Why? Do I need to be able to explain an engine before I can drive a car, or build a circuitboard before I can use a computer? Do I need to explain the quantum mechanics of an atom to you before we can discuss chemical bonds?
I’m perfectly willing to discuss current theories of abiogenesis with you if you like, but not as a requirement or prerequisite of discussion of evolution.
And you can explain where the designer came from, etc.
I have (I’m a biologist) and analogies are still explanatory devices, not arguments.
The idea that you can change the course of biology just by setting definitions (and doing no biology) is absurd.
The topic is irreducible complexity. Not evolution. And my point is that the smallest possible cell that keept the vital functions to remain alive, was irreducible complex. Its origin cannot be explained through evolution, since evolution only operates upon dna replication.
Who or what created God ?
I am not setting definitions. I am just elucidating how molecular factories and machines are build, and upon drawing comparisons and parallels to man made machines, it becomes evident that the whole conundrum of evolution being able to make new phyla and body plans is totally inadequate and nonsense.
What did the designer do? How did she do it? How did she instantiate her designs? How can all this be tested?
Hello, Otangelo. Its been a while. You might not remember me, but we had some fun in similar discussion at the facebook website Celebrating Creation by Natural Selection. Glad to see you here, where you will find a lot more experts in this area.
The problem with the quote you cited from Behe is the same problem with the statement[quote=“Otangelo_Grasso1, post:14, topic:35068”]
Biological systems are structured like manmade machines,
[/quote]
which @benkirk has already addressed. I will add a bit to that. It turns out that all of the analogies that people like to use for biology, whether they come from car or airplane manufacturing, software engineering, human language or any kind of machine, turn out to be flat out wrong. They simply dont work, except at the most elementary level. (Yes, DNA can be compared to a language, but only so far).
I recommend a book called “Arrival of the Fittest” by Andreas Wagner (been discussed here many times) about how biological networks (gene regulatory networks, metabolic networks, and so on) can easily explore new spaces and create innovative phenotypes, using very slight modifications, indeed. Also, I am sure you have heard the term exaptation. More and more discoveries of exaptation are being found, and this concept is directly contradictory to some of the basic assumptions of IC.
[quote=“Otangelo_Grasso1, post:26, topic:35068”]
I am just elucidating how molecular factories and machines are build,…[/quote]
You are elucidating nothing that I can see. You are all rhetoric.
Analogies in science are useful explanatory devices, but they always break down. Have you noticed that man-made machines are not alive and do not reproduce?
[quote]…it becomes evident that the whole conundrum of evolution being able to make new phyla and body plans is totally inadequate and nonsense.
[/quote]Only if one ignores the data in favor of rhetoric.
Hey, I was just answering the question you asked!
Not true. RNA is much more relevant, especially to any discussion of first cells. Evolution acts on any replicating, variable units, including bits of computer code.
I wish we’d had you around when we were trying to figure out the whole ‘body plan’ definition/argument a few weeks ago! If you’d like to take a look at the thread and offer your opinion, I’d love to hear it!
I disagree. With good reasons.
No evidence that RNA molecules ever had the broad range of catalytic activities
Paul Davies The Algorithmic Origins of Life
Despite the conceptual elegance of the RNA world, the hypothesis faces problems, primarily due to the immense challenge of synthesizing RNA nucleotides under plausible prebiotic conditions and the susceptibility of RNA oligomers to degradation via hydrolysis 21 Due to the organizational structure of systems capable of processing algorithmic (instructional) information, it is not at all clear that a monomolecular system – where a single polymer plays the role of catalyst and informational carrier – is even logically consistent with the organization of information flow in living systems, because there is no possibility of separating information storage from information processing (that being such a distinctive feature of modern life). As such, digital–first systems (as currently posed) represent a rather trivial form of information processing that fails to capture the logical structure of life as we know it.
We need to explain the origin of both the hardware and software aspects of life, or the job is only half finished. Explaining the chemical substrate of life and claiming it as a solution to life’s origin is like pointing to silicon and copper as an explanation for the goings-on inside a computer. It is this transition where one should expect to see a chemical system literally take-on “a life of its own”, characterized by informational dynamics which become decoupled from the dictates of local chemistry alone (while of course remaining fully consistent with those dictates). Thus the famed chicken-or-egg problem (a solely hardware issue) is not the true sticking point. Rather, the puzzle lies with something fundamentally different, a problem of causal organization having to do with the separation of informational and mechanical aspects into parallel causal narratives. The real challenge of life’s origin is thus to explain how instructional information control systems emerge naturally and spontaneously from mere molecular dynamics.
Systems of interconnected software and hardware like in the cell are irreducibly complex and interdependent. There is no reason for information processing machinery to exist without the software, and vice versa.
Perry Marshall, Evolution 2.0, page 151:
There are problems with the RNA world hypothesis: Many scientists believe RNA is too complex to have arisen without the presence of the very same life forms it is believed to have created; RNA is inherently unstable, so even if it did arise, it wouldn’t last long without a cell to protect it; catalysis of chemical reactions is seldom observed to occur in long RNA sequences only; and the catalytic abilities of RNA are limited. The RNA world hypothesis doesn’t actually solve the chicken-and-egg problem of RNA and proteins: You need RNA to produce proteins, but you need proteins to build the machinery to read the RNA in the first place. As a communication engineer, my objection to the RNA hypothesis is that to evolve any kind of cell, RNA would have to self-replicate. But the RNA strand formation you read about in the literature is not codebased self-replication. It’s similar to crystal growth, which does not use codes at all! RNA strand formation in a chemical lab is not in any way, shape, or form the same as DNA transcription and translation. In DNA transcription and translation, in order to convert code to proteins, you need a ribosome to transcribe the message. But in order to have a ribosome you have to have a plan for building a ribosome first. A ribosome is partly made from RNA. So before that, you have to have a code in the RNA. Many books and papers on the Origin of Life only discuss the assembly of the chemicals themselves. Nothing we know about chemicals tells us where codes come from. Saying you can get real DNA by stringing chemicals together is like telling your kid that TVs come from a glass factory
Without code there can be no self-replication. Without self-replication you can’t have reproduction. Without reproduction you can’t have evolution or natural selection.
This guy is not a scientist. He’s an expert in advertising.
ah, you want from a scientist… got ya.
from the book: The Logic of Chance: The Nature and Origin of Biological Evolution
By Eugene V. Koonin
The origin of replication and translation and the RNA World
The primary incentive behind the theory of self-replicating systems that Manfred Eigen outlined was to develop a simple model explaining the origin of biological information and, hence, of life itself. Eigen’s theory revealed the existence of the fundamental limit on the fidelity of replication (the Eigen threshold): If the product of the error (mutation) rate and the information capacity (genome size) is below the Eigen threshold, there will be stable inheritance and hence evolution; however, if it is above the threshold, the mutational meltdown and extinction become inevitable (Eigen, 1971). The Eigen threshold lies somewhere between 1 and 10 mutations per round of replication (Tejero, et al., 2011); regardless of the exact value, staying above the threshold fidelity is required for sustainable replication and so is a prerequisite for the start of biological evolution
Indeed, the very origin of the first organisms presents at least an appearance of a paradox because a certain minimum level of complexity is required to make self-replication possible at all; high-fidelity replication requires additional functionalities that need even more information to be encoded (Penny, 2005). However, the replication fidelity at a given point in time limits the amount of information that can be encoded in the genome. What turns this seemingly vicious circle into the (seemingly) unending spiral of increasing complexity—the Darwin-Eigen cycle, following the terminology introduced by David Penny (Penny, 2005)—is a combination of natural selection with genetic drift. Even small gains in replication fidelity are advantageous to the system, if only because of the decrease of the reproduction cost as a result of the increasing yield of viable copies of the genome. In itself, a larger genome is more of a liability than an advantage because of higher replication costs. However, moderate genome increase, such as by duplication of parts of the genome or by recombination, can be fixed via genetic drift in small populations. Replicators with a sufficiently high fidelity can take advantage of such randomly fixed and initially useless genetic material by evolving new functions, without falling off the “Eigen cliff” (see Figure 12-1B). Among such newly evolved, fitness-increasing functions will be those that increase replication fidelity, which, in turn, allows a further increase in the amount of encoded information. And so the Darwin- Eigen cycle recapitulates itself in a spiral progression, leading to a steady increase in genome complexity (see Figure 12-1A). The crucial question in the study of the origin of life is how the Darwin-Eigen cycle started—how was the minimum complexity that is required to achieve the minimally acceptable replication fidelity attained? In even the simplest modern systems, such as RNA viruses with the replication fidelity of only about 10^3 and viroids that replicate with the lowest fidelity among the known replicons (about 10^2; Gago, et al., 2009), replication is catalyzed by complex protein polymerases. The replicase itself is produced by translation of the respective mRNA(s), which is mediated by the immensely complex ribosomal apparatus. Hence, the dramatic paradox of the origin of life is that, to attain the minimum complexity required for a biological system to start on the Darwin-Eigen spiral, a system of a far greater complexity appears to be required. How such a system could evolve is a puzzle that defeats conventional evolutionary thinking, all of which is about biological systems moving along the spiral; the solution is bound to be unusual.
Or the solution might be outside the realm of philosophical naturalism, that is, intelligent design ?!!
Speaking of evidence, what is peptidyl transferase, the catalyst that is actively synthesizing all of the proteins in your body right now?
Hi Ben,
I recently read some mathematical population genetics modeling that shows that cryptic mutations can help bridge the gap to new functionality that would otherwise be considered irreducible complexity. What I would like to know is whether there is empirical evidence behind this theoretical model?
I am guessing that neutral drift could be considered a source of cryptic mutations–and biologists have indeed witnessed neutral drift. Since I am not a biologist, however, I would welcome expert feedback on whether my hunch is valid. In fact, I would be quite surprised if this has not already been explored in the literature, and I am just unaware of it.
What do you think? @sfmatheson @DennisVenema @Swamidass @Sy_Garte
Thanks!
I don’t think drift is a source of mutations. Drift can explain why mildly deleterious mutations could avoid purging by selection, but that’s not going to explain cryptic variation. I think the first-pass answer to why there is often very substantial genetic variation in populations is simply neutrality. Lots of genetic variation is selectively neutral.
But that neutrality itself has several potential explanations. Much is simply functionally inconsequential, but then we might wonder why it would come in handy during adaptation. Much is maintained by epistasis, such that there are mutations that are “deleterious” in some genetic backgrounds but neutral or even beneficial in others. This would be potentially cryptic (hidden) in a population. And then there is the issue of genetic capacitance, which Masel and colleagues emphasize in their paper. This is a super interesting concept that has at least one strong molecular basis: chaperones like Hsp90. The work of the recently deceased Susan Lindquist was pivotal in establishing this phenomenon. Look at this major paper by Christine Queitsch when in Lindquist’s lab. It’s a classic.
The capacitance concept is backed by some strong experimental evidence, IMO. When Hsp90 is inactivated, sudden diversity appears in phenotypes, seen in the Queitsch paper and in the first paper to show this, in flies. The implication is that organisms can harbor vast potential functional variation, buffered by mechanisms including the Hsp90 system.
I wrote about one great example of how the existence of standing variation underlies evolutionary change, in corn/teosinte.
Have I addressed your question? Thanks for raising a fun and interesting topic.
[quote=“Chris_Falter, post:36, topic:35068”]
I recently read some mathematical population genetics modeling that shows that cryptic mutations can help bridge the gap to new functionality that would otherwise be considered irreducible complexity. What I would like to know is whether there is empirical evidence behind this theoretical model?[/quote]
Hi Chris,
Not to my knowledge, but others here do more data mining than I do. I would agree with Steve’s reply as an empirically-known possibility.
[quote]I am guessing that neutral drift could be considered a source of cryptic mutations…
[/quote]As Steve said, it isn’t. Drift fixes alleles (cryptic and non) without selection.
This sentence is referring clearly to ribozymes in e prebiotic earth, and the hability to start with self replication . What emerged first, peptidyl transferase, tRNA’s, the Ribosomes, or the genetic code ?
The assumption that the immensely complex ribosomal apparatus of today is required to translate RNA is a direct contradiction of the whole preceding description of how the Darwin-Eigen spiral increases the complexity of the translation process as it further refines its accuracy and efficiency. We have no reason to expect that the original, inefficient versions of today’s ribosomes would still be translating a cell’s RNA. If the whole ‘dramatic paradox’ hangs on this, I’m afraid it’s not much of one.
Very nice post, Steve. Well worth the read.
This is similar to the concept of wide ranging genotype networks (A. Wagner) that allow for an immense variation in genotypes, regulatory networks, and even protein structures, all of which produce identical phenotypes. The resulting robustness allows for cryptic mutations to survive selection until they can become the basis for exaptational innovation. This could very well appear to be IC arising from nothing. The basic point is that the creationist (and some ID) view that phenotypes are highly fine tuned and extremely unlikely, (such as the rarity of a particular protein fold) is simply, demonstrably (by experiment and calculation) not true.
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