I don’t think that’s correct, but even if it is it omits the obvious possibility that the first mutation was AT to GC, making the back mutation more likely than the first one.
Fixations aren’t relevant.
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Are you familiar with the notion that intron length can function as a hardwired delay register — a non-coding sequence whose physical length determines a precise time interval, like a countdown timer encoded in the genome itself? Different genes have different intron lengths, producing different delays, which allows a single developmental signal to trigger sequential waves of gene expression — genes responding at different times to the same initial trigger, purely as a function of their intronic length. Where we see that absence of conservation is not absence of function.
Thanks for that paper in which they demonstrate a function for introns of a specific length in a single gene in mice.
Note though, that this can’t explain the large differences in genome (including intron length) size between ostensibly very similar species, and therefore can’t serve as a general explanation for intron presence in essentially all eukaryotic genes.
In the case where intron presence and length really do serve functions, we would then at the very least expect intron length conservation. Yet in many cases we don’t find that.
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Even were this to be significant, you are here arguing it is the structural length, and not the sequence, that has a function. Lack of conservation in that event, then, would indicate that the sequence itself does not define the function.
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Since most mutations that occur are nearly neutral, and the rate of fixation of neutral mutations is equal to the rate of mutation, assuming a mutation rate of 100 per new individual born, then close to 100 new mutations are fixed every generation. In 40.000 generations that amounts to about 4 million fixations.
At that number of mutations having accumulated, the probability that a new mutation will reverse one is roughly somewhere between 1 in 750 and 1 in 2250. With 100 new mutations per individual, that is approximately 1 in 8 to 1 in 23 that an individual has at least 1 reversal in their genome.
In a population of billions, tens of millions of reversals occur every generation.
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… and you cannot google this before responding why?
Okay, but first you have to overcome the unlilihood of an AT to GC mutation in the first place. You’re just switching the order of the problem, not solving it.
Hmm, so the prevalance of the allele in the population isn’t relevant to the likelihood of a mutation hitting that same spot in the genome again? Would you say that the stock of fish in a pond is also irrelevant to the question of how likely you are to catch one?
Thanks. But is that relevant? Can you respond to the point, which is that genome size is not correlated to organismal complexity?
Incidentally, those are some very cheap sparrows.
Yes, but clearly that’s not a common function. Once more, finding some function in a few cases doesn’t tell you that all introns have that function, and in fact intron length is not generally conserved.
I don’t think that’s true at all, and it should be obvious that this supposed timer can be only very short-term.
It’s true that there are a few bulk functions. But in the case of introns, even this bulk function is not generally conserved, as intron length varies enormously.
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You have failed to mention recombination, where the bias is opposite to that of mutation, favoring GC. There are a reasons LME’s all reproduce sexually.
Bias does not alter the principle that handicapped organisms will be out competed.
(Sorry to be slow responding, I have been busy with time-based tasks)
In regard to the Sim simulations, I have two concerns. Let me deal with the first one in this message.
UP/PP used an effective population size of Ne = 10,000 in his simulations. That would be appropriate for 800,000 - 100,000 years ago. In his preferred history, population sizes would change from 2 up to at least 100,000 during the first 1,000 years, say until 3004 BC. Now they are of course much larger. In my 1971 paper I presented calculations for effective size for a population with overlapping generations in a society like ours. The overlap of generations reduced the Ne to 1/3 of the census size. So maybe 2.7 billion.
The result would be that the dynamics of any new mutations, from now on, would be nearly-neutral if the selection coefficients were less than +/- 0.0000000003.
What would happen then.?
I didn’t fail to mention recombination–I didn’t mention it because it doesn’t have anything to do with the topic of back mutations. I guess you guys will inevitably get the last word because you’ll just keep posting even if your post has nothing to do with the discussion, or completely fails to follow the logic of the discussion?
Not a problem, I appreciate your interaction.
I’m sorry to have to keep being a contrarian, but that’s not exactly right. You’re conflating recent Ne with long-term Ne. Kondrashov’s paradox is calculated based on long-term, not recent Ne. Even now, the long-term Ne is still about 10,000. Or as Eyre-Walker and Keightley put it:
Effective population size
The population size of randomly mating individuals
that would behave, in a population genetic sense, as the population being studied.
For example, the genetic diversity in human populations is the same as one would find in 10,000 randomly mating individuals.
Emphasis original. Eyre-Walker et al. 2007. The distribution of fitness effects of new mutations.
Yes, and I would agree that overall the speed of fitness decline we are experiencing right now will be significantly less than the speed we had for most of our history. Increasing the population size increases the strength of selection, up to a point at least. But as I have already previously explained to Hancock, that misses the whole point of GE.
There’s a bit more to it than that. Effective population size is supposed to be a correction factor for accurate simulations and accurate equations that rely on the inaccurate simplifying assumption of random mating. Did you account for geographical isolation when you generated this number? Obviously I’m nowhere near equally likely to reproduce with someone born in India if I am born in Kansas. Even accounting for the possibility of air travel, we still are largely divided into subpopulations.
Lynch has also stated that linkage disequilibrium, or hitchhiking, serves to further reduce the effective population size.
That misses the point. On evolutionary timescales, there is no “now”. We died out hundreds of thousands of years ago from mutation load. You can’t ever make it to this point given evolutionary assumptions about the age of the earth. This means that there’s either something fundamentally wrong with population genetics models (Lynch denies this in the strongest possible terms) — or evolution simply didn’t happen as we’re being told it did, and the earth is not as old as we’re told it is. There are many other independent (and very strong) lines of evidence (e.g. collagen in dinosaur bones, unfossilized dinosaur bones, etc.) that converge on this conclusion.
First you told actual population geneticist Zach Hancock he doesn’t know when it’s appropriate to use long-term vs recent Ne, and now you’re saying the same thing to Joe Felsenstein.
This is not even funny any more, it’s just sad.
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Ah.
Unfossilized dinosaur bones.
Would those be the Alaskan ones describe by Mori as “little evidence of weathering, predation, or trampling, and are typically uncrushed and unpermineralized” by any chance?
The ones which Fiorillo and Mori clarified were actually fossilized?
The ones which some-one named Paul Price was apparently corrected on?
It’s amazing how much information you can discover from a simple Google search.
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Mainly because I was using my phone at the time.
Partly also because it’s not relevant to the point I was making.
But also because it’s so simplistic and incomplete that there’s no way it can capture the complexity of reality.
Finally because I see no need to Google something before replying to a post that shows no sign that the author Googled anything.
Besides, I was being polite. Apparently that’s not necessary.
Now that I have Googled it, I have confirmed that it is not correct. It is far too simplistic.
While C->T and G->A are the commonest mutations, their rate of occurrence is dependent on (at least) the surrounding nucleotides, the location in the genome and the proportions of each in the genome. But the reverse mutations (T->C and A->G) are the second most common. So a second mutation at the same site is far more likely to reverse the first mutation than change to something else. Also, repair mechanisms favour C-G pairs, which tilts the frequencies in the other direction, so that retained mutations are more commonly C or G than A or T (GC-biased gene conversion).
And again, if the original mutation was T->C or A->G, the back mutation is not less likely to happen than the original.
Other mutations are not directional. There doesn’t seem to be an observed difference in the rates of C->G vs G->C, for example. So those back mutations are not less likely to happen.
But I was wrong in one respect. I should not have said “I don’t think that’s correct”. That was too polite. I should have said “That’s simplistic garbage”.
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You don’t understand the relevance? It was you who brought up composition bias.
Bold mine…
Recombination reshuffles the alleles of a population through crossover and gene conversion. These mechanisms have considerable consequences on the evolution and maintenance of genetic diversity. Crossover, for example, can increase genetic diversity by breaking the linkage between selected and nearby neutral variants. Bias in favor of G or C alleles during gene conversion may instead promote the fixation of one allele over the other, thus decreasing diversity. Mutation bias from G or C to A and T opposes GC-biased gene conversion (gBGC). Less recognized is that these two processes may—when balanced—promote genetic diversity.
Quantification of GC-biased gene conversion in the human genome
gBGC is a recombination-associated process favoring G:C (S for strong, hereafter) over A:T (W for weak, hereafter) bases during the repair of mismatches that occur within heteroduplex DNA during meiotic recombination
Biased gene conversion: implications for genome and sex evolution
Molecular experiments suggest that gene conversion could favour GC over AT basepairs, leading to the concept of biased gene conversion towards GC (BGC(GC)). The expected consequence of such a process is the GC-enrichment of DNA sequences under gene conversion.
GC-biased gene conversion drives genomic base composition across a wide range of species
Ample evidence suggests that the contrasting dynamics of base composition are driven by GC-biased gene conversion (gBGC), a process that is associated with meiotic recombination. In line with this hypothesis, base composition is associated with the rate of recombination and the evolutionary dynamics of the recombination landscape, therefore, governs base composition. In addition, and at first sight perhaps surprisingly, the relationship between demography and genomic base composition is in agreement with the gBGC hypothesis: organisms with larger populations have higher GC content than those with smaller populations.
Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome.
1000 human genomes carry widespread signatures of GC biased gene conversion
On average, a human gamete acquires 7 SNP flip-over events, in which one allele is replaced by its complementary allele during the process of meiotic non-crossover recombination. In each meiosis event, on average, gBGC results in replacement of 7 AT base pairs by GC base pairs, while only 6 GC pairs are replaced by AT pairs. Therefore, every human gamete is enriched by one GC pair. Happening over millions of years of evolution, this bias may be a noticeable force in changing the nucleotide composition landscape along chromosomes.
Compensatory Evolution Following Deleterious Episodes of GC-biased Gene Conversion in Rodents
gBGC has a strong influence on the evolution of patterns of genomic variation. In particular, it drives genomic base composition by increasing the frequency of G and C alleles in regions with a high recombination rate … as demonstrated by numerous studies in mammals
There is more to biology than the slope of a tangent on some modeled DFE. You are being led astray in that you have little investment in the complexity of life because your narrow ultimate interest is defense of bronze age cosmology. You are after the pulpit and not the lectern, as you say…
The age of the earth is not an assumption of any sort, but a scientific conclusion, well understood from observed principles.
That you are appealing to population genetics to support YEC is delusional. There are 67 generations from Noah to Jesus, if you prefer Luke over Matthew. At 100 mutations per generation, that works out to under ten thousand. There are millions of differences between DNA of ancient sapien sapiens humans and Neanderthals, and then there are the Denisovans. You have waaaay bigger and more basic genetic challenges to deal with than modeling fitness.
and then…
We have intact carcasses which are tens of thousands of years old, and wouldn’t you know it, they are all mammals. @Joel_Duff has a ton of videos dealing with YEC misrepresentation of soft tissue, but if you would rather not watch them, just consider there are hundreds of dinosaur species, big, small, herbivore, carnivore, that would have disembarked the ark. The line of evidence that is obvious is that if YEC were true, we would see walking, breathing dinosaur collagen in the local zoo, not just residual detectable by mass spec.
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Yes, but I would advise you strongly against getting your information from reddit in general, and especially from Debate Evolution.
I suggest you read my followup article here:
https://creation.com/en/articles/curious-case-unfossilized-bones
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Other people here have replied to much of UP/PP’s argument. The effective population numbers in the past are relevant to how much variability there is in the population. That does affect the strength of selection on new mutants, but the effect is small if the other loci are not closely linked to the new mutant’s locus.
I think other people’s comments here address the issue of whether I have some understanding of theoretical population genetics. Maybe even more than UP/PP’s. Just maybe.
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Yeah, they definitely survived the flood and into the middle ages, but they have clearly died out since then, probably due to a combination of being less fit for the post-flood environment and hunting to extinction by humans.
There should be no amount of collagen whatsoever in bones that are millions of years old. And we definitely should not find unpermineralized dinosaur bones, either.
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Punting to self-directed argument from authority … classy!
This is evidence that you will believe anything, no matter how transparently nonsensical, as long as it fits your preconceptions. The animal on the left is clearly a mammal, probably a cat based on its digitigrade posture. Not sure what’s going on with the tail, but it looks as if a head has been pasted on to it. The one on the right is not all that clearly visible, but its legs and tail are clearly mammalian too. A child might identify them as sauropods, but nobody competent in comparative anatomy would. Of course there are living dinosaurs, around 11,000 species of them, but that’s another story.
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