Genetic Entropy and the Mystery of the Genome
Genetic Entropy and the Mystery of the Genome details compelling new genetic evidence that the human genome is deteriorating, and has always been deteriorating due to accumulations of mutations. The more scientists discover about the human genome, the less plausible Darwinism is. Dr. Sanford systematically lays out the scientific case against mutations resulting in the origin of species. A must read for every biologist or person interested in biology.
Sanford mentions at least eighteen ways in which theoretical genetics attacks the theory of evolution (reviewer’s count):
1. The incredible amount of information available in every cell seems unfeasible to have only come from genetic misspellings which are then selected.
2. Beneficial mutations are very rare, much too rare to support evolution.
3. Beneficial mutations generally fall in the neutral, ‘not selectable’ range of mutations and so could not help evolution.
4. Bad human mutations are at a rate much higher than expected, implying deterioration rather than evolution.
5. Neo Darwinism is based on 4 faulty premises, (1) Each nucleotide sorts independently.
6. Faulty premise (2) Genes do not change the function of other genes.
7. Faulty premise (3) Evolution acted on essentially infinite populations of organisms.
8. Faulty premise (4) The selection had unlimited time to act.
9. Natural selection is limited by three factors: (1) the cost of selection (Young creatures removed aren’t available for population increase, and fitness has low heritability),
10. Limiting factor (2) gene mutations usually don’t greatly affect the body of the animal but only the body determines how selection works , and
11. Limiting factor (3) the difficulty in keeping mutant animals from mating (preserving the bad mutation) without human intervention.
12. The Crowe model of removing animals which concentrate many bad mutations, does not improve the population but only allows it to continue at a lower level of fitness.
13. Even just creating one beneficial nucleotide by chance takes too long to help evolution let alone many beneficial nucleotides.
14. Good genes spread too slowly through a population to help evolution.
15. Fitness valleys caused by partially formed traits would tend to be destructive for the developing population as it evolves.
16. Some bodily functions are from polyfunctional DNA that can’t change the coding for one function without destroying another functionality that comes from the same segment of DNA.
17. Some functions are irreducibly complex in that the function needs a large group of nucleotide changes all at once in order to appear.
18. Bad mutations tend to accumulate in any given genetic block faster than good mutations.
Dr. John Sanford spent most of his career as a researcher with Cornell University working with plants in the hope of developing new strains. He mentions working with transgenic plants, and using radiation to develop mutations in plants.
Late in his career, Dr Sanford started to question the basic axioms of evolution even though he was well known in the field of Applied Genetics. Over several years, to answer his own questions, he went back and studied theoretical and population genetics, which he had always accepted by faith alone. He fully expected to hit a brick wall of support for evolution but discovered that theoretical genetics, though straightforward, was no friend of evolution. He came to believe Darwinian evolution is an extremely vulnerable theory and is essentially indefensible.
His book is well written, and surprisingly easy to understand even though it has many new concepts for us who are laymen. His conclusions are convincing and easy to understand. He shows sixteen different ways in which theoretical genetics attacks the theory of evolution, and concludes that modern genetics says that species on Earth are degenerating genetically and not improving.
Occasionally, the organization of the book falters, confusing the reader about whether one argument springs out of the previous one, or is a new line of attack. Sanford seems to struggle with the depressing feel of his conclusion (that our genome is degenerating), where a different principle of organization might relieve the tension.
Sanford says the genome is like an instruction manual for how to make cells, and compares it to all the instruction manuals needed to build a space ship, including manuals on how to build the factories to make the parts. The cell’s information system is so involved that it is much more complex than anything man has designed. The problem is discovering where all this information came from. He critiques the ‘Primary Axiom’ that life is life because random mutations at the molecular level are filtered through a reproductive sieve on the level of the whole organism (p.5).
Chapter 1 Explains what a genome is and compares it to the manuals and books necessary to provide the information to construct something, whether a little red wagon, a jet fighter, or a starship.
Chapter 2 explores whether random mutations can be good or not. Sanford notes that you can rate mutations in terms of how helpful they are. The zero rating is for mutations that are neither good nor bad. A very bad mutation that could kill an animal gets a negative number, while a good mutation would be positive.
Most mutations are nearly neutral, very close to zero just as most misspellings would not really hurt the information content of a book. If there were equally as many good mutations as bad mutations, Sanford says evolution would really be a possibility (p. 29). However, "Beneficial mutations are so rare that they are typically never even shown in such graphs" (p. 21).
For a certain distance around zero you have the effectively neutral zone, mutations that make so little difference (either good or bad) in the life of the organism that they cannot be selected by natural selection. These mutations just drift out of the population over generations, and are lost. Sanford says that it shocked him to realize that nearly all beneficial mutations fall within this effectively neutral zone (p. 24).
Sanford illustrates this by the search for beneficial mutations of corn. The only one found was low phytate corn which is useful for some animal feed (p. 25). Yet even this mutation was essentially a loss of information, rather than a mutation that gained information even though it turned out to be useful. So, while there are some beneficial mutations, they are much too rare to build a genome. Their rarity makes evolution virtually impossible (p. 32).
Chapter 3 discovers that human mutation rates are much higher than evolutionists expected. Evolutionists thought one bad mutation per person each generation would mean the human race would deteriorate over time (p. 33). Sanford cites one study that concluded that if the human mutation rate were as high as 30 (of the 3 billion possible nucleotides), it would have grave or profound implications for evolutionary theory (p. 34). Scientists recently discovered that the human mutation rate is at least 100 per person per generation and probably closer to 600 (p. 36). This implies that the humans aren’t evolving, but getting worse.
Chapter 4 questions whether natural selection (or even guided selection) could halt genetic deterioration. Sanford points out that natural selection is based on whether a whole organism lives or dies, and not just the survival of some specific gene. Sanford says that even as a geneticist he had a naïve, unrealistic view of how natural selection would function when applied to the whole genome (p. 46).
When scientists rediscovered Mendel and genetics, it caused a big problem for Darwinism, since a large number of heritable units means nature finds it harder to decide which are good and which are harmful. To solve the problem, population geneticists such as Haldane, Fisher and Wright, reinvented Darwinism as Neo-Darwinism. They decided to look at organisms as pools of genes, and then they could say that selection operates on the individual genes rather than worrying about the whole organism (p. 52). Sanford lists four assumptions they made to do this; (1) each nucleotide sorts independently, (2) no interactions between nucleotides, (3) essentially infinite populations, and (4) unlimited time (p. 53). However, all four assumptions are now considered unreasonable, so that practically, “natural selection can never create, or even maintain, specific nucleotide sequences.” (p. 55)
Three problems limit the power of selection; (1) the cost of selection (young creatures removed aren’t available for population increase, and fitness has low heritability), (2) the gene mutations don’t greatly affect the body of the animal, and (3) the difficulty in keeping mutant animals from mating (pp. 56-62). Sanford is careful to say that natural selection does work to remove the worst mutations, and selection does work to reinforce gene sequences, but “both natural and artificial selection have very limited ranges of operations” (p. 63) So, selection does not have the omnipotent power often ascribed to it
Chapter 5 focuses on humans to see if selection can rescue the human race from genomic problems. Sanford believes that what we have learned in the last few decades makes things much worse for evolution. The genetic cost of selecting out the many mutations we know exist in the human race is higher than the number of people we could lose and still maintain population size (p. 71-72). Bacteria, because of their large population and independent selection of each cell, are more resistant to genetic drift. Mammals do not have this advantage, so microbial examples do not translate well to human realities genetically (p. 74).
The larger the number of mutations you have, the more difficult it is to efficiently select them out of the population (p. 77). In fact, some selections must interfere with other selections so that removing bad mutations could cancel out any good mutations that come along (p. 82).
Chapter 6 looks at noise (unintended effects of genes and environment) in heredity and concludes that random variations cover up the signal of individual nucleotides. The signal to noise ratio in genetics is called “heritability” (p. 90). The more a trait is affected by environment, the less heritable it is. Thus, blood type has a heritability of 1 (not affected by the environment), a tattoo has nothing to do with genetics and has a heritability of 0, and intelligence is in the middle because it depends on nutrition, and environment as well as genetics. Traits such as size and growth in trees may depend more on where the seeds landed than on their genetics. Fitness, as calculated by Kimura, a well known Population Geneticist, generally has a very low heritability (.004) because so much depends on luck and environment (p. 91).
Sanford notes that as a plant breeder he scored hundreds of plants and eliminated those below a certain level, but nature does not do this. Inferior seedlings may very well reproduce while better ones may not (p. 94). This is probability noise. Finally, the chance of a certain gene being expressed in a descendant depends on the probability of gametic sampling (recessive genes are expressed with a certain, lower probability).
Population geneticists often only calculate gametic sampling noise because it disappears in large populations, but probability noise and fitness heritability noise do not disappear in large populations (p. 97). Plant and animal breeders can limit noise, but natural selection cannot and selection cost is increased. “If noise routinely overrides selection, than this makes long term evolution impossible, and guarantees genetic degeneration.” (p. 99)
Chapter 7 examines the model described by Dr. James Crow who noted that if bad mutations accumulated in some individuals who then died, it would remove a large enough number of mutations from the population that degeneration would stop. Sanford notes that this does not improve the population but only allows it to continue at a lower level of fitness. To reach the point where some individuals accumulate large numbers of bad mutations every individual must accumulates a fair number of mutations though some accumulate more. This in no way works toward the betterment of the population, but does allow it to survive.
Chapter 8 examines whether man can stop the decline by eugenics or cloning, and concludes that neither one can prevent eventual degradation of the human genome.
Chapter 9 explores whether natural selection can create genes. Sanford looks at the question by saying, if there were no deleterious genes, but only beneficial mutations, could natural selection create a gene?
He starts by trying to define the first beneficial mutation, and points out that any new nucleotide must be analyzed by looking at how it affects its neighbors. However, to create a new function you must change most of the neighbors. How can nature pick which nucleotide must be first when you need a string of, say 50 nucleotides to have a new function for the organism? You need a pre-existing concept to guide you before you can efficiently start the process of mutations.
In humans, in a population of 10,000, you will wait 3,000 generations for a specific nucleotide to mutate (p. 125). However, it has only one chance in three of mutating to the nucleotide you want. Also, it must be a dominant gene to slowly appear in enough of the population to not be lost by chance, but even so it will be lost to the population 99 times out of 100 (p. 126).
Most genes have at least 1,000 nucleotides, so that the calculated time for a new gene to appear would be nearly 12 billion years, much too long to encourage evolution. Some have argued that different individuals in the population could have the right mutations, which would splice together in their offspring, shortening the time needed. However, the human genome exists in large blocks of more than 20,000 nucleotides, in which no recombination has occurred since the origin of man (p. 127). Most genetic shuffling is only of large size genetic blocks, so that shuffling actually would take longer to develop a new gene than the sequential approach.
At a guess, a dominant gene which occupies 10% more of the population each generation would still need 105 generations to occupy the whole population of 10,000. A recessive gene would take 100,000 generations. This slow rate of fixing mutations in a population is known as “Haldane’s dilemma” because it takes so many generations for a large number of mutations to be fixed (1000 mutations would take 6 million years for humans, the time in which we supposedly evolved from chimps) (p. 128). Sanford notes that “simultaneous selection does not hasten this process” (p. 128). Remember that this is without deleterious mutations.
Sanford points out that most evolutionists agree that while a new trait is in construction, the species has a time of lower fitness called a ‘fitness valley’ (a half completed gene is likely to be hurtful until it is fully functional). However, long, deep, fitness valleys lead to extinction. Some evolutionists claim there is continual innovation, but that means continual fitness valleys which lead down and not up.
Since some portions of DNA are poly functional (they can be read in two different directions, or from two different starting points), a random change causes much more damage. A misspelling in a sentence will probably not hurt much, but one wrong number in a magic square ruins it.
Irreducible complexity is a problem for evolution; some functions simply cannot be built one nucleotide at a time, but must appear completely made. Removing one part from a mouse trap invalidates the whole mechanism, so all the parts must be available and joined at once to function correctly (p. 136).
Sanford also points out that ‘Muller’s ratchet’ means bad mutations accumulate in a block, faster than good ones, and genetic hotspots don’t help because during the time that mutations must form in the ‘cold’ areas, the hotspots have already changed back again. Sanford believes that all this evidence, taken together “constitutes what is essentially a formal proof that the Primary Axiom is false.” (p. 138) (the primary axiom being that mutations plus selection explain all life). He feels that the genome had the most information at the beginning, but develops the most diversity later with time, without new information being needed.
Chapter 10 summarizes the book, pointing out that aging and genomic deterioration are really the only conclusions to be drawn from our present scientific evidence. The genome’s existence is a mystery which apparently could only have arisen by design and never spontaneously.
Sanford includes a personal postlude about the hope that he found in Jesus Christ, and offers Him as the only reasonable hope we have. The book has four appendices which document and explain even further the concepts referred to in the book. The fourth appendix especially looks at answers to objections raised.