Dr. Sanford himself would likely agree that GE is difficult if not impossible to directly measure. If we could directly measure GE, then we could tell you when coronavirus 2019 will go extinct. We could also tell you how long before humans go extinct as well.
I don’t agree however, that the conclusion it is happening is not well founded. We can have good reasons to believe something even if we cannot precisely measure it. We can be very confident that each year there will be hurricanes, even though we cannot tell you exactly when they’ll hit or how powerful they’ll be.
For GE not to happen, things have to be neatly balanced on our chart. Especially as it regards the ratio of beneficial to deleterious e. neutrals. The problem is, nobody can seem to give a satisfying explanation for how that might be possible.
How is it possible for there to be an equilibrium if the volume of fitness effect isn’t the same on both sides of the Y axis for effectively neutral mutations? For this class of mutations, we cannot appeal to selection as a means of balancing them out.
As in this illustration of a scale with unequal arms, the weight is multiplied by the length of the arm. I think if we define volume an the integral of population density over fitness, we are saying the same thing.
Beneficial mutations tend to stay in the population longer than deleterious mutations.[edit: not always so. see reply] As deleterious mutations are selected out of the population, the balance shifts closer to the optimum (or high-end, if not optimum). It’s like taking weights off one arm of the scale, kind of.
That might be true too, but GE is different than the shape of the DFE. So measuring GE is different than measuring the fitness function, or DFE, peak near zero.
If you don’t know what this peak looks like near zero, you can’t make a confident argument that depends on details about this peak. That seriously undermines the GE argument on a conceptual level.
And in fact, if the skew was such that GE was true, observing continuous fitness increase should be impossible. Fitness declines in ALL Sanford’s models that contain DFE of mutations that Sanford consider realistic. But we can measure fitness increase in the real world.
And this is where we get to the sleight of hand. Now Sanford, Carter, Price and so on change the relevant definition to “integrity of information in the genome”, so all that talk about the shape of Kimura’s curve goes out the window. And Price will introduce a new concept like “simplicity” that he thinks affects the shape of the curve, but he can’t tell us how much.
Question: Can we really measure fitness increase in a stable population? On second thought that is a silly question → increase is necessarily requires something to improve, therefore not a stable population.
Catch that @PDPrice? Its another serious critique.
We cannot equivocate fitness with things like “integrity of information in the genome." Those are not the same things, nor is the second term well-defined in context.
Since the info in the genome is what produces the phenotype, and since the phenotype is what is either more or less fit, then we should expect there to be a very strong relationship between the fitness of the organism and the integrity of its information. The reason we humans exist as we do, with all the abilities for survival that we have, is because of the information in our genome.
I agree this is a difficulty of this whole topic. But all of us must face this same difficulty. It isn’t only a problem for Sanford, but somehow not a problem for evolutionists.
It is not a problem for me because I’m not making an argument that depends on that equivocation. If I were to make such an argument, it would become a problem.
Edit: I’d also rightly get raked over the coals if I did not make that issue clear up front, and overstated the confidence of my findings by neglecting this uncertainty.
There must either be a balance of overall effect, or the imbalance must be in the positive direction. Otherwise, we are headed toward extinction. But all the real world data skew strongly in the negative, not the positive direction. Dr. Schaffner has confirmed that the reason we see fewer selectable beneficials on our chart is that they are affecting an optimized genome. I hope he’ll explain why he feels that fact won’t affect the e. neutrals on the beneficial side.
Which is to say you agree with me? It does not need to be a balance of overall effect if the balance is in the positive direction. Even if the imbalance is the other direction, that is not necessarily a problem either, but that’s another discussion.
I don’t see how that’s another discussion. That is in fact the discussion I’ve been trying to have this entire time. If the overall fitness effects for effectively neutral mutations collectively are imbalanced toward negative effects, then that means we have an overall negative trend.
There must be SOME relationship, I would agree with that much. But it really does matter how this relationship looks, and you can’t just sort of wave your hand and say it is “very strong” and with that pretend it’s always directly proportional and therefore not really a significant problem.
Because, again to pick the example of the LTEE, here you would say the “integrity of information in the genome” is going down, right? There are entire articles on AIG and related creationist and ID sites devoted to the idea that the LTEE is an example of loss, breaking of genes, devolution etc. etc. The organisms in Lenski’s experiment are losing functional, but unnecessary genetic material. Inactivation of genes that would work on nutrients not present in the environment is beneficial. Deletions are favored in competition for limited resources in the flask, so replication speed (and the cost of replication) matters because faster replication at a lower cost allows more offspring to be churned over a given interval of time, and more individuals can consume a greater proportion of those limited resources. And so on and so forth.
But that means reproductive fitness is going up, while the “integrity of information in the genome” is going down. So they are NOT correlated in proportion to each other. There is not some absolute measure of the perfect organism, it all depends on the circumstance. Some times loss of functional genes is adaptive. But then your whole thesis collapses. The sleight of hand is bunk.
Highly specific niches can provide temporary counterexamples where jettisoning unnecessary information can help out, in the short run. But you can’t just keep doing this. There’s a certain minimum amount of required information to make the organism work at all. So even though there can be patches where the correlation gets weaker or even goes in the opposite direction during “reductive evolution”, ultimately they must come back together and meet up again.
The effect of genetic drift is pronounced in small populations (gene pools). There are nearly 8 billion humans and people mix, travel, migrate. We may be in danger of extinction but not from decrease in genetic diversity.
Fitness depends on the niche. And in the real world, niches can change, imperceptibly, cyclically, catastrophically. Pencils don’t stay balanced on their point.
In reading one of the papers from the LTEE the concept of diminishing returns epistasis was mentioned, which also helps explain why it has to be physically true that the shape of the curve for the DFE of mutations must change over time as organisms become either more less well adapted.
Imagine an organism A that has some reproductive rate, and then a beneficial mutation occurs that increases it’s expected number of offspring by one. Now if this organism normally is expected to produce 100 offspring, and it has one more, it has improved it’s number of offspring by 1%.
Now imagine another organism B that has twice the reproductive rate that A had, and then this organism suffers the same mutation A did. It produces 200 offspring normally, and now can add one more. But now the mutation only has a 0.5% effect of improvement.
But that would imply the selection coefficient for this mutations has decreased. As the organism has gotten more fit, the effects of individual mutations have gotten smaller in proportion.
An analogy is that you are to push a heavy car that has run out of fuel to the nearest gas station. When you do it alone it’s very hard, but if you get another person to help, it’s half as hard, but then if you get one more, you’re doing a 3rd the work, and then with a fourth, a quarter the work. The gain from every additional person helping push the car becomes smaller and smaller, to the point of being neglible. When you’re 30 people pushing the car, you probably can’t even feel if any single person decides to take a break.
