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What would count as ‘new information’ in genetics?

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Published: 26 November 2019 (GMT+10)
new-information-genetics123rf.com

As biblical creationists, we often like to point out that ‘information’ is a notoriously hard-to-define term. Several authors have tried to grapple with this. As far back as 1993, Walter ReMine wrote a book called The Biotic Message that explained what type of information we would expect to see if a Designer had created life. Since then, Werner Gitt has given us the Scientific Laws of Information, and Royal Truman has written extensively on Information Theory. Hence, creationists talk about information, a lot.

This will often start an argument. Darwinists rarely, if ever, talk about ‘information’. They are quick to point out that DNA can change. Thus, they claim, there is either no ‘information’ in DNA or the information can be seen to change in a Darwinian fashion. Some creationists like to say, “Mutations cannot create information. They only destroy information.” But this is a very weak argument. All the evolutionist has to do is point out an example of a DNA duplication and, suddenly, there is an “increase” in information content.

It is true that the information content of the cell can change, and it is true that mutations may add ‘information’ to the genome.1 However, as I (RC) wrote, the changes we see are not “the types of information-gaining mutations necessary for large-scale evolutionary processes.”2 There are several known examples of mutations that allegedly cause a gain of function, but these arose from corrupted genetic information. For example, recent work done at Delft University of Technology in the Netherlands, published earlier this year, claimed to show the evolution of a brand-new gene that conferred the ability to digest a new type of sugar upon yeast. However, Cserhati’s and my (RC) analysis concluded that the study “only demonstrated that existing genetic information can be reshuffled.”3 There are many similar examples in the scientific literature, but they do not represent anything genuinely new. Yet, clearly, all our genetic information had to come from somewhere, originally.

Information is impossible to quantify!

Skeptics often challenge creationists, “If information is decreasing, what is the rate of its decrease?” Another similar objection is, “Can you quantify the changes in the information content of the cell?”

This line of questioning successfully cuts to the heart of the matter. They claim our inability to define information robustly means information does not exist. We claim the information content of living things disproves random mutations as the source of that information. Who’s right? The most difficult area in the debate over information comes down to our ability (or lack of ability) to definitively define or quantify biological information. As I (RC) wrote,

When dealing with this subject, in most cases evolutionists use a statistical measure called Shannon Information. This was a concept invented by the brilliant electronic engineer C.E. Shannon in the middle of the 20th century, who was trying to answer questions about how much data one could stuff into a radio wave or push through a wire. Despite common usage, Shannon’s ideas of information have little to do with biological information.2

Why would we say Shannon’s ideas have little to do with biological information? Because Shannon’s measure was not truly a measure of information (in the sense of immaterial ideas), but rather a quantification of things that lend themselves to simple metrics (e.g. binary computer code).

For example, the English word “squirrel” and the German word “Eichhörnchen” both ‘code for’ the same information content (they refer to the same animal), yet if we use a Shannon measure we will get different results for each word because they use different numbers of letters. In this way we can see that any way of quantifying information that depends upon counting up letters is going to miss the mark. There is something intangible, immeasurable even, in the concept of ‘squirrel’. We humans have the habit of arriving at a conclusion (i.e. “That is a squirrel”) without bothering with the details (i.e. “What is the information content of that small gray rodent?”). We intuitively understand abstract levels of information, yet we struggle to define what it means at the most basic level.

So, on the one hand, the answer is no. When considering the decay of biological information over time, we cannot quantify the rate of decrease, because information, at its base, is an immaterial concept which does not lend itself to that kind of mathematical treatment.

On the other hand, the answer is yes, we can sometimes quantify information when we have something simple to measure. Biologists have long struggled with quantifying what they are studying. They can measure the size or shape of a wing, or the lifespan of an animal in the wild. That is not hard to put a number on. But they cannot say how much ‘information’ is in the genomes of living things. We can create summary statistics of things in the genome, and use that as a proxy for the information content, but this is only scratching the surface.

Let’s illustrate that information can increase and decrease

What quantity is the color red? Or the feeling of sadness? These are concepts, and information is conceptual. Yet, paradoxically, it obviously can both increase and decrease in both quality and quantity!

How do you quantify ideas? How many ideas have you had in your mind so far today? This is the quandary: it’s self-evidently true that ideas are quantifiable in the sense that they can increase or decrease in number and clarity. Perhaps a couple of clear examples of information increase will suffice to make the point:

Example 1:

A man in a coma, existing in a dreamless unconscious state, compared to a man who is conscious

During a 24-hour period, which of these two men will have had more information, or ideas, go through their minds? The answer is clearly the second man. The first man will not have had any information in his mind during that period of time.

Example 2:

A 30-page children’s book compared to a 1000-page encyclopedia

Which of these two books contains more information? Clearly the second. Yet how do you quantify this difference in information without resorting to quantifying the medium (like counting pages or counting words or counting letters)? It is entirely possible to convey more information in fewer words, so how can one know the children’s book has less information? Word count cannot tell you, but in this case you intuitively know it at a glance.

Information is carried in so many complex ways (syntax, grammar, contextual clues, etc.) that it staggers the mind to contemplate actually trying to quantify it in an objective way. Yet this is what the skeptic asks us to do. This is an attempt at obfuscation to avoid grappling with the obvious fact that life is built upon the foundation of information. In fact, life is information.

Is our DNA code really ‘information’?

Some skeptics will resort to simply denying that the DNA truly carries any information, claiming this is just a creationist mental construct. The fact that DNA data storage technology is now being implemented on a massive scale is sufficient to prove that DNA stores data (information).4 In fact, information can be stored more densely in a drop of DNA-containing water than it can on any computer hard drive. To allow that humans may use DNA to store our own digital information, yet to disallow that our genomes contain ‘information’, would be a blatant instance of special pleading.

What would a real, genuine increase look like?

To get back to the skeptics’ main question: what would real increases in information look like? I submit that to answer this, just sit at a computer and watch yourself type out a paragraph in a word processor. Mutations are incremental; they are small changes that happen in a stepwise fashion as cells divide and generations multiply. The genetic code consists of letters (A,T,C,G), just like our own English language has an alphabet. But here is the central problem—it takes hindsight to recognize whether function or meaning is really present. Watch this transformation:

--Begin--

1 H

2 HO

3 HOU

4 HOUS

5 HOUSE

--End--

At what point in that series did you understand the meaning? Perhaps you guessed it at step 4, but you would have been lucky, for you did not know if a word like housing or household was about to appear. It didn’t become totally clear until step 5, when a full word was spelled and the program ended. There’s no real way to say, before you’ve already reached step 5, that ‘genuine information’ is being added. Mutations suffer from this same problem. But there’s an even bigger problem: in order to achieve a meaningful word in a stepwise fashion (let alone sentences or paragraphs), it requires foresight. I have to already know I want to say “house” before I begin typing the word. But in Neo-Darwinism, that is disallowed. Mutations must be random and unguided. Due to the sheer number of possible nonsense words, you cannot expect to achieve any meaningful results from a series of random mutations.

What if you were told that each letter in the above example were being added at random? Would you believe it? Probably not, for this is, statistically and by all appearances, an entirely non random set of letters. This illustrates yet another issue: any series of mutations that produced a meaningful and functional outcome would then be rightly suspected, due to the issue of foresight, of not being random. Any instance of such a series of mutations producing something that is both genetically coherent as well as functional in the context of already existing code, would count as evidence of design, and against the idea that mutations are random.

Natural selection is not random, but neither can it create information

Darwinism requires that random mutations over long periods of time create decidedly non-random sets of information. The skeptic may retort here, “Yes, but evolution is not random because natural selection is not random.” Yet, natural selection cannot come to the rescue here, because it is a mindless process with no foresight or agency. It is just a term referring to the differential reproduction that happens naturally in the world. “Differential reproduction” is not a mind with foresight that can implement meaningful concepts over time. In fact, as Sanford points out in his book Genetic Entropy, natural selection cannot “see” most mutations, since their effect is so small as to have no appreciable impact on the overall phenotype of the organism. He referred to this as the ‘Princess and the Nucleotide Paradox’.5 So even if natural selection is not ‘random’, so what? It is powerless to stop the slow degradation of genetic information in the first place.

Gene duplications do not change the overall picture

Another escape for the evolutionist is to appeal to gene duplication, which we know happens from time to time.6 But duplicated genes are ripe for deletion (because one copy is not needed), and deletion mutations are quite common.7 Point mutations are also common, much more common, in fact, than duplications. And most point mutations do not have a profound enough effect to be acted upon by natural selection:

“In terms of evolutionary dynamics, however, mutations whose effects are very small … are expected to be dominated by drift rather than selection.”8

Thus, the duplicated gene still cannot escape the problem of genetic entropy. Also, since gene copy number has a dramatic effect on cellular control, most gene duplications are probably harmful. Down Syndrome is a classic case of a nearly fatal duplication that has a drastic effect on phenotype. Individuals with Down Syndrome have an extra copy of one of the smallest chromosomes, 21, which carries maybe 300 genes.

The “information” argument cannot be answered by the evolutionist, yet neither is it easy to define for the creationist; but it is self-evident that information exists (in general), is present as the foundation of our genetics, and can both increase and decrease in quantity (regardless of our ability to define a precise rate for it). As Gerrish et al. wrote,

“Even the simplest of living organisms are highly complex. Mutations—indiscriminate alterations of such complexity—are much more likely to be harmful than beneficial.”9

This underscores the fact that evolutionists have an insurmountable hurdle in attempting to explain the origin of the vast quantities of complex functional information in the genome.

Ultimately, it is not science that determines what people believe about the past; it is their heart. Will they accept the testimony of both reason and Scripture, or will they grasp at straws to deny these by claiming that life needed no Designer?

References and notes

  1. Hsieh, P. et al. Adaptive archaic introgression of copy number variants and the discovery of previously unknown human genes, Science 366(6463):eaax2083, 2019; DOI: 10.1126/science.aax2083. Return to text.
  2. Carter, R., Can mutations create new information? J. of Creation 25(2):92–98, August 2011. Return to text.
  3. Cserhati, M. and Carter, R., New sugar transport gene evolved in yeast? 23 July 2019. Return to text.
  4. Lee, S., DNA Data Storage Is Closer Than You Think, scientificamerican.com, 1 July 2019. Return to text.
  5. Sanford, J., Genetic Entropy, FMS Publications, pg. 47, 2014. Return to text.
  6. Feuk, L., Carson, A.R., and Scherer, S.W., Structural variation in the human genome, Nat. Rev. Genetics 7(2):85–97, 2006. Return to text.
  7. Conrad, D.F. et al., A high-resolution survey of deletion polymorphism in the human genome, Nature Genetics 38(1):75–81, 2006. See also the other two papers on deletions in the human genome in that same issue by Hinds et al. and McCarroll et al. Return to text.
  8. Shaw, R. et al., What Fraction of Mutations Reduces Fitness? A Reply to Knightley and Lynch, Evolution 57(3):686-689, 2003. Return to text.
  9. Gerrish, P., et al., Genomic mutation rates that neutralize adaptive evolution and natural selection, J. R. Soc. Interface 10(85): 20130329, 29 May 2013; DOI: 10.1098/rsif.2013.0329. Return to text.

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