Can random mutations cause an increase in information in the genome?

Instead of quibbling over whether you think the definition of information is precise enough, why don't you guys try answering the question.

The data on how to determine this is provided in one of my previous posts. Have at a ranking list if you like.I'm afraid you're still missing the point though. The amount of information content relative to different types of animals is not important. The fact that they have different information is all that is important. For instance, a pig doesn't have the genetic instructions needed to generate wings (until pigs fly that is). Conversely, a bird has no genetic instructions for a little curly tail.

Message 56 of 56
02-14-2006 01:39 PM Reply to: Message 50 by Jazzns
02-14-2006 01:08 PM IP Logged
Re: Creationist and their misuse of "information"
Let's use this sentence as an example. Forget about biology for a second...simple information theory here(and yes it's off topic slightly):The quick brown fox jumped over the lazy dogLet's duplicate part of it and add it back in, much in the same way a random change to the sentence may do.The quick brown fox lazy dog jumped over the lazy dog

Deoxyribonucleic acid (DNA) is a nucleic acid ”usually in the form of a double helix” that contains the genetic instructions specifying the biological development of all cellular forms of life (and most viruses).

As to evolution being a fact...you are obviously referring to microevolution (ie. adaptation, natural selection) since macroevolution (ie. goo-to-you) is completely unrepeatable. You truly don't even understand my argument. Evolutionists like to remind you that microevolution is fact then suggest that proves macroevolution.

As to why a species can't acquire information...it's because no known natural process can create specified complexity. In other words, no unintelligent process would know how to arrange the strand in an order that had any meaning to the translator.

Hmmm...can you define "random" for us here so that we have precise definitions to work with?

It's clear that in the evo models, natural selection is guided by pressure from the environment (and the local environment also guides the mutations we are learning. We also know the environment is formed from the actual physical make-up of the universe. In order to assert mutations are really random, you have to assert that the formation of the universe is random, and I think that's logically off the reservation. The universe itself exhibits rules, laws, order, etc,....what causes inanimate energy to order itself?In biology, we say the organism's programming to survive (which to my mind is evidence of ID all on it's own), but what created the rules of matter and energy to be ordered by, and matter and energy itself?I think the logical inference is an Intelligent Cause did, and so regardless of the mechanisms, whether evolution or direct creation, imo, it is all Intelligent Design because even in the evo model, the underlying guiding factor for life evolving are the physical (including QM), chemical, and environmental factors in place, and these things do not demonstrably have an origin in randmonness.In other words, the random aspect is a massive assumption on the part of evos without any evidence or logic whatsoever. If, and this is a big if, life forms only through "naturalistic means", then that is still evidence of design because the design of the universe itself in it's origins dictates what designs can flow out of it.

Except that we detect that mutations are randomly distributed. Pseudorandomly, at least. (Pseudorandom numbers, for instance, would be strings of numbers that are deterministically generated but statistically indeterminable from a truly random sequence. By definition there's no way to distinguish a random sequence from a pseudorandom one after the fact.)

Evolution = NS(RM, OS)where f is a non-trivial function, NS is natural selection and is not random, RM is random mutations and is random, and OS is other stuff, some random, and some that is not random.That is, following Dawkins and many others, evolution is the non-random selection of random variation.In probability theory, it is known that if X is a random variable, then for a non-trivial function f, f(X) is a random variable. Therefore, because evolution is a non-trivial function of variables, some of which are random, evolution is a random variable, and therefore it is correct to call it random.To summarize, while evolution could reasonably be considered and described as biologically or practically non-random, it is technically, mathematically random. To say that calling evolution random is "the opposite of truth" and "false" could itself be viewed as the opposite of truth and false.

I am not sure though that these definitions are helpful. First, just because the organism has no control over does not rule out the mutation being part of an embedded design, or actually being the result of direct intelligent action.

It is hard to understand how anyone could make this claim, since anything mutations can do, mutations can undo. Some mutations add information to a genome; some subtract it. Creationists get by with this claim only by leaving the term "information" undefined, impossibly vague, or constantly shifting. By any reasonable definition, increases in information have been observed to evolve. We have observed the evolution of* increased genetic variety in a population (Lenski 1995; Lenski et al. 1991)
* increased genetic material (Alves et al. 2001; Brown et al. 1998; Hughes and Friedman 2003; Lynch and Conery 2000; Ohta 2003)
* novel genetic material (Knox et al. 1996; Park et al. 1996)
* novel genetically-regulated abilities (Prijambada et al. 1995)If these do not qualify as information, then nothing about information is relevant to evolution in the first place.# A mechanism that is likely to be particularly common for adding information is gene duplication, in which a long stretch of DNA is copied, followed by point mutations that change one or both of the copies. Genetic sequencing has revealed several instances in which this is likely the origin of some proteins. For example:* Two enzymes in the histidine biosynthesis pathway that are barrel-shaped, structural and sequence evidence suggests, were formed via gene duplication and fusion of two half-barrel ancestors (Lang et al. 2000).
* RNASE1, a gene for a pancreatic enzyme, was duplicated, and in langur monkeys one of the copies mutated into RNASE1B, which works better in the more acidic small intestine of the langur. (Zhang et al. 2002)
* Yeast was put in a medium with very little sugar. After 450 generations, hexose transport genes had duplicated several times, and some of the duplicated versions had mutated further. (Brown et al. 1998)The biological literature is full of additional examples. A PubMed search (at PubMed) on "gene duplication" gives more than 3000 references.# According to Shannon-Weaver information theory, random noise maximizes information. This is not just playing word games. The random variation that mutations add to populations is the variation on which selection acts. Mutation alone will not cause adaptive evolution, but by eliminating nonadaptive variation, natural selection communicates information about the environment to the organism so that the organism becomes better adapted to it. Natural selection is the process by which information about the environment is transferred to an organism's genome and thus to the organism (Adami et al. 2000).# The process of mutation and selection is observed to increase information and complexity in simulations (Adami et al. 2000; Schneider 2000

While it is true that most mutations are either harmful, as suggested by the creationists, or neutral, the creationists gloss over a crucial fact: beneficial mutations do occur, though they are very rare. Can a beneficial mutation that occurs once in million individuals ever really contribute to evolution? Yes it can, since a rare beneficial mutation can confer a survival or reproductive advantage to the individuals that carry it, thereby leading -- over several generations -- to the spread of this mutation throughout a population. Beneficial mutations occurring in several different individuals in several different genes can simultaneously spread through a population, and can be followed by successive rounds of additional mutation and selection.Does the fact that we know many human detrimental mutations but essentially no clear beneficial ones mean that there are have been no beneficial mutations in human history? Not at all, since there is a clear bias in what medical scientists have studied. The human mutations we know most about are detrimental because medical scientists preferentially study illnesses that cause significant morbidity and mortality. Consider the theoretical possibility that a beneficial mutation has occurred in a particular human gene; even if this mutation were identified by a comparison of the mutated gene in a child versus the unmutated version of the same gene in both parents, there is no way that this mutation could ever be recognized as beneficial. If the mutation increased intelligence, strength, longevity or specific disease resistance, this would never be apparent without long-term breeding experiments that could obviously never be done on humans. Therefore, since such beneficial mutations in humans could never be recognized in humans, our ignorance of examples cannot be taken as evidence that they don't exist. However, the experiments necessary to demonstrate a beneficial mutation can be done with laboratory organisms that multiply rapidly, and indeed such experiments have shown that rare beneficial mutations can occur. For instance, from a single bacterium one can grow a population in the presence of an antibiotic, and demonstrate that organisms surviving this culture have mutations in genes that confer antibiotic resistance. In this case (in contrast to the situation with the peppered moth populations described above) origin of the population from a single bacterium allows comparisons of the mutated genes with the corresponding genes from the original bacterium, verifying that the variant sequences were not present before the culture with antibiotics and therefore arose as de novo beneficial mutations.

While a detailed mathematical consideration of information theory is beyond the scope of this article, none of the creationist arguments based on information theory that I am aware of adequately address the obvious increase in information that can occur when a gene duplicates and the two copies undergo independent mutations leading to two genes with somewhat different functions. Gene duplication, mutation and selection are all known to occur due to natural biochemical processes in a variety of organisms studied in the laboratory. Many gene families are known with members that encode proteins having related structure and related but distinct function. Each family can be explained by multiple gene duplications followed by random mutation and differentiation of the functions of the individual gene copies. Clearly the expansion from a single primordial gene to a large family of genes with distinct functions represents an increase in genetic information.An example that I have already mentioned in another posting on Talk.Origins is the hemoglobin/myoglobin family. The gene for a primordial oxygen-carrying protein is thought to have duplicated leading to separate genes encoding myoglobin (the oxygen-carrying protein of muscle) and hemoglobin (the oxygen-carrying protein of red blood cells). Then the hemoglobin gene duplicated, and the copies differentiated into the forms known as alpha and beta. Later, both the alpha and beta hemoglobin genes duplicated several times producing a cluster of hemoglobin-alpha-related sequences and a cluster of hemoglobin-beta-related sequences. The clusters include functional genes that are slightly different, that are expressed at different times during the development of the embryo to the adult, and that encode proteins specifically adapted to those developmental periods. Other examples of gene families that appear to have developed by such duplication and differentiation include the immunoglobulin superfamily (comprising a large variety of cell surface proteins), the family of seven-membrane-spanning domain proteins (including receptors for light, odors, chemokines and neurotransmitters), the G-protein family (some members of which transduce the signals of the seven-membrane-spanning domain family proteins), the serine protease family (digestive and blood coagulation proteins) and the homeobox family (proteins critical in development). A large part of the increase in information in our genomes compared with those of "lower" organisms apparently results from such gene duplication followed by independent evolution and differentiation of duplicated copies into multiple genes with distinct function. If an information theory analysis claims that random mutation cannot lead to an increase in information but the analysis ignores gene duplication and differentiation through independent mutations, such an analysis is irrelevant as a model for gene evolution, regardless of its mathematical sophistication.

Definition of random process. A (one-dimensional) random process is a (scalar) function y(t), where t is usually time, for which the future evolution is not determined uniquely by any set of initial dataor at least by any set that is knowable to you and me. In other words, random process is just a fancy phrase that means unpredictable function. Throughout this chapter we shall insist for simplicity that our random processes y take on a continuum of values ranging over some interval, often but not always -8 to +8. The generalization to ys with discrete (e.g., integral) values is straightforward. Examples of random processes are: (i) the total energy E(t) in a cell of gas that is in contact with a heat bath; (ii) the temperature T(t) at the corner of Main Street and Center Street in Logan, Utah; (iii) the earth-longitude f(t) of a specific oxygen molecule in the earths atmosphere. One can also deal with random processes that are vector or tensor functions of time, but in this chapters brief introduction we shall refrain from doing so; the generalization to multidimensional random processes is straightforward. Ensembles of random processes. Since the precise time evolution of a random process is not predictable, if one wishes to make predictions one can do so only probablistically. The foundation for probablistic predictions is an ensemble of random processesi.e., a collection of a huge number of random processes each of which behaves in its own, unpredictable way. In the next section we will use the ergodic hypothesis to construct, from a single random process that interests us, a conceptual ensemble whose statistical properties carry information about the time evolution of the interesting process. However, until then we will assume that someone else has given us an ensemble; and we shall develop a probablistic characterization of it.