@Professor Kent: How do you know they are interesting if …

Comment on Southern Adventist University opens Origins Exhibit by Sean Pitman.

@Professor Kent:

How do you know they are interesting if you haven’t read them?

Sean Pitman Also Commented

Southern Adventist University opens Origins Exhibit

If I may summarize our previous posts on allelic variation, SNPs and speciation
You suggest

1] There was frontloading of genetic information in a breeding pair for most species 2349-2348 BC.

The frontloading was at the time of creation by the Creator (less than 10,000 years ago), with a genetic bottleneck at the time of the Noachian Flood some 4,000 or so years ago . . .

2] Variation leading to speciation within kinds was by genetic mechanisms of allelic variation from the original gene pool. Maybe 10-20% of the variation can be attributed to this front loading.

It depends what type of variation you’re talking about. All of the variation beyond very low levels of functional complexity is the result of frontloading . . .

3] Most of the allelic variation and SNPs seen in species today has arisen by random mutation within the populations derived from this starting population of 4 haplotypes. ie 80-90% of the variation within species derived from “kind” ancestor.

At low levels of functional complexity, yes, the vast majority of allelic variations are the result of random mutations.

4] Most (80-90%) of the phenotypic differences seen between species has occurred by natural selection and genetic drift.

Within the same basic “kind” of gene pool – yes.

5] Any differences due to RM/NS after selecting the front-loaded pair can only confer very very low level complexity.

That’s right.

6] There is a barrier of 1000fsaar that limits any ability to generate anything novel and complex within this 80-90% of new mutations.


Apropos of the recent paper:

How do you modify your model of constraint by 1000fsaar to account for the role of SNPs in determining the effects of non-coding regulatory elements? In this context any discussion of hamming distance is really examining the edge effect of minimal relevance. I should not have to explain how this is particularly germane and impacts your discussion about genetics of feathers and the regulation of genes controlling feathered phenotype.

Non-coding regulatory elements are key to the building of complex systems within living things – far more important than are the protein-coding genes themselves (which function more like bricks and mortar that can be used to create many different types of buildings). SNPs can affect these regulatory elements, obviously. However, SNPs cannot affect these regulatory elements in a way that causes them to produce a qualitatively novel type of “building” with the “bricks and mortar” – beyond very low levels of functional complexity of course. In other words, you have to ask yourself the odds that a single point mutation to a regulatory non-coding sequence, or any other type of mutation, will result in a change in the location of the final product to an entirely novel island in sequence space that has a qualitatively unique function that requires a minimum of more than 1000 specifically arranged amino acid parts? That just doesn’t happen. There are no examples of this anywhere in literature – period.

If you would actually sit down and do the math, you’d see why. Sequence space has a fairly uniform distribution of potentially viable sequences/structures. As the minimum size and or specificity of the system under consideration increases in a linear manner, what do you think happens to the ratio of potentially viable/beneficial vs. non-viable/non-beneficial sequences in sequence space? The number of non-viable sequences increases in an exponential manner compared to the potentially viable sequences. The means that the viable sequences become more and more isolated in sequences space, dramatically so, with each step up the ladder of minimum size and/or specificity requirements. This means, of course that the minimum likely gap distance between viable sequences in different island clusters increases in a linear manner with each increase in the minimum size and/or specificity requirements. And, this means, of course, that the average time needed for any kind of random mutations needed to traverse the linearly increasing gap distances increases exponentially.

Now, tell me, how do you solve this sequences/structure space problem at increasing levels of functional complexity? Do you really not see the exponential nature of the problem? There is really no point in further discussion if you will not discuss this particular question. I really don’t understand your continued reluctance to substantive address such problems or consider the statistical basis for your own evolutionary assumptions. Why don’t you sit down and actually do a few calculations? Why not calculate the odds, for yourself, of any kind of mutation or series of mutations in any kind of coding or non-coding region evolving any kind of qualitatively novel system at various levels of functional complexity?

Give it a shot already. What could it hurt?

Sean Pitman

Southern Adventist University opens Origins Exhibit

Since you havent responded to my request to identify in the genomic comparison of mammalian species or primates with the instances of where the 1000fsaar criteria limiting the sequence differences, I suggest an alternative.

But I have responded to this question at least a couple times in this thread. Please go back and review these responses to you and Jeff Kent.

Please provide insights on this recent paper from Kate Sullivans group on Human Accelerated Regions that are proposed to be contributors to the differences between humans and Chimps particularly in limb and brain development. Im interested in the comparison between human SNPs and the varying presence of these SNPs in chimp, Neandertal and Denisova genomic sequences.

Differences between human and ape brain development are based on more than SNPs (which would produce quantitative differences in form and function, but not produce qualitative changes beyond very low levels of functional complexity).

As already noted a few posts above in this thread, humans and apes are quite different in various respects, to include brain structure and function – which is thought to be based on numerous differences in genetic regions that code for miRNAs (around 8% of which are human specific).

“miRNAs recently have been implicated in synaptic development and in memory formation. As the species specific miRNAs described here are expressed in the brain, which is the most complex tissue in the human body, with an estimated 10,000 different cell types, these miRNAs could have a role in establishing or maintaining cellular diversity and could thereby contribute to the differences in human and chimpanzee brain … function.”

Eugene Berezikov, Fritz Thuemmler, Linda W van Laake, Ivanela Kondova, Ronald Bontrop4, Edwin Cuppen & Ronald H A Plasterk, “Diversity of microRNAs in human and chimpanzee brain”, Nature Genetics, Vol 38 | Number 12 | December 2006 pp. 1375-1377.

The Y-chromosome is even more unique. A study published by Nature in early 2010 showed many striking differences between human and chimp chromosome structure, gene content, and even qualitatively unique genes between the two species.

As far as looking at specific genes, the chimp and human Y-chromosomes seem to have a dramatic difference in gene content of up to 53 percent. In other words, the chimp is lacking approximately half of the genes found on a human Y-chromosome. Because genes occur in families or similarity categories, the researchers also sought to determine if there was any difference in actual gene categories. They found a shocking 33 percent difference. The human Y-chromosome contains a third more gene categories, entirely different classes of genes, compared to chimps.

Hughes, J.F. et al. 2010. Chimpanzee and human Y chromosomes are remarkably divergent in structure gene content. Nature. 463 (7280): 536-539.

For further discussion see:


I am sure you see P Troglodyes as entirely unrelated to man but I am a little unclear on your model of origins in terms of relatedness of Neandertal and Denisova hominids to man. Are they the children of Adam, Noah or neither? How do you account for any sharing of SNPs, the HAR and the development of pehnotypic differences by SNPs?

Neandertals and Denisova are human, descendants of Noah. They are simply ethnic variations of humans. Even mainstream scientists think that they could interbreed with each other to produce viable and virile offspring.

Of course there will be SNP differences between modern humans and Neandertals and other ancient ethnic groups – as there are between modern ethnic groups. And, these SNPs may be associated with functional differences – but not beyond low levels of functional complexity (usually only quantitative differences of the same basic type of gene function).

As far as the HAR-1 RNA, there are 18 character differences between humans and chimps (out of 118 characters/nucleotides). These differences are thought to play some role in the development of our brain differences, but no one knows exactly what role. Obviously, there are many structural and functional brain differences at high levels of functional complexity. However, there are also many unique non-coding genetic elements that seem to be involved with these differences (as already explained). No single point mutation or small cluster of mutations is going to be able to cross the gap between any qualitatively novel higher level system of function. Again, there are no examples of this in literature – for very good statistical reasons.

Another paper that cries out for your interpretation including the point at which ignorance about the 1000fsaar limit has blinded this group of scientist.


Critique below the abstract would be most helpful in seeing the errors.

Where in this paper is there any discussion of levels of functional complexity and how mutations can generate qualitatively novel systems at high levels of functional complexity? Remember, we aren’t just talking about quantitative differences in functionality here. We are talking about qualitatively novel differences beyond low levels of functional complexity. We need some actual math here – a few statistical calculations as to the odds that the just-so stories in papers like this might or might not actually be likely to be realized in a given span of time. Please do quote for me the relevant portion of this or any other paper along these lines.

Don’t just give me a bunch of references without any quotes or commentary (aka: reference mining). Show me that you actually understand the problem under discussion by, well, discussing it for a change with the use of quotes that you think are relevant. That would be most helpful…

Sean Pitman

Southern Adventist University opens Origins Exhibit
@Professor Kent:

Again, the question is why does one accept the Bible among so many compete options as the real Word of God? If this choice is based on blind faith without any rational basis or appeal to the weight of empirical evidence, what you have is nothing much more useful than wishful thinking… not the kind of faith that has the power to provide a solid hope in the future for most rational people – especially in the face of very difficult trials or even the threat of torture and death.

What you’re asking people to do is to accept the Bible without really considering the weight of empirical evidence or any additional evidence that may contribute to the current weight of evidence for or against the Bible’s credibility. That’s simply not a rational expectation. Certain God does not expect anyone to believe without a rational basis for belief or faith set upon the weight of evidence that would appeal to the candid mind.

In this line, we are talking about what paid representatives of the SDA Church are teaching and/or preaching in the name of the Church. The Adventist Church, as an organization, simply cannot afford to pay people to go around teaching our young people that the best we have to support the Adventist position on origins is faith that is effectively blind to the otherwise overwhelming scientific basis for neo-Darwinism. That simply isn’t helpful to Adventism. Those who believe in neo-Darwinism, however honest and sincere they may be (and there are many in this category) cannot effectively represent the Adventist perspective on several fundamental doctrinal positions within our schools…

Sean Pitman

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