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Author  Topic: Rebuttal To Creationists  "Since We Can't Directly Observe Evolution..."  
Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Kleinman:I get it now! Sexual reproduction works by gravity! I'm impressed by your understanding of the laws of physics. Kleinman:Tell us how you think adaptive alleles are evolved in sexually reproducing populations.


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes: Are some of the variants more fit than other variants and are they engaged in biological evolutionary competition? Beneficial mutations on separate genes would not be in competition with each other because they could merge into the same lineage.
You aren't answering my question about whether all 100,000 individuals are on the same evolutionary trajectory. Yes I am. Because genes move through the population this puts the population on the same trajectory. The only way this could not be the case is if there is an interruption in gene flow between subpopulations.
What is the probability of beneficial alleles in a diverse population recombining in the same descendant? Your father is homozygous for a beneficial mutation in gene A. Your mother is homozygous for a beneficial mutation in gene B. You have a 25% chance of getting both beneficial mutations. Do you understand this or not? Added in edit: The probability would actually be 100% if both parents were homozygous. The 25% chance is if both parents were heterozygous for their respective beneficial allele.
How do 20 million possible beneficial mutations end up in the lineages of all humans? Natural selection drives beneficial genes to fixation, and sexual recombination drives the merger of beneficial alleles into the same genome.
Try reading beyond the abstract: That is for asexual populations. Primates reproduce sexually.
OK, Haldane's frequency equation for a sexlinked diploid is: pn^2AA + 2pnqnAa + qn^2aa = 1 Which of the variants fix in the population, AA, Aa, or aa? That's for a single allele. What about different genes?
It's the number of replications of a particular allele that determines the probability of an adaptive mutation occurring at some site in that allele. In the Lederberg experiment the mutation rate was the same for all bacteria. Spectinomycin resistance occurred once in every 10 billion divisions and phage resistance occurred once in every 10 million divisions. How do you explain this?Edited by Taq, .


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Tell us how you think adaptive alleles are evolved in sexually reproducing populations. Let's use antibiotic resistance as our model. We have two populations of the same bacterial species. We put one population on a plate that has antibiotic A and another population on a plate with antibiotic B. We get resistant colonies on both plates. We then mix the two populations together in media that has no antibiotic. How many of those bacterial descendants of this mixed population are going to have both mutations for resistance to both drugs? None, if the bacteria are reproducing asexually. Do the same for a diploid sexually reproducing population. What are the results? Could you find bacterial descendants of the mixed population that has both resistance markers if they are found on different genes? YES!!


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Kleinman:So, in your model of human evolution, the fixation of beneficial alleles does not occur? Kleinman:In your model, does every human lineage have equal reproductive fitness? Do any human lineages go extinct? Kleinman:I don't think you are doing your math correctly on that one. But WRT your model, do all the fathers in your model have beneficial allele A and all the mothers have beneficial alleles B? Kleinman:How do you compute the probability that all these beneficial mutations end up in a single lineage in your model? Kleinman:Try reading this again: quote:How do you compute the rapid fixation of 20 million beneficial mutations in your model? Kleinman:You have yet to show how you do a fixation calculation for your model for a single genetic loci let alone 20 million genetic loci. Are you ever going to get beyond your simpleminded neutral evolutionary model where you assume that 20 million mutations are beneficial? Kleinman:Where did the resistance allele come from that the phage transmits? What if the phage transmitted some other allele besides a resistance allele? Kleinman:Just as a side note to this comment, Kishony's experiment doesn't work when using two drugs simultaneously. Do you understand why? And to your comment here, you have assumed that the two subsets of your sexually reproducing population each have fixed their respective resistance alleles so they exist at frequencies of 1 in their respective populations. If we assume both subsets have equal population sizes when you combine the frequencies of the resistance alleles for each drug will be 0.5. What happens if the resistance alleles are not at high frequency in the population? What is the probability of a recombination event for the beneficial alleles if their frequencies are f1, f2, and where the remaining members of the population have frequency f3, i.e., resistance to neither drug? And BTW, combination therapy works for the treatment of malaria which can do sexual reproduction. And the malaria population size for someone with hyperparasithemia can reach 1 trillion.


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes: So, in your model of human evolution, the fixation of beneficial alleles does not occur? Fixation of beneficial mutations does occur in my model. Why you think otherwise is beyond me.
In your model, does every human lineage have equal reproductive fitness? Do any human lineages go extinct?
There would be variation of fitness across individuals just like in any mammalian population.
Do any human lineages go extinct? The only lineages that actually exist are the ychromosome and mitochondrial lineages because those are haploid, and those can go extinct.
I don't think you are doing your math correctly on that one. But WRT your model, do all the fathers in your model have beneficial allele A and all the mothers have beneficial alleles B? The math was wrong. It should be 100% if the father and mother are homozygous. If a father is homozygous for a beneficial mutation in gene A and a mother is homozygous for a beneficial mutation in gene B, 100% of offspring will have one copy of each beneficial mutation. Do you agree or not?
How do you compute the probability that all these beneficial mutations end up in a single lineage in your model? If they are all being driven to fixation because of selection then that would be population wide for all of the beneficial mutations. If you are asking for the specific equations, those are found in population genetics: Population Genetics
How do you compute the rapid fixation of 20 million beneficial mutations in your model? Fixation wouldn't need to be rapid.
You have yet to show how you do a fixation calculation for your model for a single genetic loci let alone 20 million genetic loci. quote: The equations are all over the internet. It's not like it's a secret.
Where did the resistance allele come from that the phage transmits? What if the phage transmitted some other allele besides a resistance allele? Phage resistance doesn't come from the phage genome. It is due to mutations in the gene tonB. I will ask again. In the Lederberg experiment the mutation rate was the same for all bacteria. Spectinomycin resistance occurred once in every 10 billion divisions and phage resistance occurred once in every 10 million divisions. How do you explain this?
And to your comment here, you have assumed that the two subsets of your sexually reproducing population each have fixed their respective resistance alleles so they exist at frequencies of 1 in their respective populations. If they didn't have the resistance marker then they wouldn't have grown on the antibiotic plate. 100% of the bacteria on each plate carry the mutation for each antibiotic.
If we assume both subsets have equal population sizes when you combine the frequencies of the resistance alleles for each drug will be 0.5. Exactly. The two lineages have merged. Half the population has both mutations. If they are now challenged by both antibiotics half of the population will survive, and 100% will have both mutations in the same lineage, and it wouldn't have required iterative mutations.
quote: What would happen if one village used one drug and a village close by used a different drug? Could you have resistance to each drug develop in each village, and then find both resistance markers in the offspring between those two resistant populations? The answer is yes. The same mutations wouldn't have to repeat themselves in each population.


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Kleinman:The math is way beyond you. 20 million beneficial mutations * 300 generations/fixation = 6 billion generations Kleinman:How much variation? And how many different lineages in your population? Kleinman:So you are claiming that no human lineages have ever gone extinct? What happens to the less fit human lineages when the most fit are fixed in the population? Kleinman:That's still not quite right. What if both the mother and father are homozygous for gene A or homozygous for gene B? Kleinman:Percy likes it when you post from your link. Post the equation you think applies. Kleinman:Fixation isn't rapid and Haldane's mathematical estimate of 300 generations/fixation has been verified experimentally. And if you are concerned that Lenski's experiment uses asexual replicators, don't worry, Haldane's math includes that for diploid sexual replicators. 20 million beneficial mutations * 300 generations/fixation. How many generations are in your model? Kleinman:Plug in a selection coefficient and tell us how many generations to fixation. Then you only have 19,999,999 more fixations to go. Kleinman:So the resistance allele has to evolve in the bacteria and the phage acquires the gene and transmits it to drugsensitive bacteria. Are you claiming this is the mechanism that gives humans a reproductive advantage over chimps? Kleinman:It appears the selection coefficient is extremely high, all the drugsensitive variants are killed off in a single generation. Is that how your model for human evolution works? Kleinman:That's the problem, physicians have been taught for years an incorrect way of using antimicrobial agents and it has resulted in multidrugresistant microbes. Doctors have been taught to use antimicrobial agents as single drug therapy. When one drug fails, go onto the next, and the next, and the next,... Microbiologists need to do a better job teaching physicians how drug resistance evolves. Do you know any microbiologists that know how drug resistance evolves? Kleinman:The probability of that happening depends on the frequency of the different resistance alleles in the population. I'm still waiting for you to figure out that math. I'll even give you a couple of hints. It is the same math as a random card drawing problem except you only have 3 different kinds of cards in the deck. Call one card "A" for the first resistance allele, a second card "B" for the second resistance allele, and the third card "C" for members of the population that have neither the "A" nor "B" resistance alleles. Assume all the members of the population are homozygous at the respective genetic loci to make the math a bit easier and you have nA members in the population, nB members in the population, and nC members so that nA + nB + nC = n, the total population size. What's the probability of drawing an A and B parents to give an AB offspring?


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes: The math is way beyond you. 20 million beneficial mutations * 300 generations/fixation = 6 billion generations The neutral fixation rate in diploid organisms is essentially the mutation rate, which is 50 mutations per generation. Beneficial mutations would fix at a higher rate than neutral mutations.
How much variation? And how many different lineages in your population? Every time you ask for lineages in a sexually reproducing population you demonstrate you don't know what you are talking about.
So you are claiming that no human lineages have ever gone extinct? What happens to the less fit human lineages when the most fit are fixed in the population? I am saying that asking for lineages in a sexually reproducing population makes no sense because of the intermingling of alleles and mutations.
What happens to the less fit human lineages when the most fit are fixed in the population? If the most fit are fixed in the population then there is no less fit. They are all equally fit.
That's still not quite right. It is. Father is AAbb, mother is aaBB. All offspring will be AaBb. 100% of offspring will have the beneficial mutation for both gene A and gene B.
Fixation isn't rapid and Haldane's mathematical estimate of 300 generations/fixation has been verified experimentally. The difference is that in sexually reproducing species you can have more than one mutation moving towards fixation at a time. They are moving towards fixation in parallel.
Plug in a selection coefficient and tell us how many generations to fixation. You don't even understand how sexual reproduction works. Why don't you start there.
So the resistance allele has to evolve in the bacteria and the phage acquires the gene and transmits it to drugsensitive bacteria.
No. I am simply acting as if bacteria were suddenly diploid and sexually reproducing. Phage is not moving any genes around. In one population you get antibiotic resistance through mutation. In another you get phage resistance through mutation (not through any transport of DNA from phage). When you bring the two bacterial diploid sexually reproducing populations you get offspring with both antibiotic and phage resistance.
Do you know any microbiologists that know how drug resistance evolves? This microbiologist does understand it just fine.
The probability of that happening depends on the frequency of the different resistance alleles in the population. That's not what happens in the Lenski and Kishony experiments, is it?


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Kleinman:That is hilarious. Kleinman:Taq had no parents, he is a product of a population. Kleinman:All that intermingling of alleles and mutations and still they fix at a rate of greater than 50/generation. The Mexican Salamander has a genome length of 32 billion base pairs. Does that replicator fix 500 mutations/generation? Kleinman:That's fitting, the less fit aren't fit for life anymore. Kleinman:How did all the fathers end up AAbb and all the mothers aaBB? Kleinman:Do you think that Haldane was wrong when he wrote this: Haldane:Haldane posts data from sweet peas in his paper. Sweet peas do sexual replication. And do you have any experimental data that shows that fixation can occur more rapidly in sexual replicators than in asexual replicators? Kleinman:Taq, I've taken multiple biology courses and even 2 years of microbiology. I know how meiosis works. So show us how you use the equations you posted to compute the number of generations to fixation for a single allele. Kleinman:Why should it surprise you when a scientist puts an agent into a population that transfers a resistance allele? This is simply a breeding program with a phage with a known allele and a population of bacteria. Are you claiming that the human reproductive advantage came about due to breeding? Kleinman:Tell us how the Kishony experiment works. And show your math. Kleinman:You still haven't figured out the difference between DNA evolution, biological evolutionary competition, and recombination. Don't worry, I'll be patient with you till you get it.


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Further response to Percy's Message 175
Percy, I tried to write the matrix equations using Latex. They appear correctly in the Latex editor I used but don't appear correctly here. Picking up the discussion on computing the probability of a particular mutation occurring using a Markov Process
Kleinman:OK. First, for those readers that don't know what a Markov Chain is, here's a definition from Wikipedia: Markov chain  Wikipedia quote:The first application of a Markov Chain model to DNA evolution was done by Jukes and Cantor and is called the JukesCantor model. The way one does such a calculation is first to draw a state transition diagram of the system of interest. The state transition diagram for a single site in a genome looks as follows: Then, a transition matrix can be written to describe the evolutionary change in time t is = (pij) where the pij gives the probabilities of change from the state Ei to Ej at time t + Δt where Δt is a replication. If we neglect insertions, deletions, transpositions, and other types of mutations (that is substitutions only), the transition matrix would look as follows: P (t)=( pAA pAC pAG pATpCA pCC pCG pCT pGA pGC pGG pGT pTA pTC pTG pTT ) \left[ {\begin{array} p_{AA} & p_{AC} & p_{AG} & p_{AT}\\ p_{CA} & p_{CC} & p_{CG} & p_{CT}\\ p_{GA} & p_{GC} & p_{GG} & p_{GT}\\ p_{TA} & p_{TC} & p_{TG} & p_{TT}\\ \end{array} } \right \][/latex]> If one assumes that the mutation rates are constant and have the same value for DNA transitions and transversion, we obtain the JukesCantor model. P (t)=[1−μ μ/3 μ/3 μ/3μ/3 1−μ μ/3 μ/3 μ/3 μ/3 1−μ μ/3 μ/3 μ/3 μ/3 1−μ] \left[ {\begin{array}{cccc} 1−μ & μ/3 & μ/3 & μ/3\\ μ/3 & 1−μ & μ/3 & μ/3\\ μ/3 & μ/3 & 1−μ & μ/3\\ μ/3 & μ/3 & μ/3 & 1−μ\\ \end{array} } \right] [/latex]> The JukesCantor model implicitly assumes a population of one. If one wants to compute the frequency distribution of different variants as a population grows "N", it is done as follows: P (t)=[1−μ/N μ/(3∗N) μ/(3∗N) μ/(3∗N)μ/(3∗N) 1−μ/N μ/(3∗N) μ/(3∗N) μ/(3∗N) μ/(3∗N) 1−μ/N μ/(3∗N) μ/(3∗N) μ/(3∗N) μ/(3∗N) 1−μ/N)] \left[ {\begin{array}{cccc} 1−μ/N & μ/(3∗N) & μ/(3∗N) & μ/(3∗N)\\ μ/(3∗N) & 1−μ/N & μ/(3∗N) & μ/(3∗N)\\ μ/(3∗N) & μ/(3∗N) & 1−μ/N & μ/(3∗N)\\ μ/(3∗N) & μ/(3∗N) & μ/(3∗N) & 1−μ/N\\ \end{array} } \right] [/latex]> The initial state of the system is written: E0 = (A0, C0, G0, T0) and the state of the system a time ti is: Ei = (Ai, Ci, Gi, Ti) and the state of the system going from state Ei to state Ei+1 is computed by simple matrix multiplication. Ei+1 = Ei [P] For the JukesCantor model one obtains the equations: Ai+1 = Ai(1μ) + Ci*μ/3 + Gi*μ/3 + Ti*μ/3Ci+1 = Ai*μ/3 + Ci(1μ) + Gi*μ/3 + Ti*μ/3 Gi+1 = Ai*μ/3 + Ci*μ/3 + Gi(1μ) + Ti*μ/3 Ti+1 = Ai*μ/3 + Ci*μ/3 + Gi*μ/3 + Ti(1μ) And for the variable population model: Ai+1 = Ai(1μ/N) + Ci*μ/(3*N)+ Gi*μ/(3*N) + Ti*μ/(3*N)Ci+1 = Ai*μ/(3*N) + Ci(1μ/N) + Gi* μ/(3*N)+ Ti*μ/(3*N) Gi+1 = Ai*μ/(3*N) + Ci*μ/(3*N) + Gi(1μ/N) + Ti*μ/(3*N) Ti+1 = Ai*μ/(3*N) + Ci*μ/(3*N) + Gi*μ/(3*N) + Ti(1μ/N) Note that A,C,G, and T are frequencies of the particular variants with that particular base at that site. If you multiply any of these frequencies by N, you will get the number of members in the population with that given base at that site. Then, assume that in the initial condition that the base at that site is T but the beneficial mutation is A. The initial condition is written: E0 = (A0, C0, G0, T0) = (0,0,0,1) And do lots of matrix multiplications. For the JukesCantor model and mutation rate 1e9, one obtains the following frequency curves:
For the variable population transition model and mutation rate 1e9, one obtains the following frequency curves:
And for comparison, the probability curves for the "at least one" calculation for a beneficial mutation to occur as a function of population size:
Comparing these 3 graphs shows that the JukesCantor model reaches equilibrium at about 3e9 replications. The variable population size model gets an expected number of A variants equal to 1 at about 1.5e8 and the "at least one" calculation for mutation rate 1e9 gives a rapidly rising probability at about 1.5e8.
Percy:That's right, but ultimately, I think resources are just individual components of the environment that make the energy in the environment available to the replicator. For example, plants need water to convert the energy from the sun to produce sugar. That's why drought and dehydration is a selection pressure. So tell me Percy, is the physics and math that I've presented get us into the ballpark on how biological evolution works?


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes:
That is hilarious.
You think this is hilarious?
quote: All that intermingling of alleles and mutations and still they fix at a rate of greater than 50/generation.
Generation 1 there are 5 beneficial mutations that occur in the population and they fix at generation 51. In generation 2 there are another 5 beneficial mutations, and they fix at generation 52. In generation 3 there are another 5 beneficial mutations and they fix at generation 53. See a pattern here?
That's fitting, the less fit aren't fit for life anymore. I see you are just blabbering now.
How did all the fathers end up AAbb and all the mothers aaBB? Why would all the fathers need to be AAbb in order for at least one father to be AAbb? Same for mothers.
Do you think that Haldane was wrong when he wrote this: Generation 1 there are 5 beneficial mutations, and in generation 301 they are fixed. In generation 2 there are 5 beneficial mutations, and in generation 302 they are fixed. See a pattern?
Why should it surprise you when a scientist puts an agent into a population that transfers a resistance allele? Phage do not transfer phage resistance in the Lederberg experiment. The phage in the experiment binds to the gene product of tonB. Mutations in the tonB gene prevent phage from binding to the bacteria. I will ask again. Why does spectinomycin resistance occur once every 10 billion replications in E. coli and phage resistance occurs once every 10 million replications? Why is there a 1,000 fold difference?
Tell us how the Kishony experiment works. Read the Kishony experiment. What you fail to understand is that the Kishony experiment is largely irrelevant to how humans evolved.
You still haven't figured out the difference between DNA evolution, biological evolutionary competition, and recombination. I'm not the one who hasn't figured it out.


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Taq:It appears that in your microbiology training, none of your instructors taught you what a mutation rate is. If you are able, prepare yourself to be instructed. Mutation rate  Wikipedia quote:And that rate estimated for humans is: quote:The mutation rate is not the ridiculous claim of 50 mutations per generation that you made in your post. You need to put more effort into understanding the equations you use and how you define the variables in these equations. Now put the correct values in your equation and tell us how many generations to fixation for each mutation and then understand why 20,000,000 adaptive mutations are not going to fix in your model.


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes: And that rate estimated for humans is:
quote:The mutation rate is not the ridiculous claim of 50 mutations per generation that you made in your post. You need to put more effort into understanding the equations you use and how you define the variables in these equations. Now put the correct values in your equation and tell us how many generations to fixation for each mutation and then understand why 20,000,000 adaptive mutations are not going to fix in your model. 1.1x108 per site per generation. Let's see how that works out. That is a mutation every 110 million bases. There are 6 billion bases in the human diploid genome. (6E9)/(1.1E8) = 54.5 mutations per person per generation. On top of that, we have directly sequenced the genomes of parents and offspring to directly measure the number of mutations per person, and that is where the figure you cite comes from. The directly measured human mutation rate is around 50 mutations per person. Do you also agree that the neutral fixation rate is approximately the mutation rate, meaning that for a mutation rate of around 50 mutations per person per generation that we will see 50 neutral mutations fixed per generation? Added in edit: Figure 2 from this paper which directly measured mutations between parents and offspring. The Y axis is the number of mutations per birth, and the x axis is the father's age at conception. As you can see, many of the mutations come from the father due to continual division of germ line cells (i.e. sperm).
Edited by Taq, .


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Taq:The correct value to use in your equation is 1.1x108, not 50. Your value is off by about 9 orders of magnitude. There are many reasons why the number you are trying to use is wrong but one of the biggest is that nowhere in your equation is the genome length a variable. That's why I brought up the Mexican Salamander example because its genome is 10x larger than the human genome. That doesn't make the number of fixations 10x larger, 500 in every generation! For neutral evolution, it will take 1/(1.1x108) or about 90 million generations for each neutral fixation. Haldane's fixation rate of 1 fixation for every 300 generations under selection is much more generous. How you could imagine that every member of a population ends up with the same 50 neutral (or any) mutations every generation is a mystery.


Taq Member Posts: 10158 Joined: Member Rating: 4.7 
Kleinman writes:
The correct value to use in your equation is 1.1x108, not 50.
1.1x108 per nucleotide per generation is the same as 54.5 mutations per person per generation for a 6 billion base diploid genome. Moreover, we can count the mutations by comparing the genomes of parents and their offspring. That number is about 50, on average. Check out this paper: Rate of de novo mutations, father’s age, and disease risk  PMCEdited by Taq, . Edited by Taq, . Edited by Taq, .


Kleinman Member (Idle past 415 days) Posts: 2142 From: United States Joined: 
Kleinman:And 54.5 is not the correct value to use in your equation. Just because the number of mutations that occur in a replication is 54.5 doesn't mean that all 54.5 are fixed. The correct value to use in your equation is 1.1x108.



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