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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
Andre, yup. Apparently, they think that we're obliged to believe that the random reactions in their brains can differentiate between reality and fantasy.Vy
October 28, 2015
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Vy
When evodelusionsts accuse you of quote-mining, you know you’ve got something.
And when they say "You don't understand"Andre
October 28, 2015
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If you’re suggesting that my position is that when I see data that are in apparent conflict with common descent then it is necessarily and automatically an error in the data (or software, whatever), then I don’t see how we can possibly have a respectful and honest conversation.
Squeak, those were your words not mine.
See my post at #191, and maybe re-state your argument without the obvious straw man.
They are your own words so stop imagining straw men.Vy
October 28, 2015
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Thickpython You start with the assumption that CD is true and that is why you can't see the wood from the trees......Andre
October 28, 2015
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@Vy, #346: If you're suggesting that my position is that when I see data that are in apparent conflict with common descent then it is necessarily and automatically an error in the data (or software, whatever), then I don't see how we can possibly have a respectful and honest conversation. See my post at #191, and maybe re-state your argument without the obvious straw man.ThickPython
October 28, 2015
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You’ve quote-mined like a pro
Right. When evodelusionsts accuse you of quote-mining, you know you've got something.Vy
October 28, 2015
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TP:
Just so we’re clear, you’re saying that articles like this: https://www.icr.org/article/5867/ .. are evidence against common descent.
No. My position is there isn't any evidence for Universal Common Descent. That is because no one knows what makes an organism what it is. Until someone can come up with a way to scientifically test the claim there isn't any need to refute it.Virgil Cain
October 28, 2015
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You’ve quote-mined like a pro
Right.Vy
October 28, 2015
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@Vy, #344: Similar to what I said a few posts back, I'm getting tired of people spouting off crap, and not actually doing the work. You've quote-mined like a pro. The first two quotes from the New Scientist article are clearly referring to HGT in bacteria and archaea, and you'd know that if you read and comprehended the article. Please see my post at #331. Regarding incongruence in general, please see Nick's post at #171 (and my endorsement of it at #178). There are clearly other factors that can cause trees to be incongruent, and the "Lessons from Phyllostomid Bats" paper tries to systematically remove these factors. As for your "key assumption" quote, that's blatantly out of context and I think you should retract. The heading for that section is "Only orthologous genes should be used to construct species phylogenetic trees" - meaning that merely homologous sequences (as opposed to strictly orthologous sequences) can cause incongruence in phylogenetics. Consider an example where, in the common ancestor to species A and B (and C and D and E etc.), a particular gene has undergone duplication. When constructing a phylogenetic tree, care must be taken to ensure that we are not comparing the original gene in species A to the copy of the gene in species B.ThickPython
October 28, 2015
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SqueakPython says:
You’re coming at this from the wrong direction – you’re suggesting that data is forced to fit the assumption of common descent, when that’s not what’s happening at all. There are no inbuilt assumptions of common descent in tree building – you can build a tree with whatever kind of data you like (data completely unrelated to biology) but most of them will be garbage
And yet only a few umpteen comments earlier, he said:
The software used to automatically annotate the genomes isn’t perfect. Humans can spot these errors. In fact, one of the ways to spot these sort of errors is when the data are in apparent conflict with common descent!
Anyone who hasn't got their brain clogged up with fogma (ref: CEH Dictionary) can see the blatant contradiction. Squeak, find that fish, it smells!Vy
October 28, 2015
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@Virgil Cain: "Equidistance of something your position cannot explain in the first place? LoL!" Just so we're clear, you're saying that articles like this: https://www.icr.org/article/5867/ .. are evidence against common descent. Is that your position?ThickPython
October 28, 2015
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The reason why phylogenetic trees are not garbage, and the reason they strongly indicate common descent is because they consistently match other trees that are built using independent data
Looks like you're stuck in fantasy-ville.
"For a long time the holy grail was to build a tree of life", says Eric Bapteste, an evolutionary biologist at the Pierre and Marie Curie University in Paris, France. A few years ago it looked as though the grail was within reach. But today the project lies in tatters, torn to pieces by an onslaught of negative evidence. Many biologists now argue that the tree concept is obsolete and needs to be discarded. "We have no evidence at all that the tree of life is a reality", says Bapteste. (Graham Lawton - "Why Darwin Was Wrong About the Tree of Life", New Scientist. January 21, 2009)
The problems began in the early 1990s when it became possible to sequence actual bacterial and archaeal genes rather than just RNA. Everybody expected these DNA sequences to confirm the RNA tree, and sometimes they did but, crucially, sometimes they did not. RNA, for example, might suggest that species A was more closely related to species B than species C, but a tree made from DNA would suggest the reverse.
Incongruence between phylogenies derived from morphological versus molecular analyses, and between trees based on different subsets of molecular sequences has become pervasive as datasets have expanded rapidly in both characters and species. (Liliana M. Dávalos, Andrea L. Cirranello, Jonathan H. Geisler, and Nancy B. Simmons, "Understanding Phylogenetic Incongruence: Lessons from Phyllostomid Bats" - Biological Reviews of the Cambridge Philosophical Society, Vol. 87: 991-1024 (2012))
Phylogenetic conflict is common, and frequently the norm rather than the exception.
The phylogenetic relationships among most metazoan phyla remain uncertain. (Rokas et al., "Animal Evolution and the Molecular Signature of Radiations Compressed in Time," Science, Vol. 310: 1933-1938 (December 23, 2005))
Again, the problem lies in the fact that trees based upon one gene or protein often conflict with trees based upon other genes. Their study employed the many-gene technique, and yet still found that [a] 50-gene data matrix does not resolve relationships among most metazoan phyla.
The key assumption made when constructing a phylogenetic tree from a set of sequences is that they are all derived from a single ancestral sequence, i.e., they are homologous. (Marketa Zvelebil and Jeremy O. Baum, Understanding Bioinformatics, page 239 (Garland Science, 2008))
Cladistics can run into difficulties in its application because not all character states are necessarily homologous. Certain resemblances are convergent -- that is, the result of independent evolution. We cannot always detect these convergences immediately, and their presence may contradict other similarities, ‘true homologies’ yet to be recognized. Thus, we are obliged to assume at first that, for each character, similar states are homologous, despite knowing that there may be convergence among them. (Guillaume Lecointre & Hervé Le Guyader, The Tree of Life: A Phylogenetic Classification, page 16 (Harvard University Press, 2006))
So far, all evidence points to the fact that phylogentic trees are in fact garbage and do not point to common descent, much less match independent data.Vy
October 28, 2015
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TP:
Please don’t tell me you’re going to pull out that equidistance crap?
Equidistance of something your position cannot explain in the first place? LoL!Virgil Cain
October 28, 2015
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Just want to make a correction In post 338 & 340 The figure is actually 2 940 000 000 and not 2 994 000 000, apologies for the typos....Andre
October 27, 2015
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To verify what I have to say about mutation rates from Lenski's lab http://www.nature.com/nature/journal/v461/n7268/full/nature08480.html http://www.sciencedirect.com/science/article/pii/S0960982209020594 These numbers are not nearly enough to get to where you want to be. Not even close! So if you are honest with yourself, you would know that Lenski's experiment falsifies Darwinian evolution's grand claim.Andre
October 27, 2015
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Franklin you can't compare 8/10 with 2 994 000 000/3 000 000 000 units in that way but it is the number of actual differences that need to be counted and in this case its 2 vs 60 000 000.Andre
October 27, 2015
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Franklin
Andre to better represent the conundrum you posed for yourslf if we considerd your 10 base pair alignment with 2 mismatched bases the 60 mil out of 3 bill would be analogous to 9.8 matches out of 10 for the human:chimp sequence alignment. how is that not making a case?
But its not, its a literal 60 000 000 base pair difference the percentage difference is meaningless in regards to the total amount of actual units.Andre
October 27, 2015
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Right It is true that a 8 out of 10 is a 20% difference, but its a total difference of 2 units. If we look at at 2 994 000 000 out of 3 000 000 000 its only a 2% difference but a whopping 60 000 000 unit difference. This is no trivial difference, or almost the same not by a long shot! This is not about the difference in percentage but the difference in units..... 60 000 000 of them. Now lets chat about the idea that these 60 000 000 base pair difference could become fixed in only 6 000 000 years. That means a whopping 10 million base pair changes fixed in the population for every 1 000 000 years. Do we have data that can verify or falsify such a claim? In fact we do, Lenski's experiment holds about 1 000 000 years of evolution time in the petri dishes, lets see how many changes have become fixed in that time slot? 100? 200? 1000? 5000? 100 000? Not anywhere near 10 000 000 not even close. And as I have argued before for these 60 000 000 base pair diffreces to be come fixed in only 6 000 000 years NS & RM, drift, and any other form of evolution has to deal with the following....... 1.) Multiple DNA Integrity check systems (Evolutionary conserved) 2.) Multiple DNA Repair Mechanisms (Evolutionary conserved) 3.) Multiple Apoptosis systems (Evolutionary conserved) 4.) Necrotic system (Evolutionary conserved) You are welcome to believe that these 60 000 000 base pair differences can by some magic process become fixed considering the odds and systems in place to prevent it from happening. Me I just don't have that much faith.Andre
October 27, 2015
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Andre to better represent the conundrum you posed for yourslf if we considerd your 10 base pair alignment with 2 mismatched bases the 60 mil out of 3 bill would be analogous to 9.8 matches out of 10 for the human:chimp sequence alignment. how is that not making a case?franklin
October 27, 2015
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Andre in your example you accept that a 20% difference(2:10) is non-asignificant mismatch and deemed worthy of making a case. However, you reject the 60 million out of 3 billion base pair non-alignment as being significantly mismatched and not making a case. You do realize that 60 000 000 out of 3 000 000 000 represents a 2% difference in alignment. So you don't accept an alignment that has an order of magnitude better alignment than what you describe as being acceptable. how does that work, exactly?franklin
October 27, 2015
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If there is a 98% alignment out of 3 000 000 000 pairs you still have a 60 000 000 Base pair mismatch it really is not almost all aligned no matter how much you want it to be. If there was only 10 Base pairs and 8 lined up with only 2 differences then you would sort of have a case. But yes please come give us an entire Human and chimp genome sequence.Andre
October 27, 2015
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@Peer, #327: " ... only 2.4 Mb had a match in the 2.85 Mb human probe." Of course I've read that, and done plenty of work on it. "Around the same time, Roy Britten showed that the Protein-Coding Part of the chimp and human genomes differ by 5 percent counting indels." And yes, I've read that and done my own comparisons. "Further, we know since ages that, by simply weighing, the genome of chimps exceed that of humans by approx 10 percent." Have we really? And by "simply weighing" them? I posted on this only last week: https://roohif.wordpress.com/2015/10/19/how-big-is-the-chimpanzee-genome/ "I recommend Williamson to brush up a bit into the bioscience literature instead of provoking confusion." You've made three claims above, one of which I happened to address very recently. Now, you can choose one of the remaining two, but before I post some actual results, I'd like to know what you're risking. Basically I'm getting pretty sick of people just repeating these claims that they hear or read without doing their own research to see if they actually check out. So, in the first example, I assume you're saying that only 2.4Gb of sequence actually aligns. What will you do when I demonstrate that virtually all of it aligns? Will you admit that you are wrong, or will you slink of to another forum and repeat the same crap to another bunch of people?ThickPython
October 27, 2015
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Thickpython Who drew the first tree? I think us asking Dr Venter for clarity is a very good thing. If I wrong had misunderstood him then I'll accept that.Andre
October 27, 2015
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@Virgil Cain, #320: "The NCSE did a hack job on Dr Denton after his “Evolution: A Theory in Crisis” was published. No one seemed to notice, though." Wow. Please don't tell me you're going to pull out that equidistance crap? It amazes me that two allegedly smart people - Jonathan Sarfati and Nathaniel Jeanson have actually repeated it.ThickPython
October 27, 2015
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@Andre, #282: "I am saying that the data does not show common descent it is forced to fit the assumption of common descent. If we remove the assumption what do we get?" You're coming at this from the wrong direction - you're suggesting that data is forced to fit the assumption of common descent, when that's not what's happening at all. There are no inbuilt assumptions of common descent in tree building - you can build a tree with whatever kind of data you like (data completely unrelated to biology) but most of them will be garbage. The reason why phylogenetic trees are not garbage, and the reason they strongly indicate common descent is because they consistently match other trees that are built using independent data. Plus we have a very simple, observable theory that would produce such trees: descent with modification. "I think Dr. Venter answers it aptly." I think you are missing a lot of nuance from that conversation. I guarantee you that Craig Venter accepts a "tree of life" all the way back to at least metazoans, if not all the way back to eukaryotes. The nuance that Venter is trying to get across in that conversation is that HGT is prevalent in these single celled organisms, so constructing a tree is near impossible, and that's why he uses the term "bush of life". That "bush of life" is kind of off to the side and kind of underneath the "tree of life". He is also conveying that there are several exceptions found to the standard codon table, but again, I guarantee you he will not claim that these belong to a "second genesis". If you're willing to put something on the line, I'll ask him these questions myself.ThickPython
October 27, 2015
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...logically and epistemologically cladograms should precede phylogenetic trees, and phylogenetic trees should precede scenarios.
- Robert M. Schoch. Phylogeny Reconstruction in Paleontology. 1986.Mung
October 27, 2015
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Sebestyen: However, there’s a two things to note: a) The phage was still infectious to begin with, the D1 and D3 sections of g3p were still intact. Even with D1 and D2 removed, the infectivity is still there 1. Or it wouldn't have replicated at all. Sebestyen: b) The infectivity never reached the level of the original D2 sequence and the paper states that other mechanisms than random substitutions must’ve played a role. It also requires recombination to avoid local fitness peaks, which is clear from studies of evolutionary algorithms. In any case, it answers your stated concern: "That’s like saying a feasible way to add a new function to a piece of software is by filling a module with random letters and then let a script randomly exchange letters at random positions until the module successfully compiles." That's what they did.Zachriel
October 27, 2015
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Zachrial wrote:
See Hayashi et al., Experimental Rugged Fitness Landscape in Protein Sequence Space, PLOS ONE 2006. They replace a section of a phage genome crucial for infectivity with a random sequence, then they mutate and select for infectivity. Guess what happens.
I know what happened, the mutation/selection cycles increased the infectivity. However, there's a two things to note: a) The phage was still infectious to begin with, the D1 and D3 sections of g3p were still intact. Even with D1 and D2 removed, the infectivity is still there 1. b) The infectivity never reached the level of the original D2 sequence and the paper states that other mechanisms than random substitutions must've played a role. It's an interesting read but overall I'm less than impressed by the results in regards to the neutral evolution claim. [1] L Riechmann, P Holliger The C-Terminal Domain of TolA Is the Coreceptor for Filamentous Phage Infection of E. coli Cell, 90 (1997), pp. 351–360Sebestyen
October 27, 2015
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When the chimp genome consortium published the Chimp-Human whole genome sequence comparison, something was immediately obvious for those who actually read Methode sections: only 2.4 Mb had a match in the 2.85 Mb human probe. Although 8 percent had been omitted from the studies, the consortium did not find this of sufficient importance to discuss this observation. Around the same time, Roy Britten showed that the Protein-Coding Part of the chimp and human genomes differ by 5 percent counting indels. Further, we know since ages that, by simply weighing, the genome of chimps exceed that of humans by approx 10 percent. I recommend Williamson to brush up a bit into the bioscience literature instead of provoking confusion.Peer
October 27, 2015
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NickMatzke_UD: and you are not saying what you mean by “fish”.
Zachriel: Be honest, Nick. Are you a “fish”?
Wow, what a genuinely sensible comment. I wonder which version of him was in control.Vy
October 27, 2015
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