Do all deer share a common ancestor?

In the discussion “Bills math class” @Rumraket introduced a paper including a tree diagram showing the genetic relationship of several deer species which tried to reconcile the large variation in chromosome counts.

Can we reconcile the common ancestry of deer based on population genetics for chromosome variation and gene family variation?

Is it possible that some deer have separate points of origin?

What counts as a “point of origin”?

Perhaps a chromosome fusion event could be considered a point of origin.

1 Like

According to your idea, wouldn’t it be necessary that every pair of species with different chromosome counts have separate points of origin? But if that were true, why would there be a consistent nested hierarchy uniting muntjacs, cervids, ruminants, artiodactyls, laurasiatherians, placentals, mammals, amniotes, etc.?

So the answers to your questions:

  1. We can reconcile it based on all sorts of things, and I have no reason to suspect that there’s a problem with mutation and fixation as a mechanism. Incidentally, chromosome fusion leaves evidence in the chromosomes. Have you looked? Do you have an explanation for the fact that one species has the same genes on two chromosomes, in the same order, that another species has on one chromosome? And why do these hypothesized fusions follow a nested hierarchy?

Also, isn’t asking this as a question backing down from your previous assertion that known processes could not possibly account for the pattern?

  1. No.
1 Like

We have two papers that show that this can take 10^5 to 10^10 years for large populations with much more favorable conditions then chromosome mutations.

There are similarities and differences in the chromosome pattern.

Why do you think its not possible?

I do not think this tells us much about the origin the current arrangement.

A separate starting point from the other deer. No ancestral relationship. The chromosomes were always in the condition we are observing

No, you don’t. You don’t know what you have, you don’t know the conditions, and the papers you mention are about particular mutations, i.e. a Texas sharpshooter. The probability of a particular mutation happening and being fixed is not the same as that of some mutation or other happening and being fixed.

Yes, and those similarities and differences form a nested hierarchy. Why?

Because the evidence, notably the nested hierarchy, precludes such a thing. Do you think it’s possible that your parents are not really your parents and that you poofed into existence from nothing in some woman’s womb? If not, why not?

Why not? What about the telomere and centromere remnants what are often found in the middle of such chromosomes? Coincidence?

Then how do you account for the synteny between those chromosomes? How do you account for the remnants of separation? How do you account for the nested hierarchy of all the sequence and other genetic data?


The papers are not about particular mutations they are about functional mutations. When we look at new genes we are looking at functional sequences.

There are changes that are more similar than others. Like the Texas sharp shooter the nested hierarchy is a vague and meaningless claim counting on a label vs a real argument.

The nested hierarchy is a way to organize data. It cannot preclude anything. We have very good direct evidence of our relationship with our parents. We don’t have (at this point) good evidence that all deer share a common ancestor.

How do you know they are remnants? How do you know they are not functional?

The synteny and nested hierarchy pattern could be a product of similar designs.

Particular functional mutations.

You say that because you still, after all these years, don’t know what “nested hierarchy” means. No, it’s not about “more similar”. You will note that, for example, your favorite “Howe diagram” fits one particular tree very much better than it fits any other. Why should that be? This is not simple similarity; it’s fit to a model.

You avoid dealing with the question by denying that it exists. The nested hierarchy is an observed feature of the data; that is, the data have a nested hierarchical structure. That’s not something we impose on it, and it demands an explanation. You have none. But what is this direct evidence of relationship that you so blithely toss out? How do you know my explanation for your existence isn’t true?

How do you know you weren’t poofed into existence? If it looks like a degraded centromere, shouldn’t the probable conclusion be that it’s a degraded centromere? Note the consilience of independent lines of evidence here: we infer fusion from the tree and we find evidence of fusion in the genome. And you dismiss both those lines of evidence because…?

Yes, and you could have been poofed into existence. But that isn’t what the evidence tells us. There is no reason to expect synteny or nested hierarchy from “similar designs”. Yet there is reason to expect it from common descent. Which hypothesis is better supported in that case?


Mutations that can form a particular function. Functions that exist in cells.

Is that model informative about the cause of the pattern? Could the data fit into other models?

It looks to you like a degraded centromere. I am not convinced because of the difficulty of explaining the changes through reproduction and natural variation. What you see that looks like a degraded centromere could be a functional sequence.

There is reason to expect this as Winston showed.

Common descent as the sole cause of the pattern could not be ruled out based on the chromosome counts for the deer species with 70 chromosomes.

Common descent or a single point of origin for all deer species becomes more problematic when we see differences that are difficult to attribute to reproduction.

So what? How does that answer the objection?

Yes, no. Now what?

So basically, anything could look like anything else if it were necessary to your scenario. Nothing is evidence, because anything could be anything else.

He showed no such thing. You just like his conclusion, and you don’t care about how he got there.

Once again you confuse the issue between the pattern and the causes of its elements. And you haven’t shown that any differences are in fact difficult to attribute to reproduction. The only reason you think they’re difficult is that you want them to be so as to bolster your creationism. But they don’t even do that, even if you’re right about them, because you ignore guided evolution.

1 Like

I properly states what we are observing. The use of nested hierarchy and Texas sharp shooter as vague assertions is not at all informative.

There is not other model to fit the data into?

You are ignoring the problem of chromosome mutations being deleterious and rare.

You don’t like his conclusion. He showed that the gene patterns can fit into a tree pattern and also a dependency graph as can software modules.

What’s confusing is the attempt to decouple common descent or a single point to origin from the mechanism of reproduction. Like the TSS, and Nested hierarchy this decoupling creates a vague claim.

Paul Nelson made this same point to you in the past:

Bill why does Behe say this in his paper?

Such numbers seem prohibitive. However, we must be cautious in interpreting the calculations. On the one hand, as discussed previously, these values can actually be considered underestimates because they neglect the time it would take a duplicated gene initially to spread in a population. On the other hand, because the simulation looks for the production of a particular MR feature in a particular gene, the values will be overestimates of the time necessary to produce some MR feature in some duplicated gene. In other words, the simulation takes a prospective stance, asking for a certain feature to be produced, but we look at modern proteins retrospectively. Although we see a particular disulfide bond or binding site in a particular protein, there may have been several sites in the protein that could have evolved into disulfide bonds or binding sites, or other proteins may have fulfilled the same role. For example, Matthews’ group engineered several nonnative disulfide bonds into lysozyme that permit function (Matsumura et al. 1989). We see the modern product but not the historical possibilities.

Why is that in the paper?

the simulation looks for the production of a particular MR feature in a particular gene

the simulation looks for

a particular MR feature

in a particular gene

What effect does this have? Well:

the values will be overestimates of the time necessary to produce some MR feature in some duplicated gene.

1 Like

This is what he based his model on. This is balanced against him starting with already duplicated genes in the population. From his paper:

Thus far, the starting point for the model has been a uniform population in which all genes are initially present as exact duplicates of the parent gene

Behe disagrees:

the values will be overestimates of the time necessary to produce some MR feature in some duplicated gene.

1 Like

So you flat out lied to John when you said

Behe says they are.

1 Like

No he does not say they are about particular mutations. There are different substitutions that can do the job according to the model.

As easy as slipping off a wet log.

Not “could be”; there is known function. They are sequences that functioned as centromeres, but since fusion occurred, they no longer serve that function. They are degraded but still recognizable.

1 Like

The reason you think those are vague assertions is that you, apparently, have no idea what they mean or what “observing” means or what you are even claiming. It’s impossible to deal with such incoherence.

None that fits the data as well.

How deleterious? How rare? Before you can say it’s a problem you have to know all that. In fact, many acrocentric fusions have very little effect on fertility. It varies. And all mutations are rare.

Not true. There is no dependency graph, only a set of boxes whose contents are chosen to fit a pattern, not based on any functional relationships. The ones that don’t match a tree are more easily be explained by loss, and in fact we have evidence of gene loss in pseudogenes, which the so-called “dependency graph” does not explain.

“Vague claim” seems like your new mantra that lets you ignore what you don’t like. Now, your objection is vague. What you mean by “the mechanism of reproduction” is unclear. Nor is it clear what you think is confusing. Presumably, you know what common descent means. What if God makes a tweak to the genome of the occasional gamete, or even decrees that this organism shall reproduce and that one shall not? How does that get rid of common descent?

As for Nelson, he’s just wrong. Nested hierarchies were recognized before Darwin but nobody had any sort of sensible explanation for them. Common descent is such an explanation. “It pleased God to make it that way” is not. Nor does nested hierarchy actually amount to “similarity alone”; apparently Nelson doesn’t understand nested hierarchy any better than you do. His case is no better than yours, which is to say nonexistent.

1 Like

Yes he does. That’s what a particular multi-residue (MR) feature is. One that consists of a set of multiple particular residues.

particular residues are particular amino acids and particular amino acids are produced by particular mutations

Residues are amino acids in the protein sequence, and if they’re not already present they would have to be produced by particular mutations. Not just any mutation in the protein sequence, but the particular ones that lead to those particular residues(amino acids) being present.

How have you not understood this? How is it possible you keep referencing a paper you don’t understand what says? THIS IS UNBELIEVABLE.

1 Like

What I see you are spinning the Irish yarn. He has substitutability in his model. Substitutability means different mutations can get the job done.