Daniel Arant: Questions about Evolution and Design

A commendable attitude I have to say. There’s absolutely nothing wrong with asking questions.

Yes this is a topic that sows an awful lot of confusion, among other things because scientists honestly aren’t being all that clear on this topic either.

I think you need to separate out these two questions:

  • What is the selective effect of most mutations that occur and go to fixation across some organism’s genome, over generations?
  • How does some specific, clearly adaptively beneficial organismal attribute, originate and subsequently evolve?

The idea is that a majority of mutations that go to fixation are selectively neutral, but there is still some small but significant portion that have selectively beneficial effects, and thus can contribute to optimizing some adaptation.

But you’re probably also thinking about two other things, which are rarely well articulated in these matters. You want to understand the relationship between evolutionary innovation, molecular complexity, and adaptation.
To what extend do mutations that occur and go to fixation constitute innovative mutations?(how often do mutations result in novel biological functions?).
To what extend do mutations that occur and go to fixation contribute to increases in molecular complexity? (like adding more functional genes to the genome, adding more proteins to some existing structure, and ultimately result in more complex multicellular organisms with multiple distinct organs and all that stuff)
To what extend do mutations that occur and go to fixation contribute to increases in reproductive success?

It’s important to understand that these three issues are not the same thing, and the relationship between them is complicated, depends on circumstance, and can be found anywhere from being correlated to anti-correlated.

  • Complexity can go up while fitness goes down, while number of total functions remains the same. Think of mere duplication resulting in multiple unnecessary gene-copies that negatively affects some organisms metabolic budget by the cost of expressing them, leading to a slight fitness decline. Genomic complexity has gone up as the number of functional genes and genome size has increased, but it has incurred a slight fitness loss. No new function was gained.

  • Complexity and fitness can remain the same while number of total functions goes up.
    Think of point mutations that make some enzyme able to act on a novel substrate and break it down without altering it’s existing function, but the organism has no use for these novel break down products. Number of functions have gone up, but the organism is unaltered in terms of fitness or complexity.

  • Fitness and functions can go up while complexity decreases.
    An organism is suffering deletions in some gene, which makes the gene relocate to another part of the cell when expressed, which alters it’s morphology so it becomes better able to resist an antibiotic. It’s evolved a new function through a deletion(decreasing it’s genomic complexity), and this function happened to be beneficial.

And of course many other variations on those themes.

One can imagine, and find innumerable examples of mutations that have such effects. There IS NO easy or obvious relationship between fitness, innovation, or complexity. They can all go up or down independently of each other. Sad but true.
Evolution is not thought by any extant evolutionary biologist to constitute one long unobstructed gain in organismal complexity (or reproductive fitness) through the history of life. Lots of existing genes can be duplicated and degrade to mutations, and this can be beneficial, or it can be deleterious, or it can be neutral, and new functions can be found once in a while that might suddenly become beneficial and be super-optimized by positive selection.

That said, neutral processes can contribute to the evolution of both complexity and novel functions in something called constructive neutral evolution. Selection still plays a role in this process, but it’s mostly through so-called negative selection. Removing deleterious variants while merely retaining still functional ones.
It’s important to understand that complexity is not necessarily beneficial, nor necessarily deleterious. It is highly context-specific. Complexity can result in adaptations, but it can also be mal-adaptive. There is no simple relationship between fitness and complexity.

I’ve posted this figure before that is supposed to explain how even “devolution” (not a real term in biology, just borrowing it from Behe) can result in gains in functions and increases in genomic complexity, while being almost entirely driven by a combination of neutral changes and negative selection:


Squares represent genes, colors and intensity represent functions and their degrees(brighter color = higher degree of function). Red rectangles highlight what is being duplicated and passed on.

This is “adaptive devolution” of increased complexity, and new functions, by mostly “degrading” and mostly “breaking” genes. Because these extra genes are costly to express, their death is adaptive, and so is the eventual deletion of them. But because the still functional copies continue to accumulate deleterious mutations, as these are are more frequent than beneficial ones, their duplication is also some times adaptive(more expressed genes compensates for each individual gene being weaker).

Eventually over many generations a previously dead gene locus, a black square (effectively having become non-coding DNA) evolves into a de novo protein coding gene (purple square, Function B). This new functional gene suddenly comes under strong positive selection so is quickly improved over subsequent generations. So one new function is evolved and enhanced, while all the rest degrades and breaks. The net result is more complexity and more functions than there was to begin with. And it happened almost exclusively through neutral and adaptive degeneration. There was one innovative mutation among thousands of degenerative ones.

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Sorry, I just don’t have time to respond in depth at this moment. @Rumraket’s answers are helpful to you I hope?

There are two possible answers to this, and of course both depend on what exactly you think would qualify as a complex system and what you think counts as an explanation.

Most of the evidence for evolution is inference from comparisons of different organisms. Scientists infer that certain things evolved (and how they evolved) from being able to derive the relationships between the organisms that carry these attributes using phylogenetic methods.

That said, there are of course experiments and observations of “complex systems” that evolved. But this is where much depends on what you mean by a complex system. If you think we need to show by observation the evolution of an entire bacterial flagellum from some state where none of it’s constitutent proteins even exist (or where none of them have come together), then that can’t be done as that simply takes too long. And that’s really not an excuse, because we really do have to accept that some large-scale developments just take much longer than can be directly observed.
I’ve never seen the formation of an entire mountain range, I haven’t seen the emergence of an entire forest, or a river cut a path through hundreds of meters of rock. But we can observe smaller-scale changes in the present, and with those infer that they can add up to larger-scale changes in the future if they are allowed to continue at a similar rate.

There are ways of elucidating that certain things occur on long timescales, and have occurred in the past, that allow us to conclude this with good confidence, without us having to see it happen in real time. There are such methods used in comparative genetics that allow scientists to infer not only THAT certain structures evolved, but some times even how.

There’s a method called ancestral sequence reconstruction, where scientists can test evolutionary inferences using phylogenetic methods. They can literally use phylogenetic trees to derive what ancestor states would have looked like, infer their functions, recreate them in the laboratory and test them to see if their inferences are right (and test to see if the ancestor state really would have been functional). They can then test the functional and selective effects of historical mutations that occurred between the reconstructed ancestor and it’s extant descendants.

For example, scientists from the Thornton laboratory have recreated small pieces of the evolutionary history of the vacuolar ATP-synthase molecular machine, which you can read about here:

They have many other good publications on ancestor reconstruction where they show different new functions and proteins evolved over time.

I think the statement that there are “relatively few” sequences that result in viable proteins is vague. And I think there’s good evidence that it is nowhere near so low that new proteins can’t evolve. I’d be happy to discuss more of that if you are interested.

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Perfectly understandable. I"m just grateful that you’re taking the time to entertain the musings of a layman and a nobody.

Yes @Rumraket’s comments are very informative.

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This is an inference, not really an assumption.

Generally speaking the case for homology (the inference that the proteins in question really are homologous, that is they share common ancestry and so evolved from a common ancestor) is based on being able to show that there is significant nesting hierarchical structure in their shared similar characteristics (for proteins this can be derived from analyzing and comparing their amino acid sequences and/or the DNA sequences that encode them). Most of these methods involve being able to derive a phylogenetic tree from the sequences of the proteins and seeing how well-supported the tree is by various statistical measures.

The case for actual evolutionary relatedness then can be further supported by showing that the tree implied by one protein, is largely reflected in the trees derived from other proteins. This yields a concept known as consilience of independent phylogenies. The question becomes, why should the phylogenetic tree derived (using some systematic algorithm) from the sequences of one gene, yield a tree with a similar branching topology to an independently inferred phylogenetic tree derived from an entirely independent gene?

This kind of comparison can be done both within and between genes. When similar trees are consistently recovered from different parts of the data, there’s really no other good explanation for this fact than the fact that these different parts of the data all really did go through the same genealogical process of branching descent with modification.

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Saying that anyone who disagrees with you isn’t a Christian is a real conversation-stopper. Do you really want to do that?

More briefly than possible, I’d say. You just can’t go around saying that a Christian must be an IDer or creationist (not sure which you intended).

Universal common ancestry, I believe. How he thinks ID works within that framework has never been clearly stated.

Some lens crystallins in various taxa (birds among them) would be another example. Some of them also function (presumably their original functions) as enzymes elsewhere in the body.

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Daniel, you are making good points. I am also a “layman”, and I would say these guys have a very difficult time, bringing the knowledge down from the top shelf (it’s like Computer Geeks talking in “code” language!) Simple answers are are good place to start, and usually better in all areas of life. That been said, there is value in trying to pick up what is being said. I also agree, totally, that debates are extremely valuable. In Proverbs it says… “the First to present in Court sounds Right, then the cross-examination begins”. @swamidass Josh has the guts to at least engage, respectfully, and that is very Rare. I don’t know if you are relying on your Intuition, but if you are I would Encourage you in that endevor. I would say it is Clear, that all/most of these “things” were Designed (and Evolution had nothing to do with it), you will be Fully Challenged here on your Intuition/CommonSence/ClearlySeen opinion. The Behe/Swamidass 2nd, 90 min video, pushed me even further to the Design side of the spectrum!

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I’m not talking about validating evolution, I’m talking about donstrating that it is even possible on a large scale. Without a detailed, stepwise account for a particular case, how can you call it anything more than speculation?

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What does that even mean? How many steps for you would qualify as stepwise? I’ve seen plenty of what I would call stepwise explanations. But then a skeptic, would find one area where we aren’t exactly sure and go ahah!

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@Daniel_Arant it seems the same could be said of design, right? Without a detailed stepwise account of design, how do you have anything more than speculation? The fact of the matter is that we have far more details on how evolution has taken place (even though we do not have the whole story) than we have of God’s design.

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If this were a conversation about religion and christianity, then it would be a conversation stopper. But that’s not what this conversation is about. You seem determined to be disagreeable?

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I appreciate the explanation. Forgive me if I’m oversimplifying, but it sounds like yes, evolution is now viewed as a mostly random process. Natural selection plays a relatively minor role. Does this not increase the difficulty of discovering new functionality (which I take to mean everything from a new ezymatic function all the way to a new body plan?)

I’m also struggling to understand how so many neutral mutations can become fixed without any selective pressure. I think I understand the concept of genetic drift broadly, but it must include an awful lot of scenarios in order to be able to explain so much genetic fixation, no? Are there any observations of the rapidity with which neutral mutations become fixed?

Paradoxically, perhaps, it helps.

Think about it this way. Let’s say that to “win” you have to be able to sink 100 free throw baskets (i.e. get 100 specific mutations). If you have 100 throws, how difficult is this? Pretty hard. Even professionals might struggle.

Now, what if you have a 100,000 throws to get 100 baskets? Well, now it is much much easier. The vast majority of mutations can be off in random directions, and it doesn’t really matter. Though the number of random throws is dramatically increased, the chance of getting the mutations you need has increased a great deal.

So yes, most mutations are not useful, and are not selected. But that also means that only a few mutations are required for important evolutionary changes, and there is a lot of extra shots to find those mutations.

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There’s no reason why it should should make it more difficult to discover new functions, but to understand why you need to separate the three questions of novel function, and more complexity, from the question of fitness.

Natural selection has to do with the fitness effects of mutations (natural selection doesn’t “care” how mutations achieve those effects, whether increases or decreases in functions or complexity). Do they increase survival and reproduction? A mutation doesn’t have to produce a new function, or more genes, to help survival and reproduction. It may simply change the degree of some existing function up or down, and this can help survival and reproduction.

And a mutation resulting in a new function might even be deleterious in rare cases. Suppose an existing transcription factor mutates so now it can bind a new place on the chromosome, but this new binding spot happens to block expression of another important gene. In this case, new functionality would be deleterious.

So when it comes to discovering new functions, it doesn’t matter what the fitness effects of the average mutation is. The specific proportion of these mutations that result in novel functions is largely independent of their fitness effects. So when scientists have discovered that most mutations are pretty much selectively neutral, this didn’t change anything about how likely it is for a mutation to result in a novel function.

However, when it comes to the question of complexity, there are classes of high-probability mutations that can quickly result in increases in complexity. And ironically, this tendency for complexification can actually provide the basis for increased speed of discovery of novel functions. It’s basically the scenario I described above in the figure with all the squares.

Think of it this way: Two classes of mutations are thought to be very frequent: Gene duplication and insertion-type mutations(such as transposons), and deleterious point mutations of relatively small effect.
These two types of mutations, in combination, allow for an increased rate of exploration of sequence space. Here the exploration is driven by inherent mutational tendencies. What types of mutations are most likely to occur (and by types I mean what biochemically happens at the molecular level, not their fitness effects). That is the tendency for repetitive segments to undergo duplication, and for transposons to facilitate their own copy and random insertion, combined with the tendency for “degenerative” mutations to occur in these extra gene copies.

This means the number of genes that are exploring sequence space by accumulating mutations can build up over time, leading to an increased rate of exploration of that space because more and more genes are mutating in parallel. Instead of just one gene waiting for new beneficial mutations to also have novel functions, you get lots of copies of genes that just accumulate lots of mutations of relatively small effect, and so with many genes mutating in parallel you get a much higher rate of sampling sequence space for new functions.

So complexity builds up over time while being mostly selectively neutral, but the complexity increases in turn increases the rate of discovery of novel functions.

New functionality still depends on mutations and genome rearrangements, so whether most mutations that are fixed are beneficial or neutral doesn’t make any difference to the probability of discovering a new function my mutation.

It is a well-known result in population genetics that the rate of fixation of neutral mutations is equal to the rate of mutation. This is pretty well explained in this 12 minute video:

There’s not anything special in some “scenario” that has to happen for this to occur, it simply follows mathematically.

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Not so. I merely point out the implications of your statement. If you would like to withdraw the statement, that would be a fine response.

It would be useful to consider the difference between quantity and quality. Given that most of the genomes of most eukaryotes are junk, evolving neutrally, then most mutations that become fixed in a species do so through drift. That doesn’t mean that selection is not important, in fact dominant, in the small portion of the genome under selection and subject to adaptation.

Generally not, since fixation is slow, and one would need to survey a very sizeable fraction of the population. But theory should do: if I recall, it should take on average around 4nµ generations for a new mutation that eventually becomes fixed to go from mutation to fixation, where n is the effective population size. That’s quite a long time for most populations. However, the number of fixations in any one generation is also the same as the number of mutations per individual, so they do add up.

Whoops, I think I meant just 4n, not 4nµ.

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Glad to hear it.

I’m sorry, but that makes no sense at all.

I would strongly recommend that you learn the basics. It will be impossible to understand even the most basic concepts in population genetics without being able to distinguish between genes and alleles. Alleles get fixed, not genes. That’s not pedantic.

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It’s not assumed. The evidence is consistent with homologous proteins having common ancestors, not one evolving into another. It’s an important distinction.

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You’re oversimplifying.

Nope, still major.

No, it increases it.

How many randomly-generated antibodies must one screen to get measurable beta-lactamase activity?

Here’s a chance for you to put a hypothesis to the test. Predict a number.

I would also suggest that you’ll get more constructive responses if you don’t resort to regurgitation of deliberately vague terms like “body plan.”

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I think the bigger problem, skeptics would say, is that there was precious little time for such a change to take place. Is it not the case that mutations in developmental genes are similar to any other, in that they are overwhelmingly deleterious? Are there any observed examples of undirected mutations to developmental genes producing a useful, or at least neutral, change?

Yes, they are similar, but no, they are not overwhelmingly deleterious.

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