That diagram doesn’t show a nested hierarchy from design.
You just contradicted yourself.
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Yes. That’s the very thing I am saying is opposite to what you are claiming.
There is no rhyme or reason to the pattern of WNT genes in invertebrates. It does not follow the tree at all.
There’s lots of rhyme and reason, you’re just not allowing yourself to see it. It is certainly noisy, no doubt about that, but there is nesting hierarchical structure even in that small data set.
Look at the phylogeny and see what is most closely related to what, according to the tree shown on the left. Homo sapiens is most closely related to chicken (Gallus gallus) of the species shown on that tree. Is that fact reflected in shared and missing genes between them? Yes, between humans and chicken, we need invoke no losses. WntA is absent in both, so that is probably an inherited ancestral state. Moving on, next most closely related is Xenopus tropicales (some frog species iirc). That’s a vertebrate too. Is that relationship also reflected in the 13 loci used? Yes. Again WntA is absent, so it’s probably an inherited ancestral state. Again no losses need be invoked. And so on and so forth.
In general we need to invoke fewer gene losses for members within a clade, than we do between different clades. And the gene-losses generally follow the nesting hierarchical pattern. The genes lost in some species within a clade, generally are more likely to predict other genes lost by other members of that same clade.
Even though there’s basically only 13 sites used, and they’re only counted by binary presence or absence, there’s still obvious nesting hierarchical structure in that data set.
But I’d like for you to understand and spend some time thinking about how simple and small the data set is.
At least with DNA sequences, you still have 4 possible states for each locus. Here we just have two, either the gene is present or it is not. And we only have 13 such sites used. It would be like trying to generate a phylogeny based in a nucleotide sequence of about 6-8 bases.
Still, we can see the pattern even here, despite how little data we have to work with.
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Here is a paper for the WNT embryonic development pathway and cancer. This pathway would be a good example for the ID guys. The different types of WNT generally are cell or tissue specific. Random gene loss or gain followed by selection is a very poor explanation for the pattern in the paper SCD cited.
https://dx.doi.org/10.1038%2Fonc.2016.304
Man that horse got startled.
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Why? Please show how the pattern fails to be explained by minimal number of gene losses within a tree.
You have several cases where the tree show a common ancestor is shared and the WNT types are very different. WNT type points to a specific cell or tissue. If you look at vertebrates there is very little variation.
Nevertheless, there is still obvious tree structure in that data set. Simple though it is.
WNT type points to a specific cell or tissue.
Wnt types are members of a homologous family that evolved by duplications. They may be expressed differentially across different cell types, but what does that have to do with anything here?
If you look at vertebrates there is very little variation.
Same is true for flatworms, or ringworms, or insects. Generally speaking, members of any particular clade can be explained by fewer gene losses, than differences between clades. Generally speaking, the more closely related, the fewer gene losses we need to invoke. That is exactly what you would expect from a tree. And I have to re-emphazise just how little data there is to work with here on that graphic, with only 13 sites considered in binary form.
I have to wonder whether any of the “absent” members are actually present in pseudogene form in any of the species shown. The article doesn’t specifically state whether the “absent” members are absent because of complete deletion of the entire gene, or just pseudogenization because of nonsense mutations that render it nonfunctional. They make it clear that they consider both options as counting as a “loss”.
Two main molecular mechanisms can lead to the loss of a gene from a given genome. First, the loss of a gene can be the consequence of an abrupt mutational event, such as an unequal crossing over during meiosis or the mobilization of a transposable or viral element that leads to the sudden physical removal of the gene from an organism’s genome. Second, the loss of a gene can be the consequence of a slow process of accumulation of mutations during the pseudogenization that follows an initial loss-of-function mutation. This initial mutation can be caused by nonsense mutations that generate truncated proteins, insertions or deletions that cause a frameshift, missense mutations that affect crucial amino acid positions, changes involving splice sites that lead to aberrant transcripts or mutations in regulatory regions that abolish gene expression. In this Review, the term ‘gene loss’ is used in a broad sense, not only referring to the absence of a gene that is identified when different species are compared, but also to any allelic variant carrying a loss-of-function (that is, non-functionalization) mutation that is found within a population.
Here is the figure again:
See the circles on the tree to the left? Notice how the clades have a similar distribution? That’s the evidence for gene loss.
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He’s over on theskepticalzone now, mindlessly claiming the same nonsense we’ve now explained here multiple times, as if the last few hours didn’t occur.
colewd on November 5, 2019 at 7:25 pm said:
It’s not looking like it explains much of the gene patterns. Here is a paper I came across this am that shows a gene (WNT) I am familiar with. As you can see the gene family does not even differentiate vertebrates from invertebrates and there is very little pattern to the distribution in invertebrates where 2 species that supposedly share a common ancestor have a very different gene set.
http://agri.ckcest.cn/ass/NK002-20160815003.pdf
Round and round and round it goes.
The gene loss is in the clades? Only in one case does this extend down the tree. The details of the cells are contradicting the tree. WNT is part of a complex regulatory system that supports variable cell division. The differences represent not just different genes but different cells and tissues.
The same is true for Sals flower and Winstons dependency graph. We are seeing a design (mind) pattern or the mixing and matching of components at both the gene level and the cell and tissue level.
The author is claiming gene loss as that is the only viable non design explanation. What we are seeing is a pattern that supports the design (mind) hypothesis.
For fork’s sake lol.
You know what Bill, believe what you want!
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But you don’t have a “mind hypothesis”, remember? You can’t even answer the most basic questions about this “hypothesis”, let alone test it.
- I have a mind.
- [something happens here]
- A de novo protein appears.
As you can see, something is missing, namely the mechanism. Please describe part two in detail. Please describe how I can use my mind to bring a de novo protein into being.
How do I do this with my mind? How have you tested this? Just tell me how to do it. Have you ever been able to demonstrate via an experiment, that your mind, or my mind, can generate a de novo protein?
Once you can answer those questions, and you’ve tested your hypothesis, get yourself published. If you won’t do that, then you obviously have absolutely no faith in your “hypothesis”.
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But you don’t have a “mind hypothesis”, remember? You can’t even answer the most basic questions about this “hypothesis”, let alone test it.
If you can show that all theories that are accepted follow this pattern then I will engage but I don’t see even general relativity falling the steps you have outlined.
You make a claim for a mechanism, and I ask you what the mechanism is, and you say my question isn’t part of science?
General relativity has been tested many times. You are claiming that proteins can be created de novo with a mind. I am asking you what the mechanism is, how I do this with my mind, if you’ve ever demonstrated it happening, and if you’ve tested it. This is science. It’s obviously new territory for you.
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I don’t see how that review has anything to do with your hypothesis, Bill.
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If I ask you how gravity curves space time you do not have a tested hypothesis you can cite. We know that minds can generate information as we know gravity can curve space time. The details are interesting but are not necessary for a scientific hypothesis. All for the day will respond tomorrow.
We also know evolution can.
So according to you, we can just say “the details are interesting but are not necessary for a scientific hypothesis”.
Of course, it’s wrong what you’re saying. It’s not sufficient to just say that X can do it, to have good reasons for thinking that X really did do it. We know it could “have happened by chance”, for example. The tornado in a junkyard theory, it’s strictly speaking possible. Unlikely, but possible. Can we now say “the details are interesting but not necessary” and then believe chance did it with staunch conviction? Of course not! We can’t do that for “design” or “mind”, and we can’t do that for “chance”, or whatever else.
We need models that make testable predictions, that can be compared to observations and patterns in the data. Nothing less. Not that silly handwaving you’re offering here.
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This was addressed the last time you raised it; here.
I addressed this the last time you raised it; here. As I said before, you are changing the subject. The subject is not “minds can generate information”, the subject is “minds can create de novo proteins”.
You continue to simply repeat your claims without even acknowledging they have been debunked. Until you can answer my questions, you have no case.
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Hey Bill, have you considered that gene loss is actually perfectly consistent with Michael Behe’s “devolution” argument? Behe is saying the primary mode of adaptive evolution is loss of function mutations. It also seems to fit rather nicely with Sanford’s “genetic entropy” idea that most mutational change is some sort of loss of genetic information and degeneration. Genes that become nonfunctional and are rendered pseudogenes for short-term gains in fitness. Yet here you are saying the opposite, that this can’t be true.
Maybe you should be trying to persuade Sanford and Behe to abandon their ideas since you just can’t wrap your head around how loss of functional genes can be adaptive.
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I would settle for bending a spoon.
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