I’m going to need a reference that isn’t “they said”.
Yeah the problem with that waiting time paper is they consider the human genome a “target”, rather than a result. They’re calculating the average time it would take to evolve some specific set of mutations, rather than how long it would take to accumulate the total number. It’s a classic example of the Texas Sharpshooter fallacy.
Obviously if every new person every generation is born with some X number of mutations (say 50), how long does it take to accumulate 35 million of them?
What use is it then to calculate after 35 million have fixed, how long it would take to evolve that specific set, rather than calculate the waiting time for the total number if every generation X new ones are added?
What’s ironic is their calculation would disprove the common ancestry of the primate clade even if they exclude humans. They will find all the mutations that are different from any two sets of primates impossible to evolve. The waiting time problem they concoct, if taken at face value to be valid, falsifies their own theory of hyper-evolution from Noah’s flood.
Do you see what I mean?
All models are stories, but some stories are true and some models are well supported by evidence.
Go to the bottom of this page for all the references to see if you think there’s one more relevant. I haven’t read them yet. But will try to do so tonight and then watch the video. I’m curious myself.
Tomkins has tried several times to dispute the consensus similarity between humans and chimps, and has failed on all previous attempts I am aware of. My gut instinct is that BLASTN is the wrong tool for aligning contigs to genome assemblies, but it would be good to hear from the real experts (paging @evograd and @glipsnort).
First off, it is inherited by just half the population. All chromosomes are important.
Do you think every person is created separately? Don’t you have parents, siblings, or cousins? You may want to rethink that “there are no common ancestors”.
They addressed this in the video. I don’t remember the specific response.
Possibly. But all primates would have had a common ancestor and so the difference could be described by deletions (is that the right word? lol) So no waiting time is needed. You could just extrapolate back to assume what the original genome may have been like?
So I think you’re making a wrong comparison by misunderstanding a creationism position.
lol. Of course. I think humans evolved from other humans, and descended from other humans. Yep. I have two parents, 4 siblings, and too many cousins to count.
Consider this example:
If primate 1 has somewhere in it’s genome, the gene sequence:
AAAGTTT
and if primate 2 has in a corresponding location in it’s genome, the gene sequence:
AAAGCTT
Then clearly no deletion explains the difference, a substitution does. The substitution of T for C, or the reverse.
That means in one of those primate lineages, either T had to change to C, or C change to T by a substitution mutation, right?
Now you could proceed to compare the two total genome sequences (billions of bases) of those two primates 1 and 2, and find all their differences across their respective genomes(millions of differences out of billions of shared bases). Those have to occur by mutation, right? Many of these will have to be substitutions, where a letter changed. Some will have to be duplications or deletions too.
But Sanford et al thinks there’s a huge “waiting time problem”, and they calculate that it would take much, much too long for even two specific mutations to occur and fix in some lineage.
But then their primates can’t share common descent since they left Noah’s ark(there’s not enough time for all those mutations that separate chimps from gorillas, or chimps from orangutans, or orangutans from rhesus monkeys, or baboons from orangutans etc.)
So now they all have to be on the ark, and the problem extends to all animals in the entire world. Find any two animals from some “kind”, find genetic differences between them(dogs vs wolves, lions vs tigers, etc.) and then calculate the “waiting time problem”, and suddenly you realize if this waiting time problem is real then nothing could have evolved at all because it would just take absurdly huge times for even a small handful of such mutations. Rats and mice can’t be related, differen’t breeds of cats can’t be related (not enough time for their differences to occur and fix).
So something has to give. Either the “waiting time problem” is based on some fundamental misunderstanding(specific sets of mutations rather than just the number of them), or all extant species of animals have to be on the ark. All the millions of them. Or lots of miracles, lots and lots and lots of miracles have to occur. God running around zapping up mutations like a madman I guess. You can always go there and solve any imaginable problem with that, so take your pick.
Can you explain why you selected that particular article? What other publications on this subject have you read, and why do you think this one is better than all those that do not show any such “waiting time problem”?
This article is entirely based on a program called “Mendel’s Accountant” that was devised by the author. Has this program been validated as accurate for the processes it is supposed to model? How has it been validated? What other researchers have used this program?
Of course (and I realize you know this), we don’t need genome assemblies to assess the size of the genome. In fact, I suspect that for the vast majority of plants and animals, measuring the mass of DNA in the cell will give a more accurate estimate of the size than the current iteration of the genome assembly.
It’s dealing in simple logic. Creationists are claiming that certain species hyperevolved from a common ancestor over the last 4,000 years since Noah’s Ark opened up and released them. There are more genetic differences between the species within one kind than there is between humans and chimps. Therefore, if there are too many differences between the chimp and human genomes for evolution then the same would apply to the creationist kinds.
You can simply google that yourself. Find pedigree mutation rates for various animals from whatever you consider to be “kinds”. First result on google for pedigree mouse mutation rate was “gray mouse lemur”(not really the mouse I was looking for, this one is a primate, but that’ll do). It has a rate of mutation of 1.64 × 10−8. The numbers are really not that far off from the human mutation rate(which typically is measured in the range from 2 × 10−8 to 3 × 10−8(Edit: corrected to) 1 × 10−8 to 2 × 10−8. You won’t find a hundred thousand fold increase in the mutation rate compared to humans, in another primate, or mammal, or even another vertebrate.
Sanford and his coauthor’s model basically says that mutation rates would have to increase by absurd levels to reduce the waiting times to within realistic timescales. He even shows a graph which indicates that a 10 000 fold increase in the mutation rate would decrease the waiting time for a mere five specific mutations down from 10 billion to 1 billion years. Now, please realize that you’re not going to find a 10 000 fold increase in the mutation rate compared to humans, in another primate, or dogs, or cats, or mice, or rats, or chickens, or any animal on Earth. So Sanford has basically “proven” (if we accept his argument) that, obviously, two different breeds of cats that differ by five mutations (or even less) couldn’t possibly share common ancestry within 6000 years. They couldn’t share common ancestry any time sooner than some time in the precambrian, over one billion years ago.
So, what is wrong with Sanford’s argument here? He’s focusing on specifics. How long would it take, on average, to produce this specific set of 5 mutations? This is a very different question than “how long would it take to accumulate any combination of 5 mutations?”
I’m still reading through the papers; I didn’t get enough time tonight - so I can’t point to one of them in particular but hopefully I’ll read through them tomorrow.
Also, the video is no longer publicly available, but if you had watched it carefully, they do explain that these are different types of mutations (don’t quote me, I may be remembering incorrectly): beneficial, neutral, and deleterious. Sanford is arguing that beneficials don’t add up over time fast enough. None of that has anything to do with the fact that animals could have evolved/devolved to the variety we see today and shared common ancestors. It’s a completely different type of mutation than what you’re referring to - that’s what I understood from it.
I think it’s very difficult for people that are not creationists to actually understand their arguments. As I understand it, one side is saying animals evolve to create variety and beauty. The other is saying animals devolve but the variety is still beautiful because God is a great designer. Sin really messes things up, but there’s still beauty here.
I understand, I read that too. That’s not what I’m talking about. The fitness effects of the mutations make a neglible difference here. That’s not what’s wrong with Sanford’s arguments.
I repeat, it’s that he is focusing on a particular set of mutations, for example imagine you have this sequence:
AAAAGCCCCTTTT
And it randomly suffers a single substitution once every 100 times it is copied. So you wait 500 copy events and find 5 mutations have occured. Then you say, how long would it take for those 5 particular mutations to occur, on average?
Say these are the mutations(in bold) that changed from the above sequence: TATAGTCCCCTGT
How long would you have to wait, on average, before those specific 5 mutations occur? If we started all over again, an exceptionally long time. Because there’s no guarantee that at any point the mutation that happens to occur is the one you’re waiting for. So you could wait for the first 100 copies(lets just call them generations) to see whether a mutation has occurred, and then check if it’s one of the mutations you wanted.
Since there are many more mutations possible than those 5 I have highlighted, chances are much greater that it is not the one you’re waiting for that occurs, so now you have to wait again for another 100 generations. And then the problem repeats, there’s still many more possible than the one you’re waiting for, so it’s likely another one than the one you want. And so on.
This would be very different from asking how long you would have to wait, on average, for just any 5 mutations to occur. We already know that, we waited 500 generations to get 5 mutations. If you just need to wait for any 5 mutations, you just need to wait, on average, for 500 generations to have occurred. Because on average there’s a new mutation every 100 generations.
But since we already know the first 5 mutations evolved in 500 generations, what use is it then to turn around and calculate how long we would have to wait on average for those 5 specific ones to evolve again if we started over? It doesn’t matter which 5 mutations that evolve in those 500 generations, you would always be able to calculate that it should take an extraordinary amount of time for those 5 specific mutations. And yet, we just need to wait 500 generations for some such set of 5 mutations.
Sanford and colleagues look at the differences between humans and chimps, count how many there are but then treat the waiting time problem as if these specific mutations had to occur, instead of just calculating the waiting time for the total number of them.
I hope this made the problem clear. There’s a name for what is wrong with this kind of argument Sanford is making. It commits the Texas Sharpshooter fallacy.
It’s not. What I am explaining above really is what this is all about. I agree that even if the mutations are all unrealistically beneficial it has a neglible effect on the waiting time, since we still have to wait for specific ones to occur. Making the mutations beneficial just reduces the probability of loss due to drift, and reduces the time to fixation. While those matter too on evolutionary timescales, they’re not the real problem here. It’s the specifics vs general thing.
Whether you think the mutations are “devolutionary”(or whatever you’d call that) doesn’t change the problem at all. You still have to wait for them. Sanford’s argument applies to every species that “devolves” from the pairs that leave the Ark. No creationist shows any sign of having realized this.
I think you are confused about Sanford’s treatment of the waiting time problem for he doesn’t look at the differences between humans and chimps and doesn’t count how many there are. Not at all. Did you read his paper?
It makes no difference when you still have to wait for a particular mutation regardless of what it’s phenotypic or functional effect is.
If you have the sequence AAAAAT, and you’re waiting for that last T to mutate to A, but all other sites can mutate also, then what difference does it make that the last T->A transition might be a “devolutionary” mutation? You still have to wait for it, and it’s still much more likely that some other mutation happens than the one you’re waiting for.
That’s the problem with waiting for specific sets of mutations, instead of just waiting for some X number of mutations.That’s why Sanford’s “waiting time” calculation doesn’t make sense. He’s calculating the waiting time for specific set, instead of the waiting time to accumulate some number of them.
Typical example of the Texas Sharpshooter fallacy.
In this paper we address the question, “How long does it take for the simplest biological text strings to arise and be fixed, within a hominin population?” Given the unique capabilities of humans, an evolving hominin population would need to establish a great deal of new information, leading to new functionalities. Since all information is based upon strings of symbolic characters, this suggests the need to establish a multitude of new nucleotide sub-strings. Chimp and human genomes are minimally 5 % divergent [1], representing about 150 million nucleotide differences. This substantial genomic difference implies many new sub-strings within the human genome. In this paper, we only examine the average waiting time needed to generate and fix a single DNA sub-string of minimal length (2–8 nucleotides). This sort of minimal genomic modification would alter only one (or a few) specific amino acids, or might conceivably result in one new specific protein fold.
I already clarified this. See above.