So, genetic entropy posits that deleterious mutations are progressively messing up our genome with each generation from the fit platonic ideals which were created 6000 years ago. This is presented as a scientific investigation, even though, as has been pointed out above, the idea requires that all of geology and much of the rest of science be jettisoned. However, even though much of the intended audience accepts a young earth, the question arises, if all these mutations lead to extinction why do bacteria, which typically goes through more generations that a person has days, still persist.
Well, the get out of jail card played is âthey are simple organisms, resistant to mutation, yada yada.â So an organism which has churned through 2,190,000 generations, allowing for a day per division from creation, is in better shape than mankind with say 300. That sounds pretty ad hoc, but the takeaway is that genetic entropy is not held to assert to the same degree with simple organisms. So we have what purports to be an answer.
But wait! Didnât Sanford write a paper with Robert Carter, where âThe purpose of the paper was to see if we could find genetic entropy in action, and we didâthe viral strain (the human version of H1N1) significantly degraded over time as a result of damaging mutations, eventually going extinct.â? Aside from the fact the term âgenetic entropyâ does not appear anywhere in the paper, which is questionable given its stated purpose, one might ask, what happened to the simple organism qualification??? Is not the virus simple? Bacteria resist extinction all the way from creation. Sanford has the 1918 influenza sputtering out in a few years, and this is promoted as an example of genetic entropy in action. So now the ad hoc exception has an ad hoc exception.
But wait! If H1N1 is an example of genetic decay which took place right before our eyes, where was it hiding for the 5900 years before the pandemic of 1918? How did did the virus resist genetic entropy before it got all entropied during the pandemic. Well, it was dormant in a reservoir or something! So now the ad hoc exception has an ad hoc exception to the ad hoc exception.
And Paul presents that biologists do not take Sanford seriously because they are worried about their academic standing. What a waste of time.
An exception, yes, but not ad hoc. This was an example involving an RNA virus, and RNA viruses have much higher mutation rates. Thus, faster GE.
This has to do with how we get infectious viruses in the first place. Prior to that time, it had apparently not yet jumped over to humans from its original animal host. When viruses jump to the wrong kind of host, they start running out of control, and natureâs stabilization and control mechanisms no longer function. I recommend checking out the box at the bottom of the page here: Fitness and Reductive Evolution as well as the other articles linked from there.
There are a bunch of others here who are well-versed in population genetics.
Youâre wrong about ânobodyâ. Check out videos by Granville Sewell and by Mark Champneys. They try very hard to establish that there is some sense in which the Second Law of Thermodynamics establishes that.
I donât disagree with the quotes but I notice that you do not discuss natural selection and what happens after that is included. Letâs take three cases: One with selection coefficient +0.001, one with selection coefficient 0, and one with selection coefficient -0.001. (Letâs consider a haploid organism to make things simple). The population size is 100,000. We consider these three cases: in each one the mutant is initially present as a single copy.
What is the fixation probability in each of these three cases? How many times more deleterious mutations would there have to be for there to be more fixations of deleterious mutations fixed than advantageous ones?
I have no views as to its exact shape. Qualitatively, there are two relevant regimes, one in which genetic drift is dominant and one where selection is dominant, with the fuzzy crossover region occurring around abs(s) = 1/2Ne, where s is the selection coefficient and Ne the effective population size. For abs(s) much larger than that, deleterious alleles are far more common than beneficial ones, and the tail of the deleterious distribution is much fatter. In this regime, deleterious alleles have a mean frequency given by mutation-selection balance. In the drift regime, by contrast, beneficial and deleterious mutations occur at similar rates.
As for why I think this, youâve already been told several times by various people. As you yourself have pointed out, there are far, far more sequence configurations that are suboptimal than there are optimal ones. For configurations that differ only by the kind of tiny fitness differences weâre talking about, the chance of the optimal configuration occurring by chance is exceedingly small. There is also (by definition) no way for natural selection to have generated the optimal configuration, since these differences are invisible to selection. Therefore, there is no reason to think the genome was ever in that optimal state. Instead, an actual genome is one randomly chosen configuration from among all of the selectively equivalent configurations, and effectively neutral mutations take move it to other selectively equivalent configurations. The precise fitness of the genome will drift up and down very slightly, but changes are as likely to be positive as negative.
Note that this assumes a constant size for the population in question. If the population has gotten smaller, a new class of mutations becomes invisible to selection and these mildly deleterious mutations will accumulate until a new equilibrium is reached.
Which is both true and, yes, irrelevant. Mutations that change or eliminate gene function will almost always have fitness effects much larger than the ones Sanford requires.
But you think theyâre also much simpler, so that doesnât follow if you donât have a measure of simplicity so you can derive the relationship between simplicity, mutation-rate, and GE.
You say that âSimpler genomes mean less genetic entropyâ, but since you donât have such a measure of âsimplicityâ and have no idea how it actually relates to the DFE of mutations, you canât actually claim to know that the rate of GE should be higher for RNA viruses.
Technically this has to be physically impossible. At one point youâre going to have completely broken gene function and reached some stage where itâs effect has reached itâs lowest possible state.
At this stage, only mutations that either donât further affect the degree of function, or increase gene function are possible(the only direction away from the lowest possible state is up), and must therefore outnumber mutations that reduce or eliminate gene function, since you canât reduce or eliminate a function that already reached itâs lowest possible state.
My favorite is the way they discuss function when talking about current systems versus abiogenesis.
Current systems: The slightest hint that it even âcouldâ do something = 100% functional
Abiogenesis: If it isnât a full complement of modern proteins, it isnât functional at all!!1!
RNA viruses only have much higher mutation rates when in human hosts? What stabilization and control mechanisms no longer function? Please do reply with something about âdormancyâ.
That is nonsense. It might work in the sanctuary auditorium, but as science genetic entropy does not even stand up to the most rudimentary line of questioning. Consistency is hard to maintain when the facts are not on your side.
I donât follow Sanfordâs work closely, but as far as I can tell heâs mounted two distinct arguments, one (in the paper you cite) that deleterious mutations overwhelm purifying selection and lead to inexorable decline, and the other (his original genetic entropy argument) that deleterious mutations invisible to selection accumulate and lead to inexorable decline. Either way, things are going to hell, but the mechanisms differ.
Both versions of that argument are based on a (seemingly deliberate) misreading of Kimura, 1979, which is the basis for both the figure representing the distribution of fitness effects in âGenetic Entropy and the Mystery of the Genomeâ (the âCorrect Distribution!â figure) and the gamma distribution of figure 1 in Basener and Sanford (2018).