Yet More on clarity in the design debate.

In Arguments for Intelligent Design, Definitions and Assumptions Are Important
Ann Gauger

How can random non-coding DNA be, at the same time, both functional (as in the genome) and non-functional (as in extremely unlikely to code for functional proteins)?

   This question was posed recently at Peaceful Science, a discussion site that seeks to promote dialog between atheists, theistic evolutionists, and proponents of intelligent design. (Their success is mixed. ID proponents often feel like Aragorn in the last battle.) It’s a good question. It came out of a conversation about orphan genes, where I was arguing that non-coding DNA was extremely unlikely to give rise to a new coding sequence with any function. Yet ID people claim all the time that the majority of the genome is functional.. How can sequence be both functional and non-functional at the same time? The answer turns on two things. The meaning of “function” and clarity about what’s being tested.

I had been trying to explain Doug Axe’s results to the group of debaters, most of whom did not agree. According to Axe, sequences that can produce a functional protein, namely a protein capable of carrying out an enzymatic reaction, are extremely rare. (They could be rare in number and/or rare in how far apart they are spread in sequence space.) 

Picture a Bank Vault

Think of a situation where you have to crack the code on a bank vault, with many dials in the code, say 150, each specifying 1 out of 10 digits. If there is only one code that will work, the number of possible sequences to try is 10^150, Now say that 100 sequences out of 10^150 would work. That reduces the number you would have to try. It would now be 10^148.

What’s the solution? Well, suppose there was another bank next door, that had a similar code, in fact with 125 of the dials identical! And you happened to know that code. Now the information required is greatly reduced. You have only 10^25 to get. Likely success? And if you are very lucky and know the code nearly completely, all but 3 dials (maybe you know the teller or the person who built the vault), it is definitely easier to break the code. 10^3 =10 x 10 x 10. You have a pretty good chance of success.

The problem is worse for proteins. They have twenty possible amino acids for each position in a protein, so the total possible sequences for a protein 150 amino acids long is 20^150.

To do a random search through that whole space of 20^150 is not possible, just like it would be impossible to search through the 150 dials to find the bank code. But if proteins are not far apart in sequence space, like the bank code where almost all of the code was identical to another bank’s code, then the chances of finding a sequence that will work are greatly improved.

A Crime Spree

Now consider one more thing. Suppose suddenly there were bank robberies everywhere, and it wasn’t by force. The dials had been turned to the correct combinations. What would be your inference? I would say that someone knew the codes.

So unless functional sequences are easy to find (very common), and/or are clustered together (easily reachable from one functional island to another), explaining current protein diversity without design is impossible.

I’ll break that down.

“Unless functional sequences are easy to find (very common), and/or are clustered together (easily reachable from one functional island to another)”: I am laying out the conditions where it might be possible to find function.

“Explaining current protein diversity without design is impossible”: Unless the above conditions are met, namely that functional sequences are easy to find or clustered together, we won’t be able to find functional sequences, unless design has been involved.

Now turn the sentence around.

Explaining current protein diversity without design is impossible, unless functional sequences are easy to find (very common), and/or are clustered together (easily reachable from one functional island to another).

As a consequence, if we find that apparently random non-coding sequences have given rise to new genes and proteins in many genomes, in fact representing 10-30 percent of the genomes analyzed, that result should surprise us, given what I said above. But we need additional evidence still. See below.

Now for the other half of the problem or confusion here. In ENCODE, scientists claimed that the majority of our DNA was functional, meaning it had some sign of biochemical activity. Transcription, methylation, a site for DNA binding, etc., any of these would qualify as functional in some sense. But even ENCODE workers admit they don’t know how much of that “function” will be meaningful.

In the ENCODE sense, most genomic sequence is functional, thus functional sequence is common (20-80 percent was the original range offered). Just remember what function means here — biochemical function, not sequence coding for functional proteins.

So Which Is It? 

If the genome is functional in the sense of ENCODE, that agrees with one part of ID. Some of us argued that the genome would not be junk. We would expect some kind of function for most of it.

But being functional in the biochemical sense (à la ENCODE) does not mean it is easy to give rise to new genes and proteins. When we say functional sequence is rare in sequence space, we mean a different sort of function and sequence than in ENCODE. We mean a sequence that can have the ability to carry out an enzymatic reaction. It is our claim that proteins made from random sequence will rarely if ever have any sort of enzymatic activity. 

That is why experimental tests are to be desired. Can random DNA sequence produce functional proteins with enzymatic activity or not? If experiments say no, that implies something extra is going on, because we do see lots of de novo genes.

However, such experiments may be impossible, because of the inability to test enough sequence to get a handle on a likely small signal. Proving a negative is always difficult. None of the protocols I know can screen enough sequences to test Doug’s hypothesis. 

However, if it is easy to get a functional enzyme from random DNA, if there should be a positive result,  that would definitely argue that de novo genes may be the product of natural processes, and not necessarily design.

As I said earlier, there are labs examining this question of the difficulty of getting enzymatic function from random sequence. I look forward to their results.

There is more that could be said here but I’ll save it for another time.

Reproduction v. Darwin.

Why Evolution and Reproduction Are Unnatural
Granville Sewell

In a recent American Spectator article, “Evolution — More Certain than Gravity?”,Sarah Chaffee and I made the point that to not believe in intelligent design, you have to believe that the four fundamental, unintelligent forces of physics alone (the gravitational, electromagnetic, and strong and weak nuclear forces) could have rearranged the fundamental particles of physics on our once-barren planet into encyclopedias and science texts and computers and airplanes and Apple iPhones.

In a 2017 Physics Essays article, “On ‘Compensating’ Entropy Decreases,” I argued that this spectacular increase in order seems to violate the more general statements of the second law of thermodynamics; at least that you cannot dismiss this claim, as is always done, simply by saying that the Earth is an open system and order can increase in an open system. You have to argue that the increase in order is not really extremely improbable given what has entered our open system from outside.

Darwinists Are Not Impressed

Whether or not you believe that what has happened on Earth violates the second law, I can’t imagine anything in all of science that is more clear and more obvious than that unintelligent forces alone cannot produce such things as Apple iPhones. But Darwinists are not impressed. They believe that natural selection, alone among all natural causes, can create spectacular order out of disorder, and even produce beings that can write science texts and design computers.

That it seems even superficially plausible (until we think about the details) that selection could create such order out of disorder relies completely on the fact that living things are able to reproduce, that they are able to preserve their complex structures and pass them on to their descendants without significant degradation, generation after generation. Without reproduction, there are no variants to select from. Reproduction is the most fundamental characteristic of life. We see it happen everywhere, so we may feel there is nothing “unnatural” about reproduction. 

Imagine Self-Reproducing Cars

But to appreciate how unnatural the astonishing reproductive abilities of living things really are, imagine trying to design cars that are able to give birth to other cars. Although it is far beyond our current technology, imagine that it were possible to construct a fleet of cars that contained completely automated car-building factories inside, with the ability to construct new cars — and not just normal new cars, but new cars containing automated car-building factories inside them. If we left these cars alone and let them reproduce themselves for many generations, is there any chance we would eventually see major advances arise through natural selection of the resulting duplication errors? 

Of course not. Without intelligent humans there to fix the mechanical problems that would inevitably arise, the whole process would grind to a halt after a few generations. We are so accustomed to seeing animals make copies of themselves without significant degradation that we dismiss this as just another “natural” process. But if we actually saw cars with fully automated car factories inside, making new cars with car factories inside them, maybe we would realize what an astonishing process reproduction really is. “How do these instruction sets not make mistakes as they build what is us?” asks mathematician Alexander Tsiaras in the wonderful TED Talk:

How indeed? If you — understandably — cannot accept that something we see happen every day should be called “unnatural,” please watch the video.

The Limits of Natural, Unintelligent Forces

It is not only unnatural that species should evolve from simple to complex, it is unnatural even that they should not degrade over time. Individuals of each species do in fact decay into simpler components, as soon as they die — that is what “natural” looks like. Thus even if the transitions between major groups of animals could be made without encountering irreducible complexity (they certainly cannot), there would still be something very unnatural about evolution, and it still could not be explained without intelligent design. The argument for intelligent design could not be simpler or clearer: natural, unintelligent forces of physics alone cannot rearrange atoms into computers and airplanes and Apple iPhones. Any attempt to explain how they can must run up against reality somewhere, because they obviously can’t.

A Postscript on the Second Law

I hesitate to bring the second law back into this debate because of the controversy it always generates. But people sometimes say that the second law only requires that order should not increase (entropy should not decrease), it does not require that order must actually decrease, so there is nothing unnatural about species simply maintaining their complex structures and passing them on generation after generation without significant degradation. Yet common sense tells us that, when only natural forces are at work, complex things must degrade, and slowly only if everything is almost “frozen in time” (nothing is changing), or else they are already degraded to nearly simplest form. 

Obviously, neither of these conditions holds for the case of animal reproduction. Common sense is actually confirmed by the equations of entropy change when we consider the application of the second law to diffusion of a substance X. Notice that since usually J = -D*gradient(C), equation A7 of my Physics Essays article (equation A4 for the case where X-entropy is just thermal entropy) says that if “X-order” is not imported from outside (the boundary integral term is zero), the only way X-order cannot decrease rapidly is when either things are almost frozen in time (the diffusion coefficient D is small), or the X-order is already close to the minimum possible (gradient(C) is small).

Darwinism:Where success is an orphan?

About Orphan Genes — What’s the Big Problem for Evolution?
Ann Gauger

Orphan genes — genes that are present in only one species, or a group of closely related species — are of particular interest to advocates of intelligent design. The reason for this has to do with the assumptions of evolutionary biology.

The main evolutionary assumption is common descent, that all life is descended from one or a few ancestors. Following from this, and taken as evidence for this, is the assumption that all life shares DNA in common. Prior to the advent of widespread genome sequencing, it was assumed that living things shared genes, that there was a set of shared housekeeping genes, and a set of genes specific to a taxonomic group, though these would be few in number. It was assumed that the vast majority of genes would be found multiple places in the genomes of living things. The reason? It was assumed that getting new genes was hard, and once a workable solution was found it would be preserved in the descendants that followed. The bulk of genes would have been invented early in evolution, and thus would be broadly shared.

When It All Changed

But all that changed when many genomes were sequenced and their transcripts analyzed. Each genome, or each taxonomic group, such as bivalves or insects, was found to contain unique genes, found only in that group or species. This was a surprise. At first it was attributed to incomplete sampling. As more genomes were sequenced, it was thought, the uniqueness would turn out to be illusory. Other organisms would carry those genes. As a related explanation, the sparsity of their distribution might be due to horizontal gene transfer, or to gene loss. The hypothesis was that what appeared to be unique was so because it was the result of some rare transfer between species, and we hadn’t identified the source. Or what once was widespread had been lost over evolutionary time.

These explanations are not proving true. First, the more genomes that are sequenced, the more the proportion of orphans should shrink, as more and more “orphans” should be shown to be present in other genomes. But that has not proven to be the case. The mountain of orphan genes is growing, not shrinking. Similarly, horizontal gene transfer was not born out. The sister genes of orphans should have been found as sample size increased, reducing the proportion of orphan genes. As for gene loss as an explanation, it would have to be too massive to be realistic to account for the patterns seen.

One last possibility. The orphans could be related to other genes, but their sequences could have diverged so much as to be unrecognizable. Only their protein structures might reveal relatedness. This also has not been born out by studies that have determined structures of orphan proteins.

A Sea Change in Evolutionary Thinking

So what’s the solution? If you are an evolutionary biologist, it’s simple. You decide it must be easy to get new genes directly from random (non-coding) DNA, or by frameshift or overlapping genes (which amounts to random sequence). This represents a sea change in evolutionary thinking.

Now hold it. Saying that it’s easy to get new genes from DNA by those methods overturns a major Darwinian expectation. In 1977, in his famous article “Evolution and Tinkering,” which has been cited many thousands of times, the Nobel laureate François Jacob explained the accepted view of how evolution constructed new genes:

…once life had started in the form of some primitive self-reproducing organism, further evolution had to proceed through alterations of already existing compounds. New functions developed as new proteins appeared. But these were merely variations on previous themes. A sequence of a thousand nucleotides codes for a medium-sized protein. The probability that a functional protein would appear de novo by random association of amino acids is practically zero. In organisms as complex and integrated as those that were already living a long time ago, creation of entirely new nucleotide sequences could not be of any importance in the production of new information. 

New genes must arise from pre-existing genes, leaving the signal of ancestry in their closely related (i.e., homologous) sequences, because the probability of the alternative is “practically zero.” That’s why the discovery of orphan genes, which show no homology to other sequences, came as a great surprise.

No Problem, You Say?

“No problem. Isn’t that what science supposed to be about?” said one evolutionist to me. “Adapting your theory to fit the facts?”

Well, theories have to be amenable to falsification too. They can only bend so far.

So how can we tell whether genes are easy to get or hard? By testing these alternatives in the lab.

At present the preferred theory for the birth of new genes is to take a stretch of DNA that is currently not being transcribed into RNA, then let it acquire the signals necessary for transcription, then have that new transcript have a function, either as an RNA or after being translated into protein. 

This is in fact how many orphan genes are found. An RNA transcript is made in one species from a stretch of DNA that in a sister species does not make RNA. Further work then determines if the RNA is translated into protein, and ultimately, if the protein has a function.

But in order for this scenario for orphan gene creation to work, functional protein sequences have to be easy to acquire, within reach of an evolutionary search starting from an existing non-functional stretch of DNA. Evolutionists tend to think that such a thing happens easily. Evolutionary processes can produce a new gene or structure or chemical activity easily. This must be true if evolutionary processes are the explanation for orphan genes.

The Rarity of Functional Protein Folds

In contrast, ID proponents think that it’s very difficult to get function from random sequence. There’s a definite reason for this. Experiments by Dr. Douglas Axe measured the rarity of functional protein folds in sequence space (only 1 in 10^77 proteins form a fold with a target function, a very, very, very small number). If functional proteins are very rare in sequence space, that makes it very difficult to get new genes or structures or chemical activities. Others have found similar answers, when asking for the requirements to produce an enzymatic activity. Others, when asking for simple kinds of activity, like sticking to a column loaded with a substrate like ATP, get numbers that are conceivably within range of evolutionary processes. Just sticking to a column is not nearly as demanding as carrying out an enzymatic reaction. 

There are strong points of view as to the reliability of the various methods. How the various experiments are judged tends to be influenced by one’s particular view on the question of evolution. So the best thing is to do more experiments, which is precisely what the scientific community is doing. 

Work is in progress now in many labs to test the question of how hard it is to get an orphan gene from non-coding sequence. Some are asking how hard it is to get a promoter (necessary to promote active transcription). Some are asking how likely it is for random sequence to have function. The sticking point, literally, seems to be that random sequences don’t fold properly and are insoluble in water. They aggregate. That makes most kinds of function difficult, to say the least. Lastly, how likely is it that the function will actually be helpful? We’ll see.

The answer is not in. If Doug Axe is right (and remember, he is not the only researcher to have found that functional proteins are very rare in sequence space), then getting an orphan gene by an evolutionary process is extremely unlikely. But orphan genes are possible, maybe even to be expected, when a designing intelligence acts.