Drs. Sanford and Carter respond to PS Scientists

[John_Harshman]

@Rumraket

If I understand correctly, you’re saying the so-called “zone of no selection” will widen to include mutations of stronger effects?

Yes. The value of s that is subject to selection varies directly with Ne.

[Giltil (Gilbert Thill)]

@John_Harshman

That’s a point worth considering: as GE progresses and the population decreases in size, the selection coefficient of alleles that can’t be eliminated by selection will become more negative, thus accelerating the GE.

And this has been observed many times in isolated population, hasn’t it?

[Rumraket (Mikkel R.)]

@John_Harshman

Yes. The value of s that is subject to selection varies directly with Ne.

Ahh yes, as the population gets smaller the relative influence of drift increases. That’s regardless of whether GE is true or not, of course.

[John_Harshman]

@Rumraket

Ahh yes ofc, as the population gets smaller the relative influence of drift increases.

Yes. I meant “inversely”, of course. The smaller the population, the bigger the value of s for which drift dominates.

[Rumraket (Mikkel R.)]

@Giltil

And this has been observed many times in isolated population, hasn’t it?

Is it your impression that because extinction can happen under conditions of persistent bottlenecking this is somehow incompatible with the theory of evolution?

[Giltil (Gilbert Thill)]

No, it isn’t.

[Rumraket (Mikkel R.)]

Okay. Then I have to assume there’s some key aspect of your argument I’m missing?

[PDPrice (Paul Price)]

@evograd

I think you mean 1,000,000 to 1

Yes, I did mean that.

@evograd

or even 100 to 1

That one is self-evidently false. I don’t even need to read that to know there’s some funny-business going on there.

Thanks for everybody’s time, but I don’t really have anything more to present for you. I hope my answers have been helpful for that small minority of viewers here that (possibly) may be looking at this from an open-minded perspective. I encourage all to read the joint article linked in the OP, and thanks for engaging.

[Michael_Okoko]

@PDPrice

Thanks for everybody’s time, but I don’t really have anything more to present for you. I hope my answers have been helpful for that small minority of viewers here that (possibly) may be looking at this from an open-minded perspective. I encourage all to read the joint article linked in the OP, and thanks for engaging.

Thanks for the discussion. It further exposed the weakness of GE.

To the readers, it’s pertinent you look for the specific claims made by Paul Price and the article and see if they fit with the data. For example, he claims the DFE for slightly neutral mutations are mostly deleterious, but he doesn’t give any data to support this. Also observe that commenters here don’t just offer dismissive answers, they substantiate their objections to the claims of GE. Don’t fall for his trick that those who object to GE are not open-minded, they are. They object to it because it is not well-supported.

Thanks again Paul, maybe we will see more articles again on this in the future.

[Rumraket (Mikkel R.)]

@PDPrice

That one is self-evidently false.

It is self-evidently true.

[T_aquaticus]

@Dan_Eastwood

If the population remains nearly uniform, then I would agree, but accumulating mutations imply increasing variation, therefore a non-uniform distribution.

This would seem to be the case with influenza viruses. All of the viral lineages are replicating continuously and would all be suffering GE at the same rate, and yet recombination between lineages can result in an increase in fitness. If this can happen in viruses then it should also apply to alleles in more complex eukaryotes.

[T_aquaticus]

@PDPrice

Regarding your question of how we can say they outweigh the beneficials, it is simply put because beneficial mutations are so rare as to be nearly non-existent, just like typos that add to the meaning of typed text in a useful way are nearly non-existent. One published estimate of the ratio is 1,000,000 to 1 (Gerrish and Lenski).

You are forgetting amplitude again. If the increase in fitness of one beneficial mutation outweighs the combined deleterious effect of 10,000,000 VSD’s then fitness will increase.

@PDPrice

Another way you can infer the DFE of mutations is to look at ageing. One of the chief causes of ageing is the buildup of mutations over our lifespan in our somatic cells. Lynch says that by the time one is sixty years old, one’s somatic cells have accumulated on average about 40,000 mutations (each cell has its own set).

You are making the assumption that aging is due to the accumulation of mutations.

[PDPrice (Paul Price)]

@T_aquaticus

You are forgetting amplitude again. If the increase in fitness of one beneficial mutation outweighs the combined deleterious effect of 10,000,000 VSD’s then fitness will increase.

This is the mega-beneficial mutation claim. Dr Sanford specifically addressed that in his book. Will you read it please?

@T_aquaticus

You are making the assumption that aging is due to the accumulation of mutations.

No, that’s a fact, not an assumption.

[T_aquaticus]

@PDPrice

This is the mega-beneficial mutation claim. Dr Sanford specifically addressed that in his book. Will you read it please?

You have read the book, so why don’t you explain it? Where are the references demonstrating the amplitude of effect of both VSD’s and beneficial mutations?

@PDPrice

No, that’s a fact, not an assumption.

References?

[PDPrice (Paul Price)]

@T_aquaticus

You have read the book, so why don’t you explain it? Where are the references demonstrating the amplitude of effect of both VSD’s and beneficial mutations?

I also dealt with this at https://creation.com/genetic-entropy-vs-evolution

Despite this, Kimura never questioned the notion of evolution. He took it on faith that occasional mega-beneficial mutations would cancel out the effect of this gradual decline:

"Whether such a small rate of deterioration in fitness constitutes a threat to the survival and welfare of the species (not to the individual) is a moot point, but this will easily be taken care of by adaptive gene substitutions that must occur from time to time (say once every few hundred generations)."10,11

But there is no evidence to justify Kimura’s wishful speculation. The evidence shows the opposite: given enough time, organisms will eventually succumb to the weight of the damaging mutations that accumulate gradually, and will go extinct.[12] In fact, a paper presented by Sanford and others at a symposium on information at Cornell University demonstrated that lots of such ‘high-impact’ beneficial mutations would actually hasten extinction. They “strongly interfere with selection for or against all low-impact mutations”, which makes the problem of genetic entropy worse.[13]

@T_aquaticus

@PDPrice

No, that’s a fact, not an assumption.

References?

Here’s one:

Which Is the Most Significant Cause of Aging? - PMC.

Mutations are not the only cause of ageing. But they are certainly a very significant one.

[T_aquaticus]

@PDPrice

I also dealt with this at https://creation.com/genetic-entropy-vs-evolution

The claims about viruses has already been refuted. Influenza viruses have been continuously replicating for millennia, and they have not gone extinct. Your made up “reservoirs” don’t exist.

You also have not cited any evidence for the relative effect of VSD’s and beneficial mutations. It isn’t enough to say that there are more VSD’s than beneficial mutations. You must show the amplitude of the effect.

@PDPrice

Mutations are not the only cause of ageing. But they are certainly a very significant one.

How significant? Why do some species live only a few years while others live for more than one hundred years?

[chris_doesdna2018 (Chris Hughes)]

@PDPrice

Despite this, Kimura never questioned the notion of evolution. He took it on faith that occasional mega-beneficial mutations would cancel out the effect of this gradual decline:

"Whether such a small rate of deterioration in fitness constitutes a threat to the survival and welfare of the species (not to the individual) is a moot point, but this will easily be taken care of by adaptive gene substitutions that must occur from time to time (say once every few hundred generations)."10,11

Empirical data suggests the probability of a beneficial amino-acid altering mutation in the human population (Pb) is 2.3e–5 (95% CI: 2.2e–6 to 7.6e–3) with a mean selection coefficient (Sb) equal to 0.0064 (95% CI: 0.0007 to 0.1084).

Castellano, D., MacIà, M. C., Tataru, P., Bataillon, T. & Munch, K. Comparison of the full distribution of fitness effects of new amino acid mutations across great apes. Genetics 213 , 953–966 (2019).

Presumably these are not the “mega-beneficials” Sanford refers to–seeing as this paper was written after Sanford wrote his book.

[RonSewell (RonS)]

@CrisprCAS9

All models are wrong, some models are useful.

So true. Sanford’s model comes across as, “see, we have mathematically disproved evolution”, and his audience not appreciate the math can be sound, but fail to properly represent nature. It may be possible that working scientists too become overly attached to their models.

I would not want to press the analogy too hard, but when I see these curves ending in genetic catastrophe, I am somewhat reminded of the black body radiation ultraviolet catastrophe, which was an entirely solid mathematical formulation based on reliable physics, except that the catastrophic outcome was never observed to materialize. Planck saw that it was the smooth curve that was the issue.

Back in public school, everybody has learned from their ill informed classmates that it has been proven that bumblebees cannot fly. A less banal and more recent update to this sort of discussion took the form of a recent Scientific American article titled No One Can Explain Why Planes Stay in the Air, which elicited a flurry of letters to the editor from aeronautical engineers in fact offering explanations. The truth is that while we know much, there remains more to learn. Models are abstractions which at best approximate nature.

Models become more useful the closer they track the actual messiness of nature. Having followed some of the vigorous disagreement here between very qualified individuals, it is apparent that the existence of drift, selection, and the spectrum of mutation is not in dispute, but there is much room for refinement in the weighting of contribution and compensation. This is the useful role of models; it is the divergence between prediction and observation which tells of the trail to follow. They are not meant to eclipse the data itself.

Planes do fly and living things still populate the earth, so models which conclude to the contrary cannot be complete or correct. @glipsnort has identified three premises of Sanford’s model which GE presumes but none of which has been demonstrated to be justified. In my mind, all such models, whether from Sanford or in the conventional literature, to be realistic have to eventually account for effects of classes of mutation, be they in coding, regulatory, structural, or DNA with no discernable function. If all mutations are held to be deleterious, whether slightly, ever so slightly, or infinitesimally slightly, what exactly is deleterious about mutation in pseudogenes, already degraded ERV segments, and so forth, must be identified and physiological impact detailed, or else the reasonable conclusion is that such mutations are of zero impact, individually or in aggregate. There may be considerable curve discontinuities in the zone of deleterious but not selectable mutation. The model must account for the relationship of genome conservation vs fitness distribution. These demands are not “rescuing devices” for evolution, this is what models are for - to sort out the underlying principles of the empirical world. As attributed to Einstein, everything should be as simple as possible, but no simpler. A population model and set of parameters cannot be so simple that it demands that viruses, flies, mice, and given the antiquity of the earth, everything else, be dead a hundred times over or else we would not be here to do the modeling.

[Rumraket (Mikkel R.)]

@chris_doesdna2018

Comparison of the full distribution of fitness effects of new amino acid mutations across great apes.

Sanford apparently considers a 1% fitness increase to be a “mega” beneficial effect. LOL

[CrisprCAS9]

@RonSewell

the math can be sound

That’s already generous…