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Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
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Author | Topic: NvC-1: What is the premise of Naturalism in Biology? | |||||||||||||||||||||||||||||||||||||||
Taq Member Posts: 10295 Joined: Member Rating: 7.4 |
RLW writes: I did not say that. What I pointed out is Translocation or Transposition is non-random mutation. Then you are saying that translocation and transposition can only ever be beneficial and can never be neutral or deleterious. That's what non-random mutation means. You need to explain how the mechanisms that cause translocation and transposition know to only cause beneficial mutations.
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Taq Member Posts: 10295 Joined: Member Rating: 7.4 |
RLW writes: What are the EXPERIMENTAL evidences? The experimental evidences are in posts 367 and 395.
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Richard L. Wang Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
For the English words with two letters, there are total 26x26=676 different combinations and there are 21 English words with two letters (am, an, as, at, be, by, do, go, he, hi, if, in, is, it, me, my, no, ok, so, us, we). Therefore, start from a two-letter-sequence and change it by point-substitution-mutation, on average it will take 32.2(= 676 / 21) steps to make a new English word with two letters.
Most of the genes are relatively small covering a genomic region of about 3 kb, see Overview of gene structure
. Consider a nucleotide sequence with 1000 bases and estimate how long will it take to produce a new gene by point-substitution-mutation. The 1000-base-sequence contains a total of 4^1000 = 1.15x10^602 or 10^602 different base-sequences. Here and below, all approximations will speed up the evolution. The total number of protein-coding genes (the Earth's proteome) is estimated to be 5 million sequences, see Just a moment... Therefore, on average, it will take 10^602 / 5x10^6 = 2x10^595 or 10^595 point-substitution-mutations to produce a new protein-coding gene. Point-mutations are errors in the process of DNA replication during cell division and reproduction. For E. coli, it takes about 20 minutes to reproduce a new generation, and its DNA duplicates with remarkable precision: less than one error per one billion (10^9) new nucleotides incorporated. If we use Taq(Message 367) data of point substitution rates:Transition at non-CpG 6.1810^‘9 Transition at CpG 1.1210^‘7 Transversion at non-CpG 3.7610^‘9 Transversion at CpG 9.5910^‘9 Take the rate = 10^-8 for convenience. For per 20 minutes, one replication takes place, for 1 year, 2.6x10^4(=365x24x60 / 20) time replications occur. For the 1000-base-sequence, 0.26 (= 1000 x 10^-8 x 2.6x10^4) point-substitution-mutation, or approximates to 1 point-substitution-mutation occurs per year. Therefore, in order for 1000-base-sequence to produce a protein-coding gene, it needs 10^595 point-substitution-mutations, which will take 10^595 years! Consider that life on Earth emerged about 4.5 billion or 4.5x10^9 years ago, 10^595 years is such a long period of time beyond imagination. RLW(Message 403) provides an example of how genetic novelty is generated through cellular genetic engineering — cells edit their own genome. Taq & AZPaul3, there is no evidence for point mutations to produce genetic novelty in the history of biological evolution.
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Richard L. Wang Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
What the randomness you understand is very specially defined by Neo-Darwinists that mutations occur randomly with respect to whether their effects are useful.
Please check the definition of random processes, and then you may know that the Neo-Darwinists’ definition of randomness is completely wrong.
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Taq Member Posts: 10295 Joined: Member Rating: 7.4
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RLW writes: What the randomness you understand is very specially defined by Neo-Darwinists that mutations occur randomly with respect to whether their effects are useful. When we say mutations are random, that is the randomness we are talking about. If you want to debate evolution and natural processes, then those are the concepts you are arguing against.
Please check the definition of random processes, and then you may know that the Neo-Darwinists’ definition of randomness is completely wrong. The map is not the territory. Definitions should reflect how the words are used, and in biology that is the usage of the word random. More to the point, you use the same definition all of the time. Is the lottery random? If your answer is yes, then you are using the same definition as biologists are using. The tickets are not bought at random places, but at specific places. The range of numbers are not completely random numbers, but are restricted to a set range. The drawings do not happen at random times, but at set times each week. The only thing that is random is that the process that picks the numbers is blind to the tickets being held by the players. You would use the same definition in the game of craps. There is a much higher chance of rolling a 7 than there is a 2 or 12. However, the game is still random because the dice aren't affected by the placement of chips on the table.
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Richard L. Wang Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
Let us use the simplest example of rolling dice to explain how to describe random process in mathematics. Roll a dice and look at the number on the up side. One does not know in advance what number will appear, so this is a random process. For this random process, what characteristics do we need to describe? Each rolling will generate a number on the up side, which can take 1, 2, 3, 4, 5 and 6. While one does not know in advance what number on the up side is after the rolling, one does know that if the dice is made very uniformly, the chance for each number to show on the up side is equal.
Let us describe this random process of rolling dice in mathematics. We assign a random variable x to represent the number shown on the up side after rolling. This random variable can take the following values: x = 1, 2, 3, 4, 5, and 6, and in the case of that the dice is made very uniformly, the probability of each number showing on the up side is equal: P(1) = P(2) = P(3) = P(4) = P(5) = P(6) = 1/6. Note that the sum of all possible probabilities is equal to 1 or 100%, which means that after rolling the number shown on the up side must be one of the following six numbers: 1, 2, 3, 4, 5 and 6. Now, consider the point mutation of a DNA molecule consisting of 10,000 nucleotides. If a point mutation occurs, what are the uncertainties of this event? 1) Where does the point mutation occur in the DNA molecule? 2) What kind of point mutation is this mutation, substitution, insertion or deletion? 3) If it is a point substitution mutation, what base replaces the original base? 4) If it is a point insertion mutation, what base is inserted into the DNA molecule? Therefore, to describe this random process, we need four random variables. As shown in the example of rolling dice, for each random variable, we must determine three characteristics: what kind of random process it describes, what are all possible outcomes of the random variable, and the probability that the random variable takes each possible outcome. For simplicity, we assume that the probabilities of a random variable taking all possible values is equal. Random Variable 1: w describes the base number, where the point mutation occurs, w = 1, 2, , 10000, and P(w) = 0.0001, where w = 1, 2, , 10000; Random Variable 2: x describes what kind of point mutation occurs, x = substitution / insertion / deletion, and P(substitution) = P(insertion) = P(deletion) = 1/3; Random Variable 3: y describes what base is used to replace the originating base when a point substitution mutation occurs. If the original base on the w site nucleotide is A, then y = G or C or T, and P(G) = P(C) = P(T) = 1/3. If the original base on the w site nucleotide is G or C or T, the values of the random variable y and the probabilities P(y) can be obtained similarly; Random Variable 4: z describes what base is inserted between the w-site nucleotide and the (w+1)-site nucleotide when a point insertion mutation occurs. z = A or G or C or T, and P(A) = P(G) = P(C) = P(T) = 1/4. The distribution of a random variable is not necessarily uniform. For human being, the probabilities of a base taking the values A, G, C and T are equal to 0.293, 0.207, 0.200 and 0.300, respectively; therefore, for more precise cases, we can set P(A) = 0.293, P(G) = 0.207, P(C) = 0.200, and P(T) = 0.300, respectively (Bansal M., 2003. DNA structure: Revisiting the Watson-Crick double helix. Current Science. 85 (11): 1556—1563.) In summary, if a point mutation occurs during DNA replication, in order to accurately determine the point mutation, we must know where the point mutation occurs and what kind of mutation is: substitution or insertion or deletion. If it is a substitution, we have to know what base substitutes the originate base; if it is an insertion, we have to know what base is inserted. Obviously, point mutation is a random process and it happens naturally. Taq, can you describe transposition mutation to be a random process by the above method?
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Taq Member Posts: 10295 Joined: Member Rating: 7.4 |
RLW writes: Let us use the simplest example of rolling dice to explain how to describe random process in mathematics. Roll a dice and look at the number on the up side. One does not know in advance what number will appear, so this is a random process. In the same way, before a child is born you can not predict which mutations they will have.
Taq, can you describe transposition mutation to be a random process by the above method? Can you show us how to predict where a transposon will insert? I have personally done random transposon mutagenesis experiments in bacteria, and the result was insertions all over the bacterial genome. There were short sequences that the transposon preferred to insert into, but those potential insertion sites are spread throughout the genome and there is no way to determine which site will be used for a specific insertion.
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Richard L. Wang Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
You have performed random transposon mutagenesis experiments in bacteria, which must be very interesting.
From the point of view of molecular mechanics — bond broking and binding -, transposon insertion should be similar to point insertion, that is, each site on the genome should be approximately the same. In fact, they are different. The first step of the generation of anti-freezing gene AFGP in RLW(Message 403): Duplication - make a copy of trypsinogen. Because the original gene is still valid, fish can live normally in the process of creating a new gene. In order for fish to live normally in the process of creating a new gene, the inserted copy of trypsinogen must not damage the original genome. Although insertion sites can be spread all over the genome, they cannot be any site on the genome. The choice of insertion site of the trypsinogen’s copy is controlled by the condition that it cannot damage the original genome. Therefore, this is not a random process. The third step of the generation of anti-freezing gene AFGP in RLW(Message 403): Duplication — copy the mutated segment of the original gene over and over again for forty-one times. Coping Abc on the already existing sequence AbcAbc will result in the sequence AbcAbcAbc. Obviously, it is not random. Random insertion of Abc will produce the sequence AbcAAbcbc, AbcAbAbcc, , that is not a copy. Returning back to the randomness defined by Neo-Darwinists that mutations occur randomly with respect to whether their effects are useful. In the third step, coping the mutated segment may be beneficial, neutral or deleterious, so according to Neo-Darwinian definition, coping a mutated segment is a random mutation. There are two related and different things: coping, and the effect of coping. Coping a mutated segment may be beneficial, neutral or deleterious, which means the effect of coping is uncertain, so the correct statement should be that the effect of coping is random, but the coping itself is non-random. The question is why Neo-Darwinists insist that coping is random, because the effect of coping is uncertain?
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AZPaul3 Member Posts: 8654 From: Phoenix Joined: Member Rating: 7.0 |
Although insertion sites can be spread all over the genome, they cannot be any site on the genome. The choice of insertion site of the trypsinogen’s copy is controlled by the condition that it cannot damage the original genome. Therefore, this is not a random process. Of course the insertion site can be anywhere in the genome. It is *not* limited to only specific sites where "it cannot damage the original genome." If the insertion damages the genome then most probably the fish doesn't live to breed. We're not talking "random in respect to benefit" but "random in respect to fitness". Gene duplication and insertion, regardless of where the duplicate ends up, is random. Same with massive codon copy repetition. This mutation is known to happen all over the genome, is involved in some breast cancers, and some highly repetitive intergenic regions. A mutation of a small stretch of 40+- repeated codons in some section of a gene is not unknown. Do to the mechanism that creates the repeat it could go on for dozens, even hundreds, of nucleotides and is one random mutation in total. The nucleotide sequence may be highly repetitive but is due to a single random repetitive insertion error. You still cannot show any non-random genetic mutation. Factio Republicana delenda est.
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Tanypteryx Member Posts: 4597 From: Oregon, USA Joined: Member Rating: 10.0 |
You still cannot show any non-random genetic mutation. This got me wondering, are retro-viral insertions considered to be mutations? And are their insertion points random? Also, are genetic modifications using tools like CRISPR considered mutations, and are they random or specific as far insertion point? I know this is completely unrelated to the mutations you are talking to Wang about, but I just wondered what your thoughts are?What if Eleanor Roosevelt had wings? -- Monty Python One important characteristic of a theory is that is has survived repeated attempts to falsify it. Contrary to your understanding, all available evidence confirms it. --Subbie If evolution is shown to be false, it will be at the hands of things that are true, not made up. --percy The reason that we have the scientific method is because common sense isn't reliable. -- Taq
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AZPaul3 Member Posts: 8654 From: Phoenix Joined: Member Rating: 7.0 |
This got me wondering, are retro-viral insertions considered to be mutations? And are their insertion points random? Viral insertions are mutations since the genome changed. And they are random as far as I can tell. I don't know of any mechanism that would make those insertions non-random. As far as I know a virus does not intend to leave anything behind. The host cell is supposed to lyse spilling its content. HIV and some of the herpes viruses do incorporate their DNAs into the host and lay dormant for a bit. Eventually the cell kicks off a campaign of virus making then lyses. I imagine an insertion is caused by some error in the process. CRISPER induced mutations are not random since the lab, if they have their stuff together, have specific target sites in mind for CRISPER to modify. However, recent studies seem to indicate that CRISPER may introduce unintended changes in areas around the target. CRISPR gene editing in human embryos wreaks chromosomal mayhem. Not a good thing. Edited by AZPaul3, : No reason given. Edited by AZPaul3, : No reason given.Factio Republicana delenda est.
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Tanypteryx Member Posts: 4597 From: Oregon, USA Joined: Member Rating: 10.0 |
Thanks!
What if Eleanor Roosevelt had wings? -- Monty Python One important characteristic of a theory is that is has survived repeated attempts to falsify it. Contrary to your understanding, all available evidence confirms it. --Subbie If evolution is shown to be false, it will be at the hands of things that are true, not made up. --percy The reason that we have the scientific method is because common sense isn't reliable. -- Taq
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Richard L. Wang Member (Idle past 1594 days) Posts: 104 From: Ottawa, ON, Canada Joined: |
Your reply is not long, but contains many new ideas:
- Gene duplication and insertion, regardless of where the duplicate ends up, is random - The nucleotide sequence may be highly repetitive but is due to a single random repetitive insertion error. Don’t you think your ideas are more convincing than the Neo-Darwinian concept of mutation randomness? Why don’t you argue the concept of mutation randomness with Neo-Darwinists, so as to replace the Neo-Darwinian concept of mutation randomness with yours? Unfortunately, your ideas are theoretically wrong, and you don’t know how to demonstrate your concepts theoretically. And your assertion that Of course the insertion site can be anywhere in the genome. It is *not* limited to only specific sites where "it cannot damage the original genome." If the insertion damages the genome then most probably the fish doesn't live to breed is not supported by evidence of molecular biology. What is the most important thing in science? The first one is evidence, the second one is evidence, and the third one is still evidence. Random is a very simple and popular concept in mathematics and physics. A random process simply means that the output or result is uncertain. There are no random in respect to benefit" or "random in respect to fitness", there is only random in respect to output. As pointed out in RLW(Message 413) that There are two related and different things: coping, and the effect of coping. Coping a mutated segment may be beneficial, neutral or deleterious, which means the effect of coping is uncertain, so the correct statement should be that the effect of coping is random, but the coping itself is non-random. The question is why Neo-Darwinists insist that coping is random, because the effect of coping is random? This is why I call Darwinian-Naturalism pseudoscience. Neo-Darwinists deceived society for decades by taking the effect of copying is random as their reason for claiming that coping is random.
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Taq Member Posts: 10295 Joined: Member Rating: 7.4 |
RLW writes: From the point of view of molecular mechanics — bond broking and binding -, transposon insertion should be similar to point insertion, that is, each site on the genome should be approximately the same. In fact, they are different. That's like saying the lottery is not random because the drawing happens at predictable times. There are short sequences that transposons like to insert into, but those short sequences are found throughout the genome and the transposon will insert randomly among them.
The choice of insertion site of the trypsinogen’s copy is controlled by the condition that it cannot damage the original genome. That's false. Transposons can insert into genes and knock them out. In fact, that is exactly what I used transposons for in the lab. I screened thousands of clones to find the one that lacked the activity I was focused on. This told me the trasposon had inserted into the gene responsible for the activity I was interested in. There is nothing stopping transposons from inserting into functional DNA and doing away with that function. Nothing.
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Taq Member Posts: 10295 Joined: Member Rating: 7.4 |
Tanypteryx writes: This got me wondering, are retro-viral insertions considered to be mutations? And are their insertion points random? Any change in the base sequence of a stretch of DNA is a mutation, so retroviral insertions would most definitely be a mutation. Their insertion points are also random with respect to fitness since they can be neutral, beneficial, or deleterious. Certain viruses do prefer different motifs, such as AT repeats or transcriptional units, but when biologists mean random they mean random with respect to fitness.
Also, are genetic modifications using tools like CRISPR considered mutations, and are they random or specific as far insertion point? CRISPR/Cas9 would be the big exception. Those are mutations and they are non-random. This would be a case of purposefully changing DNA to get a specific beneficial outcome. As a general rule, if mutations were non-random with respect to fitness then (at the most extreme) we would expect to see the same beneficial mutation suddenly appear in every new offspring when exposed to the same environmental challenge. For example, we would expect all bacteria to get the same mutation for antibiotic resistance right after being exposed to antibiotics. Instead, it is only about 1 in 200 million bacteria that get the needed mutation (for select antibiotics), and this happens whether or not they have been exposed to antibiotics.
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