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Natural Selection vs Artificial Selection

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gent-selecting-a-suit-1514073Stimulated by the nth discussion with Zachriel on this point, I would like to offer here some thoughts about the difference between Natural Selection and Artificial Selection.

First of all, the dramatic limitation of NS is the following: it works on one functional specification, and one functional specification only: reproductive advantage.

In a sense, that specification is the byproduct of the system: biological beings that reproduce, that use limited resources to do that, and that compete for those resources. So, NS is a selection made possible by the existence of a complex functional system, and it selects for improvement in a function critically predefined in that system: reproductive success. So, it is a byproduct of the functional complexity already existing in the system.

Now, the functional specification: “reproductive success” is rather generic. It can certainly include many sub-functions. That’s the point that neo-darwinists stress. They say: OK, NS can select only for reproductive success, but reproductive success can include any function, and everything which goes in that sense can be selected.

Well, this is a false reasoning, which takes into no account the nature of complex information. The simple fact is: the search engine to which NS can be applied is random variation, and only random variation (I exclude for the moment possible algorithmic adaptation mechanisms). So, NS works on variation that is random, and not purposeful. Can that mechanism build complex functional information?

The simple answer is: no. Simple functional variation can certainly be generated by random variation, and therefore selected by NS. Why? because a few bits of variation are in a search space small enough to be explored, even many times, by biological RV. Those rare instances where the variation can give an advantage, with a bit of luck, can certainly be selected. That is the case of simple forms of antibiotic resistance. We can call those cases “molecular microevolution”. The few examples we have of that are the only empirical examples of NS at work in biology.

But what about some function which can give reproductive advantage, but which appears only if at least, say, 500 bits of specific information are found?

Such a result is definitely beyond any resource of RV. Therefore, it will never be achieved, and therefore never be selected.

Neo-darwinists, like Zachriel, argue that gradual pathways exist that will build those 500 bits of specific information in small steps. That is simply a fairy tale, existing only in their imagination. Information does not work that way. If I need 100 specific aminoacids to make something work (a case very common), then there is obviously no pathway which goes to that sequence step by step. Why? Because those 100 AAs are specific to the function. Fragments of the sequence have no special meaning and function, unless the complete sequence is achieved.

 

What about AS? Let’s take the case of the ATP binding protein, quoted by Zachriel (IOWs the Szostak paper).

This is AS, as many times argued by me here. The designer starts by conceiving and defining a function: “I want a protein which can effectively bind ATP”. That is the functional specification, and it is a form conceived in the consciousness of the designer.

As anyone can see, the function is very different from the single function available to NS: reproductive success.

Then, the designer uses his cognitive understanding of protein biochemistry and lab techniques to devise a strategy to implement his goal.

First of all, he sets a system that measures and extracts those molecules which bind ATP.

This point is very important, and it shows one of the main reasons why AS is so effective, while NS is not.

AS can measure the function defined by the designer at any desired level of sensitivity. Instead, NS has a definite threshold, under which no selection happens: reproductive success must be present, and enough of it to ensure the fixation of the trait.

That means that our designer, if interested in ATP binding, can select molecules which bind ATP with any level of affinity. There may be practical limitations due to the technology used, bu in principle any level of binding can be detected.

The reason is simple:

1) In NS, the coupling between the new function and the selection is direct: it is due to the reproductive success conferred by the function itself.

2) In AS, the coupling between the new function and the selection is indirect and symbolic: it’s the designer of the procedure who connects two events completely unrelated, for example ATP binding and the selection and expansion process. (UB, are you there?  🙂 )

In our example of ATP binding, then the designer chooses to use some form of artificial RV (in that case, mutagenic PCR), and to apply it in rounds coupled to artificial selection again and again.

The results are powerful: he obtains, in a short time, a protein with strong affinity for ATP.

The important point is: while that protein satisfies well enough the functional definition for which it was artificially selected (ATP binding), in no way it confers a reproductive advantage. So, even at the end of the artificial selection procedure, still the protein is not in the range of NS.

So, to sum up, the main differences between NS and AS are:

1) AS can define any function, and select for it. NS works only on one function: reproductive success.

2) In NS, the coupling between function and selection is direct: it’s the function itself which confers the reproductive advantage, which is the reason for the selection itself. In AS, the coupling between the defined function and the selection process is indirect and symbolic: the connection is established by the designer, by definite procedures designed by him.

3) NS has a definite threshold of measurement: it can only act if enough reproductive success is present as to ensure the fixation of the trait. AS can measure and select any desired level of the defined function.

4) In NS, the only selecting procedure is tied to the reproductive success, and is in essence differential reproduction. In AS, any intelligent procedure can be used to isolate, expand and fix the desired function.

 

Comments
gpuccio: And let me know if and when somebody tests recombination in a similar context. There are a plethora of papers on recombination. For a review, see Long et al., The origin of new genes: glimpses from the young and old, Nature Reviews 2003. For something more specific, try Gomez, Creating New Genes by Plasmid Recombination in Escherichia coli and Bacillus subtilis, Applied and Environmental Microbiology 2005. Of course, the importance of recombination for exploring rugged landscapes is easily demonstrable with evolutionary algorithms, or even with simple abstractions.Zachriel
December 10, 2015
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Zachriel: OK, so we agree that "how much complex a structure is" is an important point. Which is a central concept in ID. And let me know if and when somebody tests recombination in a similar context.gpuccio
December 10, 2015
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gpuccio: But the point is: how complex? A complex three-dimensional structure, but not as highly specified as the native form. gpuccio: But the level of function provided by the wildtype sequence has much higher complexity, so much so that huge combinatorial resources are needed to find it (a 10^70 sequence library). They didn't test recombination, and there are reasons to expect — as the author's pointed out — that recombination would result in much higher specificity.Zachriel
December 10, 2015
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Still going on about that Mungy? And still finding ways to be wrong. I doubted the existence of a peptidyl transferase enzyme that "adds amino acids to a growing strand," and which isn't called "the ribosome." And I still doubt it, because you are yet to come up with an enzyme that fits these requirements. There is only one thing that fits these requirements and it is "the ribosome," which is technically not an enzyme, it is a ribozyme. When will you learn? Let me know when someone (like EA) comes up with something about my response to "EA's challenge."Alicia Cartelli
December 10, 2015
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Pucci, you’re still confusing “conserved amino acids” with “amino acids that are required for function,” though. I'll start doubting him when he denies the existence of the peptidyl transferase center.Mung
December 10, 2015
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gpuccio @80 Apparently your interlocutors don't understand the basic concept of complex complexity. :)Dionisio
December 10, 2015
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Pucci, you're still confusing "conserved amino acids" with "amino acids that are required for function," though. =)Alicia Cartelli
December 10, 2015
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Zachriel: Again, I will not repeat what has already been said. I want to comment on your last statement, because I believe you are definitely wrong (or at least vague). You say: "Even point mutation resulted in a complex functional sequence." OK, if we define retrieval of infectivity, then certainly the use of random libraries of growing number + RV and NS did result in one or more functional sequences. But the point is: how complex? What the study shows, very clearly IMO, is that low levels of function retrival have some complexity, but not a very high complexity. Indeed, they are easily found by the system exactly for that reason: because the target space is big enough that it can be found by the system. IOWs, gross function, at a very low level, has less functional complexity. But the level of function provided by the wildtype sequence has much higher complexity, so much so that huge combinatorial resources are needed to find it (a 10^70 sequence library). You should know that in ID we quantify functional (specified) information. That a sequence with low dFSCI can be found by a highly efficient RV + NS system like the phage system is simply what we can expect. What cannot be found by such a system is a sequence with very high dFSCI, beyong a threshold which makes the probabilistic resources of a natural system completely powerless. The wildtype sequence seems to be in that range, if the authors are right in their conclusions. After all, they anticipate about 35 AA substitutions to get to it, and, if true, that would be a functional complexity of the order of magnitude of 150 bits, enough to frustrate any natural system. And yet, that would still be much less than what we observe in a lot of functional proteins, like the many times quoted alpha and beta subunits of ATP synthase and histone H3.And many others. Those examples are definitely beyond any cosmic natural system. So, remember, ID is a quantitative theory. Affirming that "a complex functional sequence" has been found is vague. You have to try to evaluate the functional complexity.gpuccio
December 10, 2015
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gpuccio: The wildtype of our discussion is an isolated sequence, which has not been found and cannot be reasonably found by mutation and NS. That's your claim. gpuccio: You think that recombination with unknown genes, which have nothing to do at sequence level with the wildtype itself, should help, That is incorrect. In the particular case, homologous recombination would probably be sufficient. What the study showed was that the landscape has a huge number of local peaks, so that simple mutation starting from random sequences can only explore a small portion of the landscape. gpuccio: but you have given no reason to believe that. 1. Population genetics shows the importance of recombination. 2. Evolutionary algorithms show the importance of recombination. 3. Empirical evidence shows that importance of recombination in organisms as varied as viruses and humans. 4. A simple example was provided to show how recombination can overcome local peaks. gpuccio: The simple reason why the wildtype, the true optimal peak, cannot be found is because it is too small and isolated, and the random search is not powerful enough to find it. It's probably not isolated in the multi-dimensional recombination space. We don't know, because the study didn't include recombination, but we do know that recombination works like this in other cases. gpuccio: The point is, and always has been: is recombination an important mechanism in the random search for complex functional sequences? Even point mutation resulted in a complex functional sequence.Zachriel
December 9, 2015
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gpuccio @74, 75, 77 Very insightful comments.Dionisio
December 8, 2015
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Zachriel: The wildtype of our discussion is an isolated sequence, which has not been found and cannot be reasonably found by mutation and NS. You think that recombination with unknown genes, which have nothing to do at sequence level with the wildtype itself, should help, but you have given no reason to believe that. The simple reason why the wildtype, the true optimal peak, cannot be found is because it is too small and isolated, and the random search is not powerful enough to find it. Recombination is a form of random variation too, unless part of the functional sequence to be found is already present in the genes which recombine. Therefore, unless you recombine with phages which still have the wildtype gene, I can't see how recombination can help in that scenario, and you have given no reasons to believe that. The simple truth is that the highly functional wildtype is not an optimization of the random sequences that were used in the experiment: there is no convergence towards the wildtype at the sequence level, as the authors state clearly. You seem to forget too often that all the variation happens at sequence level in the genome. The search is a search for a sequence, the sequence which bears the optimal function. If that sequence is small enough and isolated enough, that peak will simply not be found by random variation, of whatever kind, including recombination. And you have shown no experimental data where recombination really helps to find a functional result which eludes simple mutations. That would be some support to your ideas. Not certainly the papers about the role of recombination in virus diversity. Nobody denies that "recombination is an important mechanism of genetic diversity.". That is simply obvious. The point is, and always has been: is recombination an important mechanism in the random search for complex functional sequences? I believe that the answer is definitely: no.gpuccio
December 8, 2015
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gpuccio: 5) The most important effect of recombination is to increase genetic heterogeneity and diversity. In that sense, it acts like mutations. Recombination generates different mosaics of viral genes in different strains. Recombination allows for variants not available to simple mutation, including the evolution of new strains. A schematic example was provided above that should be clear enough. gpuccio: 7) What I have not found is any indication, in any of the papers, that gene recombination may have any helping power in the generation of new functional genes. The discussion wasn't of new genes, but of how genes are optimized in a complex landscape. With simple point mutation, genes tend to become fixed on local fitness peaks. With recombination, much more of the landscape can be explored. Consequently, recombination is an important mechanism of genetic diversity. As for new genes, we know that even random sequences can have function, so duplicates and fused fragments of old genes clearly can have function. There are a number of known mechanisms for the creation of new genes. See this review article for a discussion; Long et al., The origin of new genes: glimpses from the young and old, Nature Reviews 2003.Zachriel
December 8, 2015
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Zachriel: Of course, if what you mean is that the defective phage in the Hayashi paper could easily retrieve the wildtype efficiency by recombination if it recombines with a normal phage, which has retained the wildtype sequence, well, that is obvious! Recombination certainly can do that! It can shuffle existing information, and that's more or less what it can do. But I don't think that that is what you meant. Another comment: in your toy examples, you always reason about recombinations of small sequences, like a couple of letters. But that's not what usually happens in biology. As you can see in the quoted papers, recombination usually implies long sequences of DNA. The so much invoked exon-shuffling, for example, implies more or less whole exons. There is an important consequence of that: recombination of long sequences is bound to be recognizable because of the implicit homology: we can recognize what was recombined, and how. That's exactly how recombination is studied and detected. Small variations of a couple of nucleotides are more easily explained by simple mutations, including indels.gpuccio
December 8, 2015
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Zachriel: OK. I have read, briefly, the introduction to that issue and the 6 papers in the issue. Here are my comments. 1) Recombination does occur in viruses, although for many types of them it seems to be an uncommon event. In other types, it is very frequent. 2) Recombination usually occurs between different strains or subtypes of the same virus, and even between different, but similar viruses. The most common scenario for recombination events is the infection by two different types or subtypes of viruses. 3) Recombination can be homologous (between homologous genes), or non homologous. 4) In many cases, recombinants are non vital, or show less fitness than the parental strains. In other cases, fitness is not affected. 5) The most important effect of recombination is to increase genetic heterogeneity and diversity. In that sense, it acts like mutations. Recombination generates different mosaics of viral genes in different strains. 6) Obviously, that has important consequences regarding vaccine sensitivity, virulence against specific hosts, resistance to therapies, and phylogenetic studies of viruses. 7) What I have not found is any indication, in any of the papers, that gene recombination may have any helping power in the generation of new functional genes. Its role seems to be simply to redistribute existing genes, and mix them somewhat. While the consequences of that can certainly be of great relevance, there seems to be absolutely no relevance of these phenomena to the generation of complex functional information. All of them seem to be examples of molecular microevolution, and none of them seems to be implied in scenarios like the one we have discussed previously. There is no doubt that viruses are probably the best scenario for RV + NS: their rate of variation is astounding, and they are probably engineered to change as much as possible and to gain as much as possible from those changes. That is probably implicit in their basic program. However, even in that incredibly favorable scenario, the limitations of RV + NS are obvious, and nothing goes beyond simple microevolutionary events, whose functional complexity is very low.gpuccio
December 8, 2015
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Zachriel: OK, thank you. I will look into it.gpuccio
December 8, 2015
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gpuccio: If you have any biological papers regarding the role and powers of recombination, I would be interested. How about an entire issue of the journal Viruses dedicated to recombination: "Recombination is an important source of genetic variability in viruses"Zachriel
December 7, 2015
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gpuccio @69
If you have any biological papers regarding the role and powers of recombination, I would be interested.
I agree. Perhaps that should be a requirement for any serious discussion. It could be named "the gpuccio rule": biology-related arguments should be supported with references to specific papers that can stand thorough review by anyone.Dionisio
December 7, 2015
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gpuccio @59
[...] in the meantime true biology makes ever new discoveries of unending functional complexity (see epigenetics and cell differentiation) [...]
:)Dionisio
December 7, 2015
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Zachriel: However, thank your for your contributions. They are appreciated. I think I have said more or less all that I had to say on the points you offered. I hate repetition, so that's it. If you have any biological papers regarding the role and powers of recombination, I would be interested.gpuccio
December 7, 2015
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Mung: So small that “Mother Nature” can’t tell the difference. Some changes are below the effect of natural selection, depending on population size. Some changes are subject to natural selection, most of which cause small differences in reproductive potential.Zachriel
December 7, 2015
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Zachriel: Most natural selection is due to small differences in reproductive potential. So small that "Mother Nature" can't tell the difference.Mung
December 7, 2015
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Eugene: Flexibility means control. Flexible means capable of bending. Many mutations to genomes cause little or no selective change, hence genomes are considered flexible. Eugene: The control is effectively binary: survive or die. That is incorrect. Most natural selection is due to small differences in reproductive potential.Zachriel
December 7, 2015
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Zachriel, "Then that peak will probably never be found by evolutionary search..." You are right. It won't be found in that case. "...keeping in mind that actual evolution includes a lot more flexibility than the toy example" I can't agree with this though. Flexibility means control. There is minimum control in blind evolutionary search. The control is effectively binary: survive or die. Flexibility, IMO, assumes a lot more than that. You seem to always conflate the capabilities of artificial selection with those of natural selection.EugeneS
December 7, 2015
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Evolutionary algorithms still exemplify evolution by DESIGN.Virgil Cain
December 7, 2015
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gpuccio: you have no empirical evidence that recombination can help in a scenario like the one we were discussing. We provided four lines of evidence concerning the effectiveness of recombination in scenarios like the one we were discussing. We did not provide evidence of the effectiveness of recombination in the exact scenario because the researchers did not include that in their study. gpuccio: You seem to forget that: a) The wildtype sequence was much more efficient then the sequences they evolved Didn't forget it. In fact, we addressed it directly. Lack of recombination leaves evolution stuck on local peaks. gpuccio: b) A sequence like the one found in the experiment, which has nothing in common with the sequence in the wildtype, can scarcely be considered “a pathway” to the wildtype That can't be known based on the research. Recombination is such that offspring are usually unique. gpuccio: “we replaced the D2 domain of the fd-tet phage genome with the soluble random polypeptide RP3-42.” Solubility doesn't significantly change the denominator, so it doesn't change the overall findings. Keep in mind that, in nature, the starting point is probably a duplicate or fragment of an existing sequence, so the denominator is much lower than in a random sequence, even if we assume solubility. EugeneS: The toy examples suggested by Zachriel assume that since we can walk, we can walk to the Moon, given enough time. No. The example is much more limited. It shows 1) how simple mutation can be stuck on local peaks; 2) how recombination can overcome local peaks to find the global peak. EugeneS: What about scenarios where there is NO landscape at all around a peak? I.e. where no recombination or mutation selectably leads from one group of peaks isolated by chaos to another. Then that peak will probably never be found by evolutionary search (keeping in mind that actual evolution includes a lot more flexibility than the toy example). Turns out, though, that the natural landscape is not chaotic in that sense, but highly ordered. gpuccio: Zachriel’s “examples” are abstract toys, completely out of context. The toy example shows 1) how simple mutation can be stuck on local peaks; 2) how recombination can overcome local peaks to find the global peak. Mung: Does population genetics show the importance of lateral gene transfer and symbiosis? Classical population genetics didn't, but modern population genetics has incorporated these mechanisms. Computer simulations, in conjunction with empirical evidence, are now the primary means of exploring population genetics. Mung: Not every EA uses recombination. Are you claiming an EA always performs better if you introduce recombination? Most evolutionary algorithms use some sort of crossover, because most complex spaces require recombination for an extensive search. https://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)Zachriel
December 7, 2015
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Zachriel: 1. Population genetics shows the importance of recombination. Does population genetics show the importance of lateral gene transfer and symbiosis? Zachriel: 2. Evolutionary algorithms show the importance of recombination. Not every EA uses recombination. Are you claiming an EA always performs better if you introduce recombination?Mung
December 7, 2015
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1. Population genetics shows the importance of recombination.
Yes, recombination is an important design feature.
2. Evolutionary algorithms show the importance of recombination.
Evolutionary algorithms exemplify evolution by DESIGN. Zachriel is too dim to grasp any of that.Virgil Cain
December 7, 2015
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GP, Absolutely. Evolutionism as any other type of reductionism suffers from its ancestral diseases, so to speak. They claim that biology must be reducible to chemistry, chemistry to physics. But in the real world, there are huge problems with reducibility: combinatorial problems are irreducible to polynomial time problems, semiotic phenomena (biology included) - to physicality, information - to mass/energy, consciousness - to matter.EugeneS
December 7, 2015
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EugeneS: You are right. Zachriel's "examples" are abstract toys, completely out of context. He is probably a good expert of algorithms, especially with words, but I am afraid that he is less familiar with biological contexts. Not his fault, however. The simple fact is that neo darwinism (or its personal variants) badly needs vague explanations. So, random walk and genetic drift along imaginary pathways is a neo darwinist star, until experiments show that it cannot even really optimize a damaged domain in an existing, still functional protein. Then when numbers like 10^70 come to the attention (for once, not because of IDist plots), some new magic is needed, something that has not yet been really tested in a biological context, and can therefore be vague enough to satisfy the true believers. So, recombination is ready to fill the void. OK, we are here to patiently witness all these games. Luckily, in the meantime true biology makes ever new discoveries of unending functional complexity (see epigenetics and cell differentiation), and this ugly nightmare of biased cognition will be over, sooner or later.gpuccio
December 7, 2015
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The toy examples suggested by Zachriel assume that since we can walk, we can walk to the Moon, given enough time. What about scenarios where there is NO landscape at all around a peak? I.e. where no recombination or mutation selectably leads from one group of peaks isolated by chaos to another.EugeneS
December 7, 2015
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