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Double debunking: Glenn Williamson on human-chimp DNA similarity and genes unique to human beings

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Computer programmer Glenn Williamson now claims that ICR geneticist Jeff Tomkins made an elementary error when using the nucmer program to show that human and chimp DNA are only 88% similar. Williamson also asserts that 60 de novo protein coding genes said to be unique to human beings have very similar counterparts in apes, contrary to claims made last year by Dr. Cornelius Hunter, who is an adjunct professor of biophysics at Biola University.

What Dr. Tomkins allegedly got wrong

As readers of my recent post, Human and chimp DNA: They really are about 98% similar, will recall, Glenn Williamson demolished Dr. Tomkins’s original claim, made back in 2013, that human and chimp DNA are only about 70% similar. Williamson’s detailed takedown of Dr. Tomkins’s 70% similarity figure can be accessed here. In short: the version of the BLAST computer algorithm used by Tomkins contained a bug which invalidated his results. Dr. Tomkins responded by performing a new study which came up with a similarity figure of 88% – still far below the 98% similarity figure commonly claimed in textbooks for human and chimp DNA. Tomkins arrived at that figure by using a version of the BLAST algorithm which did not contain the bug, and in my last post, I pointed out the errors identified by Glenn Williamson in Dr. Tomkins’ new paper, relating to BLAST.

But to give credit where credit is due, Dr. Tomkins didn’t rely on just one computer program to come up with his 88% figure; he relied on three. In addition to BLAST, Dr. Tomkins made use of two other programs: nucmer and LASTZ. Creation scientist Jay Wile described these programs in a recent post discussing Dr. Tomkins’ work:

The nucmer program’s results agreed with the unbugged BLAST results: on average the human and chimpanzee genomes are 88% similar. The LASTZ program produced a lower average similarity (73%), which indicates that perhaps LASTZ has a bug or is not optimized for such comparisons, since its results are very close to the results Dr. Tomkins got with the bugged version of BLAST.

In today’s post, I’ll discuss the flaws identified by Glenn Williamson in Dr. Tomkins’s comparisons that were made using the nucmer program.

Basic methodological errors?

As we saw in yesterday’s post on Uncommon Descent, Glenn Williamson claims that Dr. Tomkins’s new study makes some fundamental errors in the way it performs the BLASTN analysis. Now, however, Williamson has gone further, and identified some very basic errors in the way Dr. Tomkins obtained his results from the nucmer program. What Williamson has shown is that even when human chromosome 20 is compared with itself, the calculation method used by Dr. Tomkins when running the “nucmer” program would imply (absurdly) that it is less than 90% similar to itself!

I have been in email correspondence with Glenn Williamson over the past 24 hours, and he kindly allowed me to publish his responses, as well as some emails he sent to Dr. Tomkins. Here’s an excerpt from his first email to me.

Hi Vincent,

I’ve only just seen your post on UD, and I thought I’d fill you in on where we are at with one of the other comparisons (“nucmer”) Jeff did in his recent paper. Basically what he is doing in this comparison is taking every single alignment for each query sequence (as opposed to taking just the best alignment) and taking the average of all those. Obviously all the repeat motifs will find many matches across each chromosome, but only one of those will be (putatively) homologous. If you can follow the email thread from the bottom, hopefully you can understand the issue.

I’m currently running a nucmer job with human chromosome 20 being compared to itself, just to show the absurdity of his calculation method. I should have the results by tomorrow.

I subsequently emailed him, and asked if he could tell me about the results:

I would greatly appreciate it if you would let me know about your results, after you finish running your nucmer job. I was also wondering if you would allow me to quote excepts from your correspondence in a forthcoming post on UD.

Glenn Williamson replied:

Hey,

Yup, no problems quoting any of the emails…

The first nucmer job I ran took 37 hours (human 20 to chimp 20), and this current “control” job (human 20 to human 20) has taken 37 hours as of right now, so it should finish soon. It will take a couple of hours to put all the results together, so should have something by tonight.

It wasn’t long before I heard from Glenn Williamson again:

It’s done!

And human chromosome 20 is only 88.86% identical to human chromosome 20! 🙂

Unix commands, if you care:

awk ‘NR>5 { print $7″\t”$8″\t”$10 }’ control.coords > control.tab
awk ‘{ sum += ($1 + $2) / 2; prod += ($1 + $2) / 2 * $3 } END { print prod; print sum; print prod / sum }’ control.tab

Output:

1.71549e+09
1.52439e+11
88.8601

So basically the alignments covered 1.715Gb for a chromosome that is only 64Mb long (27x coverage). There were 4.8 million individual alignments …

So there we have it. If Dr. Tomkins is right, then not only is chimpanzee DNA only 88% similar to our own, but human DNA is only 89% similar to itself!

Do human beings really have 60 de novo protein-coding genes with no counterparts in apes?

But there was more – much more. In my original email to Glenn Williamson, I had expressed curiosity over a comment he made on a January 2014 post titled, Chinese Researchers Demolish Evolutionary Pseudo-Science, over at Dr. Cornelius Hunter’s Website, Darwin’s God, in which Williamson expressed skepticism over Dr. Hunter’s claim that no less than 60 protein-coding orphan genes had been identified in human DNA which had no counterpart in chimpanzees. To support his claim, Dr. Hunter cited a 2011 PLOS study by Dong-Dong Wu, David M. Irwin and Ya-Ping Zhang, titled De Novo Origin of Human Protein-Coding Genes. Here is the authors’ summary of their paper (emphases mine – VJT):

The origin of genes can involve mechanisms such as gene duplication, exon shuffling, retroposition, mobile elements, lateral gene transfer, gene fusion/fission, and de novo origination. However, de novo origin, which means genes originate from a non-coding DNA region, is considered to be a very rare occurrence. Here we identify 60 new protein-coding genes that originated de novo on the human lineage since divergence from the chimpanzee, supported by both transcriptional and proteomic evidence. It is inconsistent with the traditional view that the de novo origin of new genes is rare. RNA–seq data indicate that these de novo originated genes have their highest expression in the cerebral cortex and testes, suggesting these genes may contribute to phenotypic traits that are unique to humans, such as development of cognitive ability. Therefore, the importance of de novo origination needs greater appreciation.

Commenting on the paper, Dr. Hunter remarked (bold emphases mine – VJT):

A 2011 paper out of China and Canada, for example, found 60 protein-coding genes in humans that are not in the chimp. And that was an extremely conservative estimate. They actually found evidence for far more such genes, but used conservative filters to arrive at 60 unique genes. Not surprisingly, the research also found evidence of function, for these genes, that may be unique to humans.

If the proteins encoded by these genes are anything like most proteins, then this finding would be another major problem for evolutionary theory. Aside from rebuking the evolutionist’s view that the human-chimp genome differences must be minor, 6 million years simply would not be enough time to evolve these genes.

In fact, 6 billion years would not be enough time. The evolution of a single new protein, even by evolutionists’ incredibly optimistic assumptions, is astronomically unlikely, even given the entire age of the universe to work on the problem.

Note the claim that Dr. Hunter is making here: “60 protein-coding genes in humans that are not in the chimp.” But as we’ll see, these genes do have virtually identical counterparts in chimps, even if they are noncoding.

So, how many ORFan genes do humans really have?

In his comment, Glenn Williamson responded to Dr. Hunter’s claim that humans have 60 protein-coding genes that are “not in the chimp” by pointing out that the first of these 60-odd genes actually has a counterpart in chimpanzee DNA which is 98% identical to the human gene (emphasis mine – VJT):

“So how many ORFan genes are actually in humans???”

Depends what you call an ORFan gene. I looked at the paper that Cornelius cites as having 60 de novo protein coding genes.

Now, granted that I only looked at the very first one (“ZNF843”), it was quite easy to find the corresponding DNA on the chimpanzee chromosome, with approximately 98.5% identity.

So whether it is protein-coding in humans and non-coding in everything else doesn’t really concern me. What concerns me is whether it has an evolutionary history: clearly this one does.

Like I said, I’ve only done one. I’d happily take bets on the majority of these de novo genes having an evolutionary history (chimpanzee > 95% and/or gorilla > 90%).

Any takers?

I had only come across this exchange in the last couple of days, while surfing the Net, and my curiosity was piqued. So I wrote back to Williamson:

By the way, I was intrigued with your work on orphan genes, and I thought I’d have a look at the 60 genes mentioned by Cornelius Hunter in a post he wrote last year. However, I don’t have any experience in this area. Can you tell me how to go about running these comparisons?

Orphan genes – did Dr. Hunter get his facts wrong?

Glenn Williamson’s reply was very helpful – and it pulled no punches. He accused Dr. Hunter of getting his facts wrong about ORFan genes (emphasis mine – VJT):

As for Orphan genes, I assume you mean this comment? http://darwins-god.blogspot.com.au/2014/01/chinese-researchers-demolish.html?showComment=1421299517820#c1105680265537141676

There are a couple of points to be made here. First is that Cornelius fundamentally misunderstands what an orphan gene is and what an ORF(an) is – they are not equivalent terms. A true orphan gene should be called a “taxonomically restricted gene” (TRG), and no trace of its evolutionary history can be found outside a particular taxonomic group. These would be examples of de novo evolution. With respect to humans and chimpanzees, I don’t know of any TRGs that exist in either genome (with respect to the other), and if there were, I would then check the other great apes to see if it was likely that this gene was deleted in one of the genomes (rather than evolved out of nothing in 6mn years!).

Good point. Williamson continued:

An ORFan gene usually refers to a putative protein coding gene. “Putative” because these are generally the result of a computer program trying to find long open reading frames, and if it finds something over a certain length (300bp? 400bp?) then, since a long open reading frame is quite unlikely, the program thinks that this open reading frame is evolutionarily conserved, and it might be conserved because it codes for an important protein. Have a read of Eric Lander’s paper – http://www.ncbi.nlm.nih.gov/pubmed/18040051 – where he says we should be removing these ORFs from the gene database unless and until we can actually find their corresponding proteins.

Glad we got that point cleared up. So, what about those 60 protein-coding genes in humans which Dr. Hunter claimed are not found in the chimp? Here’s what Williamson wrote back to me:

So, these 60-odd genes that Cornelius brings up, he is claiming that they must have evolved de novo:

“In fact, 6 billion years would not be enough time. The evolution of a single new protein, even by evolutionists’ incredibly optimistic assumptions, is astronomically unlikely, even given the entire age of the universe to work on the problem.”

And that’s why I checked the first one on the list, just to demonstrate that it was in the chimpanzee genome (at 98.5% identity). So if this gene codes for a protein in humans, maybe we just haven’t found the protein in chimps. Maybe it codes for a protein in humans, and there was a single mutation that caused it not to be translated in chimps. Maybe it doesn’t actually code for a protein in humans at all? (Although I think we can check that). In any case, it’s not an example of de novo evolution – it’s not an orphan gene in the sense of being taxonomically restricted.

As to how to do the work yourself .. let me send this one off first and I’ll start another email 🙂

For my part, I am somewhat skeptical about Williamson’s speculation that these genes got switched off in the lin leading to chimpanzees – especially in view of the discovery of three undoubted cases of de novo genes in human beings where the ancestral sequence in apes was noncoding. But given the striking 98% similarities between these genes and their non-coding counterparts in apes, I would also urge caution about Dr. Hunter’s claim that even billions of years would not have been long enough for these protein-coding genes to have evolved. If they were evolving from scratch, yes; but if they were evolving from 98% identical counterparts, I wouldn’t be so sure about that.

I learn how to do a BLAST comparison

In his next email, Glenn Williamson kindly informed me how to do a BLAST comparison, and how he obtained his results for ZNF843, which was the first of the 60 de novo protein coding genes cited by Dr. Hunter in his 2014 post. In his response to Dr. Hunter, Williamson had reported that “it was quite easy to find the corresponding DNA on the chimpanzee chromosome, with approximately 98.5% identity.” Here’s what he wrote to me:

Alright, I’ll run you through a simple BLAST search on the Ensembl website. Although, if you want to do some serious BLASTing, then you probably should install the software on your own machine, and download the genomes onto your hard drive.

Anyway, go to:

http://www.ensembl.org/index.html

and stick the name of the gene: ZNF843 into the search box. That should get you to here:

http://asia.ensembl.org/Homo_sapiens/Gene/Summary?db=core;g=ENSG00000176723;r=16:31432593-31443160

On the left hand side, there should be an “Export Data” tab. Click it. Deselect all the checkboxes (we just want the raw DNA) and hit “Next”. Hit the “Text” button, and then just Copy the whole output, starting with the “>blah blah blah”. Now, at the top left of the page is the “BLAST/BLAT” tool. Click it.

Paste the copied DNA into the box, make sure you search against the chimpanzee genome (i.e. uncheck the human genome) and then run the search – using the default parameters should be fine for now.

The results can be found here:

http://www.ensembl.org/Homo_sapiens/Tools/Blast/Ticket?tl=mQCTv8YnFRQKB0Kx

Unfortunately the results are given in chunks, and if you want to get an exact number, stick them in Excel and work it out. But if you just want to look at it on the website, click on the “Genomic Location” header to sort them in that order, scroll down to chromosome 16, and you’ll see that it covers the vast majority of the 10.5kb of query DNA, and the matches are around 98.5%-99.5%. Rough guess for the overall identity (including some small indels) is about 98.5%.

If you need help just email me back and I’ll see what I can do. I gotta run now tho 🙂

And here’s what Williamson got when he ran the BLAST comparison on his computer:

I ran it on my local machine:

#!/bin/sh

QRY=”ZNF843.fa”
SBJ=”${HOME}/Data/Ensembl/chimp/Pan_troglodytes.CHIMP2.1.4.dna.chromosome.16.fa”

blastn -query ${QRY} -subject ${SBJ} -max_hsps 1 -outfmt ’10 qseqid qstart qend sstart send nident pident qlen length’

Output:

16,1,10568,31611859,31601307,10375,97.62,10568,10628

So, only 97.62% identity for that one … 0.57% of the alignment is indels. Boooooooooooooo.

So, for the first of the alleged 60 “de novo” protein coding genes cited by Dr. Hunter (“ZNF843″), Glenn Williamson managed to locate some corresponding DNA on the chimpanzee chromosome, which was approximately 98% identical. Are these genes without an evolutionary history? I hardly think so!

More good news – the results for all the other genes are already in!

In his most recent email, Glenn Williamson shared further good tidings: comparisons for the other 59 genes have already been done!

Just looking into that 2011 paper a little further – they’ve already done all the work for us!

http://journals.plos.org/plosgenetics/article/asset?unique&id=info:doi/10.1371/journal.pgen.1002379.s009
http://journals.plos.org/plosgenetics/article/asset?unique&id=info:doi/10.1371/journal.pgen.1002379.s011

These are the 60 “de novo” genes, and their alignments with chimpanzee and orang-utan 🙂

I’ve had a look at the output, and even to my untutored eye, it’s obvious that any claims that these “de novo” genes are not found in the DNA of chimps and other apes are flat-out wrong. They have virtually identical counterparts on the chimpanzee and orang-utan genomes, even if these are non-protein coding.

Some cautionary remarks about the 2011 paper cited by Dr. Hunter

The 2011 paper by Wu et al. which was cited by Dr. Hunter was critiqued in another article in PLOS Genetics (7(11): e1002381. doi:10.1371/journal.pgen.1002381, published 10 November 2011), titled,
De Novo Origins of Human Genes by Daniele Guerzoni and Aoife McLysaght. The authors felt that the estimate of 60 de novo human-specific genes in the paper by Wu et al. was based on rather lax criteria. What’s more, they seemed confident that the genes could have evolved:

In this issue of PLoS Genetics, Wu et al. [15] report 60 putative de novo human-specific genes. This is a lot higher than a previous, admittedly conservative, estimate of 18 such genes [13], [16]. The genes identified share broad characteristics with other reported de novo genes [13]: they are short, and all but one consist of a single exon. In other words, the genes are simple, and their evolution de novo seems plausible. The potential evolution of complex features such as intron splicing and protein domains within de novo genes remains somewhat puzzling. However, features such as proto-splice sites may pre-date novel genes [9], [17], and the appearance of protein domains by convergent evolution may be more likely than previously thought [2].

The operational definition of a de novo gene used by Wu et al. [15] means that there may be an ORF (and thus potentially a protein-coding gene) in the chimpanzee genome that is up to 80% of the length of the human gene (for about a third of the genes the chimpanzee ORF is at least 50% of the length of the human gene). This is a more lenient criterion than employed by other studies, and this may partly explain the comparatively high number of de novo genes identified. Some of these cases may be human-specific extensions of pre-existing genes, rather than entirely de novo genes — an interesting, but distinct, phenomenon.

In a 2009 paper titled Recent de novo origin of human protein-coding genes (Genome Research 2009, 19: 1752-1759), David Knowles and Aoife McLysaght presented evidence for the de novo origin of at least three human protein-coding genes since the divergence with chimp, and estimated that there may be 18 such genes in the human genome, altogether. Here’s what they said about the three genes they identified:

Each of these genes has no protein-coding homologs in any other genome, but is supported by evidence from expression and, importantly, proteomics data. The absence of these genes in chimp and macaque cannot be explained by sequencing gaps or annotation error. High-quality sequence data indicate that these loci are noncoding DNA in other primates. Furthermore, chimp, gorilla, gibbon, and macaque share the same disabling sequence difference, supporting the inference that the ancestral sequence was noncoding over the alternative possibility of parallel gene inactivation in multiple primate lineages.

Note the wording: “Each of these genes has no protein-coding homologs in any other genome.” Nevertheless, the genes have non-coding counterparts in the DNA of apes: “High-quality sequence data indicate that these loci are noncoding DNA in other primates.”

Whether these genes could have evolved naturally from their ape counterparts is a question I’ll leave for the experts to sort out. One thing I do know, however: they are not “new” in the sense that layfolk would construe that term – that is, functioning genes which have no counterparts in the DNA of apes. Clearly, they do have very similar counterparts in apes, even if those counterparts are non-coding.

Conclusion

Well, I think that’s about enough new revelations for one day, so I shall stop there. It seems to me that any claims that humans have a large number of “de novo” genes with no counterparts in the DNA of chimpanzees and other apes should be treated with extreme caution. In fact, I wouldn’t bet on our having any de novo protein-coding genes having no counterparts in apes, after that takedown.

We already have very good arguments demonstrating the impossibility of proteins having evolved via an undirected process, thanks to the excellent work of Dr. Douglas Axe – see, for instance, his excellent article, The Case Against a Darwinian Origin of Protein Folds. It seems to me that arguments based on de novo genes alleged to exist in human beings, with no counterparts in apes, have much weaker evidential support, and that Intelligent Design proponents would be better off not using them.

But perhaps those who are feeling adventurous might like to take up Glenn Williamson on his 2014 wager:

I’d happily take bets on the majority of these de novo genes having an evolutionary history (chimpanzee > 95% and/or gorilla > 90%).

Any takers?

Well? Is anyone feeling lucky?

POSTSCRIPT: Readers may be interested to know that Dr. Ann Gauger has written a very balanced post titled, Orphan Genes—A Guide for the Perplexed. In her post, Dr. Gauger defines orphan genes as ” those open reading frames that lack identifiable sequence similarity to other protein-coding genes.” Note the word “protein-coding.” She raises the possibility that “they are uniquely designed for species- and clade-specific functions” but draws no firm conclusions.

Comments
@Mung, #624:
So why the objection to my original comment that led to all this?
I objected because you used the word "pretending" as if it were not legitimate to reduce the search space in the way I have suggested. I agree with Nick's use of the word "bogus" when you calculate the probability of forming a functional protein using the 10 ^ 130 figure.
Do you have anything set up to accept donations for expenses for your family?
Nope, I live in Australia! Total cost is zero. Socialised medicine for the win :DThickPython
November 7, 2015
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ThickPython, we seem to have reached agreement on a number of points. The theoretical search space is the amino acid sequence space. The amino acid sequence space "size" is dependent on the number of amino acids and the length of the sequence. There are two ways to reduce the size of the search space: 1. Reducing the length of the sequence 2. Reducing the number of amino acids The paper (assuming I understand what you've said) chose #2, reducing the number of amino acids. So why the objection to my original comment that led to all this? Mung:
Sure. By pretending that there aren’t really 20 amino acids.
Now compare that to Nick's comment:
That article shows just how bogus it is to take the (length of sequence)^20 [later corrected to 20^(length of sequence)] as a measure of sequence space.
see also Do you have anything set up to accept donations for expenses for your family? If so please feel free to post it here.Mung
November 7, 2015
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@Mung, #621:
How do you reduce the size of the amino acid sequence space without doing one of the following? 1. Reducing the length of the sequence. 2. Reducing the number of amino acids. What is the variable that I am not taking account that allows the size of the sequence space to be reduced?
We are speaking in the context where there is a "one in a gazillion" chance of a functional protein forming from a random string of amino acids. It is trivially true that there are 20 ^ 100 unique sequences (1.27 x 10 ^ 130). That is the theoretical search space, and we agree on that. What Nick and I are saying is that there have been empirical studies that show just how much of particular sequences are "hyper-variable". The study I gave showed that much of the Cytochrome C is hyper-variable. So, instead of each individual amino acid taking the specific value that it does, we say that each amino acid could be replaced with (for example, and on average) two other amino acids without affecting function. So, it's no longer 20 ^ 100, it might be closer to 7 ^ 100. That would knock off 46 zeros from the search space. I don't know if 7 ^ 100 is a good approximation or not. Some of the amino acid positions in the sequence can be replaced by half a dozen different amino acids without affecting function, while some positions are restricted to only one or two values. Only a miniscule fraction of the search space was tested. If there are on average four amino acids that can appear in a certain position without affecting function, then your search space falls to 5 ^ 100 (10 ^ 69).ThickPython
November 7, 2015
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@BornAgain, @Andre: Thanks guys, I'm sure I'll pop back in here when I need a distraction! :DThickPython
November 7, 2015
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ThickPython:
Do you understand that because much of the amino acid sequence is replaceable, that this sequence space is reduced enormously?
I know that's what you and Nick M think. I know that's the claim from your side of the aisle that is on the table. Frankly, I think it's mathematically impossible. I think the probability is "exactly zero." Given your circumstances, I can understand how you may have missed the relevant post. Take the definition of a sequence space. According to your example the relevant numbers would be 20 (the number of amino acids) and 100 (presumably the length of the sequence of amino acids). How do you reduce the size of the amino acid sequence space without doing one of the following? 1. Reducing the length of the sequence. 2. Reducing the number of amino acids. What is the variable that I am not taking account that allows the size of the sequence space to be reduced?Mung
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Thickpython Will have you and your family in my thoughts in the hope that your son will make a full recovery.Andre
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I hope and pray your son gets better Python.bornagain
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Thirdly, and most importantly, the alternative splicing code is 'species-specific'
Canadian Team Develops Alternative Splicing Code from Mouse Tissue Data Excerpt: “Our method takes as an input a collection of exons and surrounding intron sequences and data profiling how those exons are spliced in different tissues,” Frey and his co-authors wrote. “The method assembles a code that can predict how a transcript will be spliced in different tissues.” http://www.genomeweb.com/informatics/canadian-team-develops-alternative-splicing-code-mouse-tissue-data
And yet these supposed 'junk intron sequences', that Darwinists use to ignore, that were used to decipher the splicing code of different tissue types in an organism, are found to be exceptionally different between even chimpanzees and Humans:
Modern origin of numerous alternatively spliced human introns from tandem arrays – 2006 Excerpt: A comparison with orthologous regions in mouse and chimpanzee suggests a young age for the human introns with the most-similar boundaries. Finally, we show that these human introns are alternatively spliced with exceptionally high frequency. http://www.pnas.org/content/104/3/882.full Characterization and potential functional significance of human-chimpanzee large INDEL variation - October 2011 Excerpt:,,, we categorized human-chimpanzee INDEL (Insertion, Deletion) variation mapping in or around genes and determined whether this variation is significantly correlated with previously determined differences in gene expression. Results: Extensive, large INDEL (Insertion, Deletion) variation exists between the human and chimpanzee genomes. This variation is primarily attributable to retrotransposon insertions within the human lineage. There is a significant correlation between differences in gene expression and large human-chimpanzee INDEL variation mapping in genes or in proximity to them. http://www.mobilednajournal.com/content/pdf/1759-8753-2-13.pdf
Jonathan Wells comments on the fallacious 'Darwinian Logic', within the preceding paper, that falsely tried to attribute the major differences that were found in INDEL variation to unguided Darwinian processes:
Darwinian Logic: The Latest on Chimp and Human DNA – Jonathan Wells - October 2011 Excerpt: Protein-coding regions of DNA in chimps and humans are remarkably similar -- 98%, by many estimates -- and this similarity has been used as evidence that the two species are descended from a common ancestor. Yet chimps and humans are very different anatomically and behaviorally, and even thirty years ago some biologists were speculating that those differences might be due to non-protein-coding regions, which make up about 98% of chimp and human DNA. (In other words, the 98% similarity refers to only 2% of the genome.) Now a research team headed by John F. McDonald at Georgia Tech has published evidence that large segments of non-protein-coding DNA differ significantly between chimps and humans,,,, If the striking similarities in protein-coding DNA point to the common ancestry of chimps and humans, why don’t dissimilarities in the much more abundant non-protein-coding DNA point to their separate origins? http://www.evolutionnews.org/2011/10/the_latest_on_chimp_and_human052291.html
This following, more recent, paper also found that Alternative Splicing patterns to be 'species-specific' between chimps and humans:
Evolution by Splicing - Comparing gene transcripts from different species reveals surprising splicing diversity. - Ruth Williams - December 20, 2012 Excerpt: A major question in vertebrate evolutionary biology is “how do physical and behavioral differences arise if we have a very similar set of genes to that of the mouse, chicken, or frog?”,,, A commonly discussed mechanism was variable levels of gene expression, but both Blencowe and Chris Burge,,, found that gene expression is relatively conserved among species. On the other hand, the papers show that most alternative splicing events differ widely between even closely related species. “The alternative splicing patterns are very different even between humans and chimpanzees,” said Blencowe.,,, http://www.the-scientist.com/?articles.view%2FarticleNo%2F33782%2Ftitle%2FEvolution-by-Splicing%2F Gene Regulation Differences Between Humans, Chimpanzees Very Complex – Oct. 17, 2013 Excerpt: Although humans and chimpanzees share,, similar genomes, previous studies have shown that the species evolved major differences in mRNA (messenger RNA) expression levels.,,, http://www.sciencedaily.com/releases/2013/10/131017144632.htm ,,,Alternative splicing,,, may contribute to species differences - December 21, 2012 Excerpt: After analyzing vast amounts of genetic data, the researchers found that the same genes are expressed in the same tissue types, such as liver or heart, across mammalian species. However, alternative splicing patterns—which determine the segments of those genes included or excluded—vary from species to species.,,, The results from the alternative splicing pattern comparison were very different. Instead of clustering by tissue, the patterns clustered mostly by species. "Different tissues from the cow look more like the other cow tissues, in terms of splicing, than they do like the corresponding tissue in mouse or rat or rhesus," Burge says. Because splicing patterns are more specific to each species, it appears that splicing may contribute preferentially to differences between those species, Burge says,,, Excerpt of Abstract: To assess tissue-specific transcriptome variation across mammals, we sequenced complementary DNA from nine tissues from four mammals and one bird in biological triplicate, at unprecedented depth. We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific. Thousands of previously unknown, lineage-specific, and conserved alternative exons were identified; http://phys.org/news/2012-12-evolution-alternative-splicing-rna-rewires.html
Of related interest: The position and organization of genes on the chromosome is not arbitrary but is irreducibly complex in its organizational complexity
Refereed scientific article on DNA argues for irreducible complexity - October 2, 2013 Excerpt: This paper published online this summer is a true mind-blower showing the irreducible organizational complexity (author’s description) of DNA analog and digital information, that genes are not arbitrarily positioned on the chromosome etc.,, ,,,First, the digital information of individual genes (semantics) is dependent on the the intergenic regions (as we know) which is like analog information (syntax). Both types of information are co-dependent and self-referential but you can’t get syntax from semantics. As the authors state, “thus the holistic approach assumes self-referentiality (completeness of the contained information and full consistency of the different codes) as an irreducible organizational complexity of the genetic regulation system of any cell”. In short, the linear DNA sequence contains both types of information. Second, the paper links local DNA structure, to domains, to the overall chromosome configuration as a dynamic system keying off the metabolic signals of the cell. This implies that the position and organization of genes on the chromosome is not arbitrary,,, http://www.christianscientific.org/refereed-scientific-article-on-dna-argues-for-irreducibly-complexity/
Since unique codes must be implemented top down, the finding of a 'species-specific' alternative splicing code for humans is certainly not a minor problem to your Darwinian beliefs in gradualismbornagain
November 7, 2015
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Python, I know you are fairly well enamored with this questionable 98% figure that you came up with by crunching numbers on your computer, but I would like to (re)point you to one problem in particular, out of many, that refutes your belief in gradualism. First off, codes must be implemented top down. It is physically impossible to evolve a code from the bottom up. All of our empirical evidence confirms this fact. In fact, so solid is this scientific fact that Perry Marshall has organized a 3 million dollar prize for the first person who can prove to the contrary that codes can possibly evolve in a bottom up Darwinian fashion without a mind. In other words, it ain't going to happen. A technical way of understanding this fact is 'Shannon channel capacity'
“Because of Shannon channel capacity that previous (first) codon alphabet had to be at least as complex as the current codon alphabet (DNA code), otherwise transferring the information from the simpler alphabet into the current alphabet would have been mathematically impossible” Donald E. Johnson – Bioinformatics: The Information in Life
But an easier way of understanding why a code will never evolve in a gradual bottom up Darwinian fashion is elucidated by Dawkins himself:
Venter vs. Dawkins on the Tree of Life - and Another Dawkins Whopper - March 2011 Excerpt:,,, But first, let's look at the reason Dawkins gives for why the code must be universal: "The reason is interesting. Any mutation in the genetic code itself (as opposed to mutations in the genes that it encodes) would have an instantly catastrophic effect, not just in one place but throughout the whole organism. If any word in the 64-word dictionary changed its meaning, so that it came to specify a different amino acid, just about every protein in the body would instantaneously change, probably in many places along its length. Unlike an ordinary mutation...this would spell disaster." (2009, p. 409-10) OK. Keep Dawkins' claim of universality in mind, along with his argument for why the code must be universal, and then go here (linked site listing 23 variants of the genetic code). Simple counting question: does "one or two" equal 23? That's the number of known variant genetic codes compiled by the National Center for Biotechnology Information. By any measure, Dawkins is off by an order of magnitude, times a factor of two. http://www.evolutionnews.org/2011/03/venter_vs_dawkins_on_the_tree_044681.html
The bottom line is that if any code is ‘randomly changed’ in part, it throws a huge monkey wrench into the code and will be ‘instantly catastrophic’, to use Richard Dawkins most appropriate term, to the species thus rendering gradual change to the code impossible. In other words, the entire code must be implemented ‘top down’! Please note, this is not randomly changing sequences within the code that we are talking about, as you are talking about with your questionable 98% figure, this is talking about making changes to a code itself. The reason I bring this non-evolvability of codes up is because of alternative splicing codes. Namely, alternative splicing codes are found to be 'species-specific'. First off, there was recently discovered to be an alternative splicing code that sits on top of the genetic code. A code that regulates when and where genes get turned on and off, among other things:
Deciphering the splicing code - May 2010 Excerpt: Here we describe the assembly of a ‘splicing code’, which uses combinations of hundreds of RNA features to predict tissue-dependent changes in alternative splicing for thousands of exons. The code determines new classes of splicing patterns, identifies distinct regulatory programs in different tissues, and identifies mutation-verified regulatory sequences.,,, http://www.nature.com/nature/journal/v465/n7294/full/nature09000.html Breakthrough: Second Genetic Code Revealed - May 2010 Excerpt: The paper is a triumph of information science that sounds reminiscent of the days of the World War II codebreakers. Their methods included algebra, geometry, probability theory, vector calculus, information theory, code optimization, and other advanced methods. One thing they had no need of was evolutionary theory,,, http://crev.info/content/breakthrough_second_genetic_code_revealed Researchers Crack 'Splicing Code,' Solve a Mystery Underlying Biological Complexity - May 2010 Excerpt: "Understanding a complex biological system is like understanding a complex electronic circuit. Our team 'reverse-engineered' the splicing code using large-scale experimental data generated by the group," http://www.sciencedaily.com/releases/2010/05/100505133252.htm
Secondly, alternative splicing is simply astonishing and is certainly nothing that was expected on a neo-Darwinian view of things:
Researchers Crack ‘Splicing Code,’ Solve a Mystery Underlying Biological Complexity Excerpt: “For example, three neurexin genes can generate over 3,000 genetic messages that help control the wiring of the brain,” says Frey. “Previously, researchers couldn’t predict how the genetic messages would be rearranged, or spliced, within a living cell,” Frey said. “The splicing code that we discovered has been successfully used to predict how thousands of genetic messages are rearranged differently in many different tissues. http://www.sciencedaily.com/releases/2010/05/100505133252.htm Design In DNA – Alternative Splicing, Duons, and Dual coding genes – video (5:05 minute mark) http://www.youtube.com/watch?v=Bm67oXKtH3s#t=305 The Extreme Complexity Of Genes – Dr. Raymond G. Bohlin - video http://www.metacafe.com/watch/8593991/ Time to Redefine the Concept of a Gene? - Sept. 10, 2012 Excerpt: As detailed in my second post on alternative splicing, there is one human gene that codes for 576 different proteins, and there is one fruit fly gene that codes for 38,016 different proteins! While the fact that a single gene can code for so many proteins is truly astounding, we didn’t really know how prevalent alternative splicing is. Are there only a few genes that participate in it, or do most genes engage in it? The ENCODE data presented in reference 2 indicates that at least 75% of all genes participate in alternative splicing. They also indicate that the number of different proteins each gene makes varies significantly, with most genes producing somewhere between 2 and 25. Based on these results, it seems clear that the RNA transcripts are the real carriers of genetic information. This is why some members of the ENCODE team are arguing that an RNA transcript, not a gene, should be considered the fundamental unit of inheritance. http://networkedblogs.com/BYdo8 Landscape of transcription in human cells – Sept. 6, 2012 Excerpt: Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.,,, Isoform expression by a gene does not follow a minimalistic expression strategy, resulting in a tendency for genes to express many isoforms simultaneously, with a plateau at about 10–12 expressed isoforms per gene per cell line. http://www.nature.com/nature/journal/v489/n7414/full/nature11233.html
bornagain
November 7, 2015
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@Mung, #614:
Hi ThickPython, and welcome back. Were you off celebrating that own goal along with Nick M?
No, I'm preparing my 5 year old son (for the THIRD time) to have his skull removed, expanded, remodelled and glued back onto his head so that he doesn't die from intracranial pressure. Excuse me for thinking that's more important than talking to you.
Do you know what a sequence space is yet?
Yes, theoretically the sequence space is 20 ^ 100. Do you understand that because much of the amino acid sequence is replaceable, that this sequence space is reduced enormously?ThickPython
November 7, 2015
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@BornAgain, #613:
That’s your story and your sticking to it? a half man half ape creature existed BEFORE the supposed split of chimps and man?
Well, you changed "half man half chimp" to "half man half ape" in this comment, but that's fine. Approximately 6 million years ago, there was a common ancestor to both chimps and humans, and it is the genome of that species that has been passed on to the progenitors of the human lineage, and the progenitors of the chimpanzee/bonobo lineage. That's what common descent entails. Were you under the impression that we actually evolved from chimps?ThickPython
November 7, 2015
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Hi ThickPython, and welcome back. Were you off celebrating that own goal along with Nick M? Do you know what a sequence space is yet?Mung
November 7, 2015
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That's your story and your sticking to it? a half man half ape creature existed BEFORE the supposed split of chimps and man? Okie Dokie, FYI, I've got a movie to go to tonight that has a far more believable plot line than that. :)bornagain
November 7, 2015
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I'd like to know if anyone has contacted Dr Tomkins and asked him to come here and defend himself. Anyone?ThickPython
November 7, 2015
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@BornAgain, #579:
So, since he cut the number in half, I guess that means he believes a half human, half chimp, creature existed BEFORE chimps and humans diverged from that supposed half-man half-chimp common ancestor?
Yes.
What about all those cartoon drawings showing chimps coming from some apelike creature and humans coming from some chimp-like creature?
You mean "The Ascent of Man" cartoons? I think they're quite misleading. They aren't an accurate representation of common descent.ThickPython
November 7, 2015
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@Virgil Cain, #605:
That is the propaganda I am looking for validation.
... and @Andre, #577:
It’s also possible that he doesn’t get that, under neutrality (without selection), the substitution rate equals the mutation rate.
Are you assuming it? Or can you actually very this?
I posted a very easy-to-understand link to the mathematical formula. It's fairly trivial, I'm very concerned that you don't understand it. This little "fixation" tangent came about after I posted an explanation to Andre in #569, showing why the difference between human and chimpanzee genomes was easily achievable in the ~6m years since divergence. And if you [ can't | don't | won't ] understand the fixation formula, then as I wrote before, it is easier if you:
Think of yourself as the accumulation of all the mutations going back six million years. Every generation you accumulate a handful of mutations, and you pass those mutations on to your children.
... and then you just do the math to work out how many mutations need to be passed down each generation, and then compare that to empirical studies. You'll see that they are in line. All this talk about repair mechanisms is irrelevant - the repair of "almost mutations" (nice one Nick!) is already taken into account.ThickPython
November 7, 2015
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The rate of fixation for neutral mutations is equivalent to the mutation rate.
That is the propaganda I am looking for validation.
You don't even know what it means.Roy
November 7, 2015
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Me:
But I will nevertheless attempt to support that claim in terms you might understand if you have the guts to try to differentiate fixation time from fixation rate. Otherwise I won’t waste my time.
VG's response:
OK Roy, we get it. All you can do is post your tripe as if it means something.
VG chickened out. Not that I'm surprised.Roy
November 7, 2015
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When one picture speaks louder than a thousand words.Box
November 6, 2015
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I wonder why these creatures don't follow the math? Perhaps they just don't understand the math and need to read wikipedia? :)
The Paradox of the "Ancient" (250 Million Year Old) Bacterium Which Contains "Modern" Protein-Coding Genes: Heather Maughan*, C. William Birky Jr., Wayne L. Nicholson, William D. Rosenzweig§ and Russell H. Vreeland ; Excerpt: “Almost without exception, bacteria isolated from ancient material have proven to closely resemble modern bacteria at both morphological and molecular levels.” http://mbe.oxfordjournals.org/cgi/content/full/19/9/1637 “Raul J. Cano and Monica K. Borucki discovered the bacteria preserved within the abdomens of insects encased in pieces of amber. In the last 4 years, they have revived more than 1,000 types of bacteria and microorganisms — some dating back as far as 135 million years ago, during the age of the dinosaurs.,,, In October 2000, another research group used many of the techniques developed by Cano’s lab to revive 250-million-year-old bacteria from spores trapped in salt crystals. With this additional evidence, it now seems that the “impossible” is true.” http://www.physicsforums.com/showthread.php?t=281961 Revival and identification of bacterial spores in 25- to 40-million-year-old Dominican amber Dr. Cano and his former graduate student Dr. Monica K. Borucki said that they had found slight but significant differences between the DNA of the ancient, 25-40 million year old amber-sealed Bacillus sphaericus and that of its modern counterpart, http://www.sciencemag.org/cgi/content/abstract/268/5213/1060
According to prevailing evolutionary dogma, there ‘HAS’ to be ‘major genetic drift’ to the DNA of modern bacteria from 250 million years ago, even though, in the ever flexible theory of Darwinism, the morphology (shape) of the bacteria can be expected to remain exactly the same. In spite of their preconceived materialistic bias, scientists find there is no significant genetic drift from the ancient DNA. In reply to a personal e-mail from myself, Dr. Cano commented on the 'Fitness Test' I had asked him about: Dr. Cano stated:
"We performed such a test, a long time ago, using a panel of substrates (the old gram positive biolog panel) on B. sphaericus. From the results we surmised that the putative "ancient" B. sphaericus isolate was capable of utilizing a broader scope of substrates. Additionally, we looked at the fatty acid profile and here, again, the profiles were similar but more diverse in the amber isolate.": Fitness test which compared ancient amber sealed bacteria to its modern day descendants, RJ Cano and MK Borucki
Thus, the most solid evidence available for the most ancient DNA scientists are able to find does not support evolution happening on the molecular level of bacteria. In fact, according to the fitness test of Dr. Cano, the change witnessed in bacteria conforms to the exact opposite, Genetic Entropy; a loss of functional information/complexity, since fewer substrates and fatty acids are utilized by the modern strains. Considering the intricate level of protein machinery it takes to utilize individual molecules within a substrate, we are talking an impressive loss of protein complexity, and thus loss of functional information, from the ancient amber sealed bacteria. Further notes to 'drift'
Natural Selection Struggles to Fix Advantageous Traits in Populations - Casey Luskin - October 23, 2014 Excerpt: Michael Lynch, an evolutionary biologist at Indiana University,, writes that "random genetic drift can impose a strong barrier to the advancement of molecular refinements by adaptive processes."2 He notes that the effect of drift is "encouraging the fixation of mildly deleterious mutations and discouraging the promotion of beneficial mutations."3 Likewise, Eugene Koonin, a leading scientist at the National Institutes of Health, explains that genetic drift leads to "random fixation of neutral or even deleterious changes."4 http://www.evolutionnews.org/2014/10/natural_selecti_3090571.html "Lynch and Abegg assumed [in their paper] that organisms will acquire a given complex adaptation by traversing a direct path to the new anatomical structure. Each mutation would build on the previous one in the most efficient manner possible – with no setbacks, false starts, aimless wandering, or genetic degradation – until the desired structure or system (or gene) is constructed. Thus, they formulated an undirected model of evolutionary change, and one that assumes, moreover, that there is no mechanism available (such as natural selection) that can lock in potentially favorable mutational changes on the way to some complex advantageous structure…. Yet nothing in Lynch’s neutral model ensures that potentially advantageous mutations will remain in place while other mutations accrue. As Axe explains [in his reply to Lynch], “Productive changes cannot be ‘banked,’ whereas Equation 2 [one of Lynch’s equations] presupposes that they can.” Instead, Axe shows, mathematically, that degradation (the fixation of mutational changes that make the complex adaptation less likely to arise) will occur much more rapidly than constructive mutations, causing the expected waiting time to increase exponentially." Stephen Meyer - Darwin”s Doubt (Harper One, 2013, p. 328, "For example, McBride criticizes me for not mentioning genetic drift in my discussion of human origins, apparently without realizing that the result of Durrett and Schmidt rules drift out. Each and every specific genetic change needed to produce humans from apes would have to have conferred a significant selective advantage in order for humans to have appeared in the available time (i.e. the mutations cannot be 'neutral'). Any aspect of the transition that requires two or more mutations to act in combination in order to increase fitness would take way too long (greater than 100 million years). My challenge to McBride, and everyone else who believes the evolutionary story of human origins, is not to provide the list of mutations that did the trick, but rather a list of mutations that can do it. Otherwise they're in the position of insisting that something is a scientific fact without having the faintest idea how it even could be." Doug Axe PhD. Ann Gauger on genetic drift - August 2012 Excerpt: The idea that evolution is driven by drift has led to a way of retrospectively estimating past genetic lineages. Called coalescent theory, it is based on one very simple assumption — that the vast majority of mutations are neutral and have no effect on an organism’s survival. (For a review go here.) According to this theory, actual genetic history is presumed not to matter. Our genomes are full of randomly accumulating neutral changes. When generating a genealogy for those changes, their order of appearance doesn’t matter. Trees can be drawn and mutations assigned to them without regard to an evolutionary sequence of genotypes, since genotypes don’t matter. https://uncommondescent.com/evolution/ann-gauger-on-genetic-drift/ The waiting time problem in a model hominin population - 2015 Sep 17 John Sanford, Wesley Brewer, Franzine Smith, and John Baumgardner Excerpt: The program Mendel’s Accountant realistically simulates the mutation/selection process,,, Given optimal settings, what is the longest nucleotide string that can arise within a reasonable waiting time within a hominin population of 10,000? Arguably, the waiting time for the fixation of a “string-of-one” is by itself problematic (Table 2). Waiting a minimum of 1.5 million years (realistically, much longer), for a single point mutation is not timely adaptation in the face of any type of pressing evolutionary challenge. This is especially problematic when we consider that it is estimated that it only took six million years for the chimp and human genomes to diverge by over 5 % [1]. This represents at least 75 million nucleotide changes in the human lineage, many of which must encode new information. While fixing one point mutation is problematic, our simulations show that the fixation of two co-dependent mutations is extremely problematic – requiring at least 84 million years (Table 2). This is ten-fold longer than the estimated time required for ape-to-man evolution. In this light, we suggest that a string of two specific mutations is a reasonable upper limit, in terms of the longest string length that is likely to evolve within a hominin population (at least in a way that is either timely or meaningful). Certainly the creation and fixation of a string of three (requiring at least 380 million years) would be extremely untimely (and trivial in effect), in terms of the evolution of modern man. It is widely thought that a larger population size can eliminate the waiting time problem. If that were true, then the waiting time problem would only be meaningful within small populations. While our simulations show that larger populations do help reduce waiting time, we see that the benefit of larger population size produces rapidly diminishing returns (Table 4 and Fig. 4). When we increase the hominin population from 10,000 to 1 million (our current upper limit for these types of experiments), the waiting time for creating a string of five is only reduced from two billion to 482 million years. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4573302/ Majestic Ascent: Berlinski on Darwin on Trial - David Berlinski - November 2011 Excerpt: The publication in 1983 of Motoo Kimura's The Neutral Theory of Molecular Evolution consolidated ideas that Kimura had introduced in the late 1960s. On the molecular level, evolution is entirely stochastic, and if it proceeds at all, it proceeds by drift along a leaves-and-current model. Kimura's theories left the emergence of complex biological structures an enigma, but they played an important role in the local economy of belief. They allowed biologists to affirm that they welcomed responsible criticism. "A critique of neo-Darwinism," the Dutch biologist Gert Korthof boasted, "can be incorporated into neo-Darwinism if there is evidence and a good theory, which contributes to the progress of science." By this standard, if the Archangel Gabriel were to accept personal responsibility for the Cambrian explosion, his views would be widely described as neo-Darwinian. http://www.evolutionnews.org/2011/11/berlinski_on_darwin_on_trial053171.html (With the adoption of the 'neutral theory' of evolution by prominent Darwinists, and the casting aside of Natural Selection as a major player in evolution),,, "One wonders what would have become of evolution had Darwin originally claimed that it was simply the accumulation of random, neutral variations that generated all of the deeply complex, organized, interdependent structures we find in biology? Would we even know his name today? What exactly is Darwin really famous for now? Advancing a really popular, disproven idea (of Natural Selection), along the lines of Luminiferous Aether? Without the erroneous but powerful meme of “survival of the fittest” to act as an opiate for the Victorian intelligentsia and as a rationale for 20th century fascism, how might history have proceeded under the influence of the less vitriolic maxim, “Survival of the Happenstance”?" - William J Murray
bornagain
November 5, 2015
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TP:
The rate of fixation for neutral mutations is equivalent to the mutation rate.
That is the propaganda I am looking for validation.Virgil Cain
November 5, 2015
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@virgil Cain, #603:
OK Roy, we get it. All you can do is post your tripe as if it means something. No one has any idea if neutral mutations will reach fixation nor do they know the rate at which it will happen. There isn’t any mathematical relationship other than that which exists in imaginationland.
The rate of fixation for neutral mutations is equivalent to the mutation rate. We've both told you that this is a simple mathematical proof, yet you seem to be incapable of doing even the most basic of research to verify this for yourself: https://en.wikipedia.org/wiki/Fixation_(population_genetics)#Probability_of_fixation And no, I'm not "off celebrating", I've got some real world things happening for about the next two weeks. If anyone wants to discuss Jeff Tomkins results then I'll be sure to respond, but I'm not going to waste my time explaining stuff to people that should be able to work it out for themselves.ThickPython
November 5, 2015
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OK Roy, we get it. All you can do is post your tripe as if it means something. No one has any idea if neutral mutations will reach fixation nor do they know the rate at which it will happen. There isn't any mathematical relationship other than that which exists in imaginationland.Virgil Cain
November 4, 2015
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1) That would be validation, not verification.
Provide the validation, then
No. Verifying the mathematical relationship between mutation and fixation rates is straightforward; validating it in the field would be extremely difficult and time-consuming and to anyone who actually understands the maths it's as unnecessary as tossing two million coins to see if you get a million heads and a million tails. If you want it validated, do it yourself.
I was showing how the math didn’t pan out for that.
You were saying that a number from a paper you haven't read is bigger than a number from another paper you haven't read. Your preceding comment: "Roy, I asked for verification, you know something real that says the math is correct. As in show us a new neutral mutation becoming fixed in a typical population." suggests that you don't know the difference between fixation time and fixation rate, since you're asking for an example of one to validate a calculation of the other. Unless you can demonstrate that you actually can tell the difference there's not even any point providing the mathematical relationship between mutation and fixation rates since you wouldn't know what to do with it.
You shouldn’t make claims that you cannot support and pass them off as facts. ... Yes, I know. That is my whole point- you shouldn’t be making claims that you cannot empirically support. ... What I have done is merely ask you to support your claims.
The only claim I made was that I had verified the mathematics behind the relationship between mutation and fixation rates. You are not only asking me to support claims I haven't made, you're asking in a way that demonstrates you don't have the faintest clue about fixation rates. But I will nevertheless attempt to support that claim in terms you might understand if you have the guts to try to differentiate fixation time from fixation rate. Otherwise I won't waste my time. RoyRoy
November 4, 2015
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Cornelius Hunter:
A beautiful pair of own goals in quick succession.
I think they are off celebrating.Mung
November 4, 2015
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Roy:
1) That would be validation, not verification.
Provide the validation, then
2) You were querying that the fixation rate without selection was the same as the mutation rate – not the number of generations required for fixation of beneficial mutations.
I was showing how the math didn't pan out for that.
3) I’ve read Haldane’s paper.
And?
The math is so commonplace it doesn’t need to be experimentally validated.
Yes, it does. The math may be commonplace but if it doesn't fit reality then it is not only useless but harmful.
5) Even though the maths is commonplace it is apparently beyond you.
Your cowardice is duly noted
6) Showing that the number of generations to fixation is high is irrelevant to a claim about the rates of mutation and fixation.
You shouldn't make claims that you cannot support and pass them off as facts.
7) Since truly neutral mutations have no effect on phenotype, the only way to detect their first appearance and follow them to fixation is to sequence the DNA of every member of a population over many generations.
Yes, I know. That is my whole point- you shouldn't be making claims that you cannot empirically support.
What you have just goalpost-shifted...
What I have done is merely ask you to support your claims. If you can't support your claims then continually making them and acting as if they are facts, is a sign of insanity and dishonesty.Virgil Cain
November 4, 2015
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1) That would be validation, not verification. 2) You were querying that the fixation rate without selection was the same as the mutation rate - not the number of generations required for fixation of beneficial mutations. 3) I've read Haldane's paper. You clearly haven't. 4) The math is so commonplace it doesn't need to be experimentally validated. You might as well have asked for something real that says tossed coins land heads-up roughly 50% of the time. 5) Even though the maths is commonplace it is apparently beyond you. 6) Showing that the number of generations to fixation is high is irrelevant to a claim about the rates of mutation and fixation. 7) Since truly neutral mutations have no effect on phenotype, the only way to detect their first appearance and follow them to fixation is to sequence the DNA of every member of a population over many generations. What you have just goalpost-shifted to is so obviously impossible to provide that only an incompetent would even ask.Roy
November 4, 2015
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Roy, I asked for verification, you know something real that says the math is correct. As in show us a new neutral mutation becoming fixed in a typical population. Haldane thought a beneficial mutation would get fixed in about 300 generations. Fruit fly experiments have it over 600.Virgil Cain
November 4, 2015
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ROY So probability like assumptions are considered facts?Andre
November 4, 2015
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VG @ 591: I'm afraid I didn't keep the scrap of paper of scribbles where I independently derived that result. You probably couldn't have understood my handwriting anyway. But it's not that hard - mostly high-school algebra and probability. Again, why don't you try working it out for yourself?Roy
November 4, 2015
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