin has shown us a new way to get there. I’m going to say at least 5 years. You’ll see some miraculous tech out of me before then but artificial life needs a lot of progress.


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