Dr Page's best example of common descent explained from the GUToB.

Dear Dr Page,After careful consideration of your ultimate evidence of common descent I like to propose an alternative explanation from the GUToB (=(Non-)Random in a multi-purpose genome).As I understand it --correct me if I am wrong-- your figure demonstrates 21 old world monkeys (from Hsa to Tob) and 22 new world monkeys (from Cap to Ocu).I assume that you posted these homologue sequences in primates (I couldn’t find what gene it is) and the alignment of shared mutations as the ultimate proof for common descent. And you could be right if mutations are introduced at random only. However, as recently demonstrated mutations can be either random or non-random. Non random mutations (NRM) may have important implications for phylogenetic analysis based upon alignment of genes/DNA regions. We already discussed the mtDNA in ancient human and the ZFY region in primates and it should be obvious that NRM play an important role in the illusion of common descent.I also assume that the sequences start top-left at position 759. Since you also included a tree, it is now clear what the codes stands for. At least, for the old world monkeys. For instance, Hsa means Homo sapiens, Ptr means Pan troglodytes (chimp), Ppa is Pan paniscus (bobobo), Ggo is Gorilla gorilla, Ppy is Pongo pygmaeus (Orangutan), etcetera, etcetera. I do not know what the abbreviations of the new world monkeys stand for, since you didn’t provide the information and so we have to do without.Let’s have a thorough look at the figure.http://www2.norwich.edu/spage/alignmentgam.htmThe figure reveals that several spots in the homologues sequences demonstrate shared mutations: mutations on exactly the same spot in the DNA of several distinct organisms. Are these shared mutations due to common descent or due to a common mechanism?According to evolutionism the shared mutations are due to a mutation that occurred in a common ancestor and has been passed through into the species, thus being proof of common descent. On the other hand the GUToB holds that shared mutations are non-random mutations that have either been introduced on spots that are more prone to mutations --so called hotspot mutations--, while other shared mutations are due to a protein and/or RNA mediated mechanism. The mechanism are still obscure but probably due to the physicochemical properties of 3-dimensional DNA and protein/RNA mediated. NRM has been observed in bacteria, cone snails, viruses, in subspecies of D. melanogaster (e.g. the 1G5 gene), in the ancient human mtDNAs and in the ZFY region.
At first sight evolutionists seem to have a strong case with the sequences provided by Page. A superficial look would readily convince someone that common descent is a fact. However, I am not so easy to convince since I already found several examples in scientific literature that defy evolutionism (as demonstrated on this board and still denied by orthodox evolutionists).On second thought, however, most mutations in these sequences that are taken as proof for common descent behave very peculiar. They do not simply stay put after initial change, but often they are subject to another change. Overall the picture seems a lot like NRM in combination with RM (as expected from GUToB). Let’s have a close up look at the shared mutations in the first 110 nucleotides that give the impression of common descent.* Position 764/5: It is obvious that 764 (and also 765) is a non random position. It is either C or T and there is NO association with common descent (CD): Neither in old world monkeys (OWM) nor in new world monkeys (NWM).* Position 772: Non random (NR) position: Either G or T, and NO association with CD: Neither in OWM nor in NWM.* Position 779: semi-random (SR)-NR position. SR with respect to nucleotide, NR with respect to position. In NWM there is another peculiar rapid change in 5 positions (790, 791, 812, 814, 860) in the Ase, Abe, Aca clan (an MPG?).* Position 781: NR position: Either G or A, independent of NWO or OWM (as demonstrated for Hsa and Ptr).* Position 802: NR position: Either A or T, independent of NWM or OWM ( as demonstrated for Hsa, Ptr, Tba and Tsy)* Position 809: NR position in NWM. No association with CD.* Position 810: Probably reflects SR-NR: C, A or G on this position in OWM.* Position 812: NR position: Either C (in Cce; OWM) or G or T (in Bar; NWM).* Position 828: NR position: Either C or T, independent of NWM (e.g. Bar) or OWM (e.g. Has, Ptr, Ggo).* Position 831: SR-NR position in NWM (as observed in Apa).* Position 852: May reflect SR-NR position in OWM (e.g. Tob and Lat)* Position 856: SR-NR position in OWM: Either A (Aaz and Ana, as observed in NWM), but mostly G.* Positions 808, 819, 845: pure-NR positions, i.e NR with respect to nucleotide and with respect to position. (NB: These P-NR mutations are very tricky since they seem to give ultimate 'evidence' of common descent. Therefore we should also have a look into these sequences in subspecies).* In contrast, random mutations (RM) are scattered throughout the sequences and are easy to spot since they do not line up. For instance position 786 in Hla, and position 848 in Mmu. (According to ToE such mutations are introduced after they organisms split. Nice try, but never to be proven).Of course one can claim random mutation plus selection. But I don’t believe that selection takes place at the level of the nucleotide (and probably a lot of neutral positions are involved). Rather, non-random mutations may explain Page’s best example of common descent.
It should also be noted that a good theory must be able to explain all biological phenomena. As demonstrated in another thread the mutations in the primate ZFY region could not be explained by common descent, while the GUToB didn’t have a problem explaining these sequences. Overall, I expect the GUToB to be superior to the ToE.Best wishes,
Peter

Dr Borger,How many MPGs are there in the data?Or are they all included in the vertebrate arcehtype MPG which includes humans, fish, frogs, dinosaurs, whales, 'walking whales', and birds?

How do you know which nucleotide was in any particular
position before a copy error event?If you do not, then all copy errors could be random with
respect to nucleotide.Just because the modern sequences show either a G or a C
does not mean that some ancestor had a T at that location.The sequences are not descended from one another, after all.Hotspots aid ToE as currently considered, otherwise there is
no way to explain how a random copy error (in the time/effect
domain) can occur at the same locus.Overall, however, this argument is dead in the water before it
begins.You have proposed an explanation for the sequences that fits the
current data.ToE also explains it well.Using data that suports both views does not allow for a refutation
of either ... we need alternate evidence lines to make that
decision.The question at this stage is whether or not you idea really matches the data.

Hi Peter!Please provide a definition of GUToB and MPG and any other terms you commonly use. I might ask for changes/clarfications, but when we're done I'll put it on a webpage for easy reference.------------------
--EvC Forum Administrator

Hi Admin,A couple of months ago I posted my ideas about biology. Here is the updated version:The General and Universal Theory of Biology (GUToB) holds that organism are geared with multipurpose genomes (MPG) and can change within a limited range through non-random mutations (NRM). The GUToB does not exclude random mutations. For both MPG and NRM biological evidence has been presented on the EvC board.Why do we need a new biological theory?As demonstrated on several occasions evolutionary mechanism are questionable on the level of the genome and thus cannot be the right hypothesis to explain life on earth in all its variation. Why? Evolutionism supposed to have its foundations in molecular biology and genetics, and when the theory can be falsified at this level it lacks a proper foundation. Thus, it cannot be the right theory. Therefore, I introduced the GUToB. The pillars of GUToB are the multipurpose genome working in conjunction with non-random mutations.The concept of a multipurpose genome is not entirely new since a similar concept has been introduced by P. Scheele in his book ‘Degeneration’ (http://www.evolution-is-degeneration.com) and by L. Spetner in his book ‘Not by Chance’.In my opinion their hypotheses cannot explain all biological observations --like sequence similarities/shared mutations within related species-- and so it cannot be complete.Therefore, I also introduced and provided scientific evidence for non-random mutations (http://EvC Forum: molecular genetic proof against random mutation (1) -->EvC Forum: molecular genetic proof against random mutation (1)). The non-random mutations should be conceived as non-random with respect to nucleotide and position. At present they should not be conceived as deliberately introduced as a response to environmental change, since that cannot be scientifically proven (although such directed mutations have been found in Cone snails). NRM do have important implications for common descent, as explained in # 184 in ‘molecular genetic evidence against random mutation’ and here: http://EvC Forum: Dr Page's best example of common descent easily --and better-- explained by the GUToB -->EvC Forum: Dr Page's best example of common descent easily --and better-- explained by the GUToB).In conjunction with non-random mutation the idea of a multipurpose genome are able to explain all biological phenomena, including genetic redundancies and phylogenetics.
For scientific back-up for NRM see also Dr Caporale's book 'Darwin in the Genome' (ISBN 0-07-137822-7).The concept 'multipurpose genome' holds that:1) Functional DNA sequences —although plastic-- are stable throughout time,2) organisms demonstrate genetic redundancies that reside in the genome without selective constraint,3) mechanism for adaptive phenotypes and variation are preexisting and due to duplication and/or shuffling of preexisting DNA elements —either genes or other non-coding elements-- that affect gene expression, or due to loss of (redundant) genes, and through RNA editing,4) the main function of natural selection is to remove degenerate organisms, and5) there is/has been creation (=creaton interactions with matter in a morphogenic field giving rise to genes and genetic programs in preexisting genetic programs) of multipurpose genomes.Predictions:1) predicts that within species we do not see abundant variation with respect to genes, and usually such genetic alterations are neutral or degenerate (although distinct alleles can be expected through the principle of degeneration, which is in effect the action of entropy, the major mechanism is NRM).
It also predicts that all organism --even the simplest-- have an elaborate and accurate mechanism to counteract mutations.2) predicts that a considerable part of the genes of any organism can be knocked out without being lethal.3) predicts that adaptive phenotypes of organism do never demonstrate new genes unrelated to preexisting genes.4) predicts that organism lacking vital DNA elements are selected against.5) could predict that there are organisms that have not undergone genetic changes (yet).Falsification:1) The GUToB will be falsified by the observation of the evolution of new genes unrelated to preexisting genes.Of course, a novel theory is subject to changes. I invite everbody to think about it and to have constructive comments.Best wishes,
Peter[This message has been edited by peter borger, 03-05-2003]

Hi Peter,I was hoping for something a little more concise, along the lines of evolution's "Descent with modification through natural selection." I've started a new thread where we can hone this down: I'll post some suggestions over there soon.------------------
--EvC Forum Administrator

Hi Admin,Admin: I was hoping for something a little more concise, along the lines of evolution's "Descent with modification through natural selection."PB: What about "Variation through non-random mutation (NRM) of a multipurpose genome (MPG)"Peter

This leaves open the definition of NRM and MPG. Please see the thread Defining GUToB.------------------
--EvC Forum Administrator

Hi Admin,1) Non-Random Mutations type 1 (NRM1). This type of NRM introduces mutations on the same positions and the position where they are introduced depends on the DNA regions where it is part of. NRM1 are also known as ‘positional NRM’. NRM1 has been described for T4 virus. NRM1 is likely to be present in the ZFY region and in mtDNA.
Semi-Random positional mutations are a special form of NRM, i.e. semi-random with respect to nucleotide, but non-random with respect to position (=when mutations occur in the region they are always introduced at the same spot).
Implications: NRM1 will line up and give the illusion of common descent in phylogenetic analysis. Since phylo-geneticists cannot exclude NRM1, this type of mutations question the evolutionary conclusions that the alignment of genes and shared mutations is proof for common descent.2) Non-Random Mutations type 2 (NRM2). This type of NRM is mediated by protein and/or RNA driven mechanism that translocate preexisting DNA elements, or vary nucleotides in genes in a similar fashion as observed for immunoglobulins. NRM2 also plays a pivotal role in parasite-host interactions, and are likely to be abundant in other interactions between organisms where ‘evolutionary armsrace’ is ongoing. They have been demonstrated in the 1G5 gene in Drosophila, and in cone snail toxin genes.
Implications: NMR2 may give alignment of mutations (‘shared mutations’) in related MPGs. Variation is limited and preexistent.Best wishes,
Peter

These are the codes for the new world monkeys: (from here )
Platyrrhini - New World monkeys
Cal Cebus albifrons White-fronted Capuchin
Age Ateles geoffroyi Black-handed spider monkey
Apa Ateles paniscus Black spider monkey
Lla Lagothrix lagothrich Common wolley monkey
Bar Brachyteles arachnoides Wolley spider monkey
Aca Alouatta caraya Black howler
Abe Alouatta belzebul Black and red howler
Ase Alouatta seniculus Red howler
Tarsiiformes - tarsiers
Tba Tarsius bancanus Western tarsier
Tsy Tarsius syrichta Philippine tarsier
Strepsirhini - the "wet nosed" primates
Lorisiformes - lorises, bush babies, and galagos.
Ocr Otolemur crassicaudatus ---------------
Lemuriformes - lemurs
Efu Eulemur fulvus ---------------
Cme Cheirogaleus medus Fat-tailed dwarf lemur
Lagomorpha (Rabbits, hares, and pikas)
Ocu Oryctolagus cuniculus Domesticated / wild European wild rabbitCommon descent provides a very simple and clear explanation for the similarity as well as the differences in this sequence. That is genes are inherited and mutate. What is the GUToB explanation for the similarity?.The best way of detecting non random patterns and ensuring a minimum of observer bias is to use statistical tests. If statistical tests failed to support the predictions of common descent it would provide powerful support for the GUToB, but could potentially falsify GUToB. They are the only objective way to distinguish the two theories and should be relatively simple to perform as both theories make distinct predictions about the pattern of mutations you would expect to see.

Hi Peter,It would probably work better if we use this thread for a discussion of the common descent evidence and worked on a definition of GUToB over at the Defining GUToB thread. I'll post a response there.------------------
--EvC Forum Administrator

Itzpapalotl:
Common descent provides a very simple and clear explanation for the similarity as well as the differences in this sequence. That is genes are inherited and mutate. What is the GUToB explanation for the similarity?.The best way of detecting non random patterns and ensuring a minimum of observer bias is to use statistical tests. If statistical tests failed to support the predictions of common descent it would provide powerful support for the GUToB, but could potentially falsify GUToB. They are the only objective way to distinguish the two theories and should be relatively simple to perform as both theories make distinct predictions about the pattern of mutations you would expect to see.Judge:
Hi Itzpapalotl...this is interesting can you tell me where can be found the most comprehensive statistical analysis of this data?
Has anyone ever put this data into easy to an easy to understnd formula in one place?
What percentage of the data has been examined?Thanks for the other link...but do you know how much of the genomes were examined to arrive at these percentages?thanks[This message has been edited by judge, 03-11-2003]

Admin asked me to repost this here as it was more relevant
to this discussion ... I'll delete it from the
GUTOB thread.The following is how Peter Borger describes NRM:

quote:

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1) Non-Random Mutations type 1 (NRM1).
This type of NRM introduces mutations on the same positions and the
position where they are introduced depends on the DNA regions where it is part of.
NRM1 are also known as ‘positional NRM’.
NRM1 has been described for T4 virus.
NRM1 is likely to be present in the ZFY region and in mtDNA.

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Some locations in DNA sequences are more likely than others
to suffer copy errors.That is statistically more likely.Decsribing this as 'non-random' is spurious at best. Randomness
is takne, generally to mean, unpredictable ... which is what is
seen. Sometimes the location appears to have changed, sometimes
not. There is no known causative link.

quote:

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Semi-Random positional mutations are a special form of NRM, i.e. semi-random with respect to nucleotide, but
non-random with respect to position (=when mutations occur in the region they are always introduced at the same spot).

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'Semi-random' does not make sense at all.The changes seen are either caused by a mechanism or are
copy errors.The above observation would tend to undermine the idea of a
directed mechanism involved in copy errors.

quote:

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Implications: NRM1 will line up and give the illusion of common descent in phylogenetic analysis. Since phylo-geneticists cannot exclude NRM1, this type of mutations question the evolutionary conclusions that the alignment of genes and shared mutations is proof for common descent.

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That mutations often occur at a particular locus does not
undermine the common descent hypothesis.Perhaps common descent gives the illusion of directed evolution.The existence of alignments is not considered proof of common
descent ... it is one evidence for it.

quote:

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2) Non-Random Mutations type 2 (NRM2).

​

This type of NRM is mediated by protein and/or RNA driven
mechanism that translocate preexisting DNA elements, or vary nucleotides in genes in a similar fashion as observed for immunoglobulins.
NRM2 also plays a pivotal role in parasite-host interactions, and are likely to be abundant in other interactions between organisms where ‘evolutionary armsrace’ is ongoing.

​

They have been demonstrated in the 1G5 gene in Drosophila, and in cone snail toxin genes.

​

Implications: NMR2 may give alignment of mutations (‘shared mutations’) in related MPGs.

​

Variation is limited and preexistent.

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First, the last line in the above quoted section is, surely,
a starting assumption and not an implication of the NRM2.Mechanisms for mediating copy errors are compatible with standard
evolutionary theory too. They aid in preventing unviable organisms.Some questions for Peter Borger::1) Why do some MPG's translocate sequences and otehrs not when
there is a mechanism at work? Does the mechanism do different
things on the same inputs?2) Since we only have current genomes to examine, how can you tell
that some locii only ever bear certain nucleotides ... maybe ancient
versions of the same genome had different nucleotides in those
locations ... we cannot tell from modern genomes.3) If you are marking four assigments and find that they each have
the same opening paragraph but different concluding paragraphs
do you assume they are independent or based upon the same
source?

I don't think there has been a statistical analysis of the data certainly from the GUToB point of view. I was just suggesting that a visual inspection of data can give misleading conclusions and a statistical analysis would give more unbiased results. I will leave it up to peter borger to test the data against the predictions made by GUToB as he has the most complete understanding of his theory.Unfortunately only small parts of the chimpanzee genome have been sequenced so the comparison can only be made over short sequences and so low percentages of the genome. The final percentage difference will only be definatively calculated when the chimpanzee genome is finished which should hopefully be sson.http://sayer.lab.nig.ac.jp/~silver/ has a number of ape sequences and information on the genome projects.

Judge:
Hi Itzpapalotl...this is interesting can you tell me where can be found the most comprehensive statistical analysis of this data?
Has anyone ever put this data into easy to an easy to understnd formula in one place?
What percentage of the data has been examined?When you say of "this data", are you referring to the linked alignment?
If so, I can tell you from first hand knowledge that the analyses of that data are statistical tests. The phylogeny produced - the 'trees' - are the results of these analyses. When I performed the Maximum likelihood analysis on that data, for example, it took nearly a week to run (300Mhz processor - could be done in a few hours today I suppose). Phylogenetic analysis is not, contrary to what many creationists seem to want people to think, merely looking at data and saying 'well, looks like this goes with this.' In fact, phylogenetic analyses are very stringent, complicated statistical analyses of the data.

​

As for the formulas - they are not easy to understand. Or I should say the programs are not. They take into account substitution rates, rate variance, etc.
Here:
http://sherb.lin.irk.ru/phylogeny/paml.html
You can see the types of analyses these programs can do. No easy-to -read formulas, but an overview of the methods employed by that particular system.

​

As far as the amount of data, again, I am not sure what you mean - how mich of the genomes? If so, Itz is right that only a small percentage has been analyzed. However, taken as such, it can be somewhat misleading. For loci from many chromosomes, mitochondria, and even the entire single-copy genome (DNA-DNA hybridization) have been analyzed, and the story is basically the same. Just like one can get a feel for the mood of a nation of 265 million by surveying a couple thousand, one can get a picture of the evolution of a species with a genome of 3 billion by (effectively) randomly analyzing a few tens of thousands of nucleotides in that genome.[This message has been edited by SLPx, 03-12-2003]