From ape to man via genetic meltdown: a theory in crisis
A review of Genetic Entropy & The Mystery of the Genome by John
C. Sanford,
Ivan Press, Lima, New York, 2005
by Royal Truman
I write this review with very mixed feelings. On the one hand, for the first time
some key data are being divulged which we need to include in our models, and which
honest thinkers who question evolutionist theory need to digest. But I have a problem.
In the Prologue professor Sanford wrote, ‘I knew I would be at odds with the
most “sacred cow” of modern academia. Among other things, it might even
result in my expulsion from the academic world.’ I know John personally
and treasure his intelligence and integrity. In further drawing attention to his
book, I may be contributing to having his ties to academia severed, a world to which
he has such strong emotional ties and to which he has made so many contributions.
I know academics and journalists who have already lost their jobs for questioning
Darwinian theory.
He is not exaggerating. I myself have also had my experiences in this matter.
‘I started to realize (again with trepidation), that I might be offending
a lot of people’s religion,’ he confides early on. How correct he is.
I recently discussed the issue of life’s origins with a dear friend I’ve
worked together with for years. He brought up three arguments contra creation
which I easily answered on strictly scientific terms. Suddenly he leaped to his
feet. Trembling with rage he pointed a finger at me, and yelled that what I was
doing was dangerous! The fundamentalists in America are dangerous!
They are fighting against tolerance! They refuse to accept science! They are irrational
and have no facts!
Dr Sanford is an applied geneticist semi-retired from Cornell University and now
with the Institute of Creation Research. He is also the inventor of the ‘gene
gun’, widely used in the genetic modification of crops. In this book the reader
is confronted with compelling reasons to reject the claim that mutations plus natural
selection have led to the marvels found in nature.
Many scientists do not believe man is merely the product of random mutations
plus natural selection, what Sanford calls the Primary Axiom.
One line of reasoning, that of irreducible complexity, has been very capably
championed by professor Behe:1 molecular machines require many complex components,
the absence of only one rendering that entity non-functional. Evolutionary processes
cannot be expected to provide the necessary building blocks.
Others have argued that the high fidelity of DNA replication leads to very low rates
of mutation. Developing humans from an ape-like forefather would just take
too long. In a much cited paper, Drake has estimated2 that the rate of spontaneous
mutations for humans is about 5 x10–11 nucleotides per generation. In some 6 million
years from a claimed split from the chimpanzee lineage, no humans could be generated
if this is true.
Sanford was a practising evolutionist and at heart a eugenicist (p. 116), who ‘gradually
realized that the seemingly “great and unassailable fortress” which
has been built up around the Primary Axiom is really a house of cards. …
Its apparent invincibility derives largely from bluster, smoke, and mirrors’
(Prologue). But we will learn that evolutionary theory fails on grounds most people
did not suspect.
Mutations are bad
Sanford forces us to recognize clearly that the relentless net effect of random
mutations is degradation or complete destruction of function.
Sanford forces us to recognize clearly that the relentless net effect of random
mutations is degradation or complete destruction of function. After decades of research,
if even one mutation out of a million really unambiguously created new information
(apart from fine-tuning), we would all have heard about it by now (p. 17). This
is to be distinguished from certain changes in for example bacteria (p. 19), which
merely fine-tune a component of a system already in place. The changes typically
involve modification of one or two nucleotides, and in huge bacterial populations
these are usually already present, a solution waiting for the precise niche. In
other words, ‘When we use a rheostat to dim a light, we are not creating a
new circuit, nor are we in any way creating new information’ (p. 19).
Mutagens have been used for years in plant breeding, creating billions of mutation
events: mostly small, sterile, sick, deformed and aberrant plants (p. 25). One improvement,
low phytate corn, was caused by mutations which damaged the metabolism of phytic
acid, making hungry cows happy, but hardly explaining the origin of this biochemical
process (p. 25). ‘However, from all this effort, almost no meaningful crop
improvement resulted. The effort was for the most part an enormous failure, and
was almost entirely abandoned’ (p. 25).
Indeed, no one is suggesting replacing incubators with X-ray machines to help evolution
along. On the contrary, health policies are in place aimed at reducing or minimizing
mutations (p. 15).
Disastrously high mutational rates
Now Sanford provides a key fact, inimical to evolutionary theory, but fully consistent
with the Second Law of Thermodynamics. The genetics community now accepts that point
mutations in human reproductive cells are in the range of at least 100–300
per individual each generation (p. 34). In fact, additional kinds of mutations,
such as deletions, insertions, duplications, translocations, inversions, micro-satellite
mutations and all mitochondrial mutations exacerbate the situation. Mitochondrial
mutations alone would add about another mutation per individual each generation
within the reproductive cell line, and macro-mutations can generate more sequence
divergence than all point mutations combined. The overall contributions imply more
than 1,000 nucleotide changes in every person, every generation (p. 37).
Using the unrealistic lower bound of 100 mutations, and assuming 97% of the genome
has no function, implies three new relevant mutations per individual each generation
are generated (p. 34). Before someone attempts to shrug off these new findings,
let us evaluate whether it is true that only 3% of the human genome is relevant.
If the percent is twice as high, then we would double the proportion at risk through
mutations.
Junk DNA or masterpiece?
The genome is full of countless loops and branches—like a computer program
using analogue and Boolean logic.
Driven by an incorrect model, genomes are generally characterized as chaotic and
full of meaningless evolutionary relics. The irony is that the more advanced the
organism, the more so-called ‘junk DNA’ is claimed to be present (p.
37). Perhaps we should be exposing our babies to radioactivity after all?! Biochemists
discover ever more complex metabolic networks, with elaborate regulatory schemes
to provide feedback inhibition or acceleration. The genome is full of countless
loops and branches—like a computer program using analogue and Boolean logic.
It has genes that regulate genes that regulate genes, able to set in motion complex
cascades of events (p. 3).
But the fact that research is steadily decreasing the proportion of supposed non-functional
DNA has not been properly integrated into evolutionist thinking. ‘In just
a few years, many geneticists have shifted from believing that less than 3% of the
total genome is functional, to believing that more than 30% is functional—and
that fraction is still growing’ (p. 21). Seriously now, when we examine organisms,
such as dolphins, swallows or humans, do we get the impression of final products
driven by a chaotic information processing system? In any event, in our thinking
we need to start getting used to the fact that over 30 new genetically relevant,
function-altering mutations occur per individual each generation.
Unity of complexity
Reductionist, materialistic thinking prevents more effective reasoning constructs
from being developed. If we could understand to the finest detail the properties
of all atoms in a computer we’d still fail to grasp the logic of algorithms
programmed to solve a mathematical problem. We would not even suspect its existence.
None of the individual components of an airplane can fly, but the integrated unity
can. The purpose of a back-up in-flight computer may appear to be ‘parasitic
junk’, especially if we limit our analysis to the material properties of the
atoms it is constructed with. When it is to be brought into action, why
and in response to what circumstances, would not be discerned by researching individual
characteristics such as atomic vibrations and molecular rotations and bond strengths.
Before we assume that the information in the genome used to generate mature organisms
is mostly junk, we would be wise to examine the final morphological product with
more humility.
Good and bad mutations inseparable
Are mutations really causing all that much damage? Many Hollywood stars (and my
wife!) sure seem awfully attractive. Since interchange of the genes provided from
the father and the mother occurs, might this not provide a means of avoiding passing
on defective genes? Might not ‘bad’ sperms and eggs lead to defective
offspring which simply don’t survive, leaving many ‘good’ versions
in the population? Well, unfortunately not. A huge number of mutations are added
to the germline of every baby born, and these are spread throughout the various
chromosomes. Human nucleotides exist in large linked clusters or blocks, ranging
in size from 10,000 to a million, inherited in toto, and never break apart
(p. 55, 81). A desirable trait will be accompanied by an undesirable trait, within
the same individual (p. 79).
Therefore, within any physical linkage unit, on average, thousands of deleterious
mutations would accumulate before a beneficial mutation would arise (p. 82). All
of the individual 100,000–200,000 linkage blocks in genomes are deteriorating.
Furthermore, recombination appears to be primarily between genes rather
than randomly between nucleotides. This means that an inferior gene is
doomed to remain in that lineage, unless a back-mutation occurs, which is vanishingly
unlikely. This means that the good mutations and the bad mutations cannot be separated,
another example of the one-way direction of degradation known as ‘Müller’s
ratchet’.
Being now clearly persuaded that the net effect of mutations will be loss of information-guided
functionality, we are ready to digest another insight. Tragic as a devastating mutation
may be to the affected and family, the effects of this ‘curse’ would
be limited to the victim if no offspring survive. But for the population as a whole,
the major damage turns out not to be the severe mutations.
Near neutrals
Figure 1. Far more mutations are deleterious than advantageous. Individually, most
have too small an effect to be acted upon by natural selection (p. 32).
The majority of deleterious mutations have individually a negligible effect on viability
of the organism. This is especially true if the ‘competitors’ are also
accumulating non-deadly but nevertheless undesirable mutations. This is like the
rusting of a car, one iron atom at a time (p. 72). Even one extra unnecessary nucleotide
is slightly deleterious—as it slows cell replication and wastes energy (p.
21).
This issue has been mostly ignored in the literature. Mutations in the ‘near-neutral
box’ (figure 1) are redefined as being completely neutral, and so dismissed.
It is then claimed that more severe mutations to the left of the near-neutral box
can be entirely eliminated by natural selection (p. 23). I supposed that if we are
talking about a very small number of mutations this would be to a first approximation
reasonable. But the accumulation of dozens or hundreds of such mutations every generation
presents a totally different picture.
Incidentally, we must remember that essentially all hypothetical beneficial mutations
also fall within Kimura’s ‘effectively neutral’ zone (p. 24).
Therefore, positive selection would also be too weak to have an effect!
It would be desirable if natural selection could remove at least some damaging mutations.
In fact, this remains our last hope to avoid a fitness meltdown. Before abandoning
hope, we need to consider natural selection carefully.
Natural selection is ineffective
The same environmental factor is unable to severely penalize different
deleterious mutations. It is not realistic to invoke strongly negative selection
to quickly eliminate a large number of unrelated mutations. As the number of minor
mutations increases, each mutation becomes noise for the others (pp. 77, 78).
Now, in a laboratory one can intelligently favour natural variability to accentuate
some chosen trait (p. 98). This requires carefully crafting the external environment
(nutrition, temperature, natural enemies, etc.) to minimize mutational noise. Nevertheless,
no one has ever claimed to have created brand new functions not already coded for
on the genome in this manner. And inevitably the organisms fine-tuned in the laboratory
for a single trait are less viable long-term, living freely in nature where all
natural ranges of environmental challenges occur. It is possible to optimize things
such as the amount of sugar a beet produces, as long as this plant is later protected
from full competition with the original stock. The changes may be in man’s
interest, but at the price of the organism’s natural fitness (e.g. the large
sugar production might result from a mutation damaging its control mechanism so
it over-produces; in the wild, this could not compete because it is wasting valuable
resources).
Outside of the laboratory the matter is much worse. There is no intelligent guidance.
The judge is also nearly blind (p. 7). There is a very long chain of events separating
the direct effects of a genetic change and the consequences for the whole organism
level. There is a logarithmic dilution at each step, a huge loss of cause-effect
resolution and correspondence. ‘It is like measuring the impact of a butterfly’s
stroke—on a hurricane system which is a thousand miles away’ (p. 49).
‘It is a little like trying to select for a specific soldier, based upon the
performance of his army’ (p. 49).
The literature is full of statements and abstruse computer programs claiming natural
selection can perform near miracles.3–5 But after 25 years of searching,
I have yet to find an analogy or computer model backing up this claim which has
any biological relevance. Generally it is enough to simply ask what kind
of organism would be suitable to check and perhaps calibrate the claims against,
to reveal the irrelevance. Sanford offers an illustration of how natural selection
really works, which reflects formally the issues involved very realistically, which
I will modify to maximize correspondence to how selection really works in nature
(p. 50).
Let’s imagine a new method for improving biochemistry textbooks. A few students
are randomly selected who will get a biochemistry textbook each semester during
the next four years, whether or not they take a biochemistry course. Each new book
will have 100 random changes in the letters. Those receiving the textbook are forced
to read it (whether they take the biochemistry course or not). Different teachers
assign grades to all courses taken by all students across the country each semester
(whether they received the biochemistry textbook or not). The correlation between
true ability and each grade (math, history, Latin … ) is weak and often wrong.
At the end of the semester we compare the average grades of all students nationwide
and identify from among the best students those in possession of a mutated biochemistry
textbook. Each of these latter textbooks are borrowed, 100 new random changes are
made, and then returned to the owner. The whole cycle of reading and grading is
repeated, multiple times. Will a better textbook result in this manner? No, since
there is no meaningful correlation between the small differences in textbooks and
the grades. Too many other factors (‘noise’), such as home life, lack
of sleep, classroom setting etc. override the effect of a few misspellings.
Any trait such as intelligence, speed or strength depends on gene characteristics
and environmental factors (nutrition, training, etc.) (p. 90). For example,
height is about 30% (h2 = 0.3) heritable. For complex traits such as
‘fitness’ heritability values are low (i.e. 0.004). ‘This is because
total fitness combines all the different types of noise from all the different aspects
of the individual’ (p. 91). Low heritability means bad genotypes are very
difficult to eliminate. Survival becomes primarily a matter of luck, and
not better genes:
‘If Kimura’s estimate is correct, then 99.6% of phenotypic selection
for fitness will be entirely wasted. This explains why simple selection
for total phenotypic fitness can result in almost no genetic gain.’ (p. 93)
Natural selection is a probabilistic matter. ‘Mother Nature’ does not
compute for each member of a population a ‘total fitness value’ based
upon all phenotypic traits (p. 94).
Furthermore, almost all mutations are recessive, camouflaging their presence and
hindering selection against them (pp. 56, 76). Another consideration, not explicitly
brought out in this book, is that key environmental factors (disease, temperature,
mutation, predators, etc.) affecting survival vary over time. Strong selection must
be present for a huge number of generations if fixation of a (temporarily) favourable
trait throughout a population is to occur. Relaxation for just a few generations
could undo this process, since selection for a different trait would then be at
the expense of the preceding one.
We must recognize clearly this lack of strong correlation between a mutation (whether
having a positive or negative effect) and reproductive success. It is a fact of
nature, yet most people attribute incorrectly near miraculous creative powers to
natural selection.
But then how could natural selection supposedly develop optimized proteins, such
as enzymes, one nucleotide mutation after the other, leading to almost identical
versions throughout nature?6–8 Each improved nucleotide would have to
be selectable in the presence of all the other noise-causing mutations within the
same linkage blocks. This cannot occur by somehow selecting for superior individuals
on average—which inherently involves thousands of different genes and millions
of different nucleotides (p. 117).
We conclude that evolutionary theory has a major problem. If mutation/selection
cannot preserve the information already within the genome, it is even more difficult
to argue that billions of slight improvements were selected gradually over time
(p. 106). The matter is not merely an issue of low probabilities. Theoretically
a huge number of offspring could be generated, each differing by many random mutations.
Might not a lot of luck bordering on the miraculous cherry-pick out the best? Not
really. Sanford explains why there are physical constraints as to what natural selection
could do in the real world.
The cost of selection
The number of offspring which humans can produce is rather small. For a human population
to maintain its size, about three individuals per couple would be needed. This is
because not all who live go on to have children, due to personal choice, accidental
death, etc. Eliminating individuals carrying bad mutations would require that additional
children be born, to be sacrificed to natural selection (p. 57). ‘All selection
has a biological cost—meaning that we must remove (or ‘spend’)
part of the breeding population’ (p. 56). In other words, deleterious mutations
in man must be kept below one mutation for every three children for flawless,
100% effective selection to be able to eliminate all the mutations and still allow
the population to reproduce (p. 32).
There are several kinds of costs, all additive, which must be paid for before ‘real’
selection can be covered (p. 59).9 As mentioned above, fitness has low heritability,
meaning environmental factors are much more important than genetic factors in determining
who survives. This means that a very large number of additional offspring is needed,
which must die due to natural selection independent of genetic causes, simply to
remove non-heritable variations (p. 59). In these circumstances, having to additionally
select the worse culprits which carry 100 or more mutations, every generation, is
not physically possible (p. 62).
Haldane’s Dilemma
A process which steadily degrades a genome cannot produce a better organism.
Having demonstrated conclusively that the degradation of the human genome (in the
presence of such high mutations rates, preponderance of deleterious mutations and
lack of huge expendable proportions of offspring) cannot be avoided, we return to
what evolutionary theory claims happened. Ever more complex and sophisticated genomes
are supposed to have arisen, step by step, over eons.
In the 1950s, one of the most famous population geneticists, John Burdon Sanderson
Haldane, presented an observation known as ‘Haldane’s dilemma’
(p. 128): it would take (on average) 300 generations to select a single new mutation
to fixation. However, his calculations were only for independent, unlinked mutations.
He assumed constant and very strong selection for a single trait, which is not realistic.
The interference by hundreds of random mutations was not taken into account. Even
so, selection for only 1,000 specific and adjacent mutations could not
happen in all putative evolutionary time. There is no way an ape-like creature could
have been transformed into a human (p. 129). Man and chimp differ at roughly 150
million nucleotide positions (p. 130) and humans show remarkably little variation
worldwide.
Think for yourself
Advanced education is dominated by evolutionary theory taught as established fact.
But ‘are you really just a meaningless bag of molecules—the product
of nothing more than random molecular mutations and reproductive filtering?’
(Prologue). This doctrine is presented as unquestioned truth, an axiom accepted
by faith because many scientists present it as obviously true (p. 5). But if you
come to the point where you feel that the Primary Axiom is no longer obviously true
to all reasonable parties, then you must not accept it on blind faith (p.
10). At best the materialist model could be basically right, but it is absurd to
continue believing that it is self-evident. At the very least, critical thought
and fair discussion is required, something scorned and denigrated by the current
high priests of biology.
Historically, the entire field of population genetics was developed by a small,
tightly knit group of people radically committed to the Primary Axiom. They were
free to explore many scenarios and adjust multiple parameters unconstrained by objective
calibrations, and to optimize frameworks to appear internally consistent. Their
mathematical approach was to define the unit of selection as discrete genetic units,
such a gene or nucleotide, instead of whole organisms with all the contradictory
influencing factors (p. 52).
‘For the most part, other biologists do not even understand their work—but
accept their conclusions “by faith”’ (p. 46). The theorists’
models can be shown to never have matched biological reality to the minimal degree
expected of useful models, but these men were undeniably intelligent and had an
incredible aura of intellectual authority (p. 53). In many ways they deserve our
admiration, since transforming any scenario, correct or not, into an appropriate
mathematical formulation requires a great deal of skill. One can also admire honestly
the brilliant lawyer who argues ever so cleverly against the truth in his client’s
interest. How we wish they would contribute their gifts within a correct paradigm!
There is hope
Finally, professor Sanford makes it clear that no amount of human intervention can
salvage the relentless degradation of our genomes. We will experience much and increasing
suffering on the part of our children and grandchildren. But our Creator made the
genome in the first place.
‘ … Jesus is our hope … He gave us life in the first place—so
He can give us new life today. He made heaven and earth in the first place—so
He can make a new heaven and earth in the future’ (p. 155).
Read this book twice. Then read it again with a highlighter. Technical aspects are
easy to follow, and the specialist will benefit very much for the highly relevant
references offered.
Further reading
Related resources
References
- Behe, M., Darwin’s Black Box: The Biochemical Challenge
to Evolution, The Free Press, New York, NY, 1996. Return to
text.
- Drake, J.W., Charlesworth, B., Charlesworth, D. and Crow,
J.F., Rates of spontaneous mutation, Genetics 148:1,667–1,686,
1998. Return to text.
- Dawkins, R., The Blind Watchmaker, Penguin Books,
London, 1986. Return to text.
- Lenski, R.E., Ofria, C., Pennock, R.T. and Adami, C, The evolutionary
origin of complex features, Nature 423(8):139–144,
2003. Return to text.
- Schneider, T.D., Evolution of biological information,
Nucleic Acids Res. 28:2794–2799, 2000.
Return to text.
- Truman, R. and Heisig, M., Protein families: chance
or design? Journal of Creation 15(3):115–127, 2001,
<www.creation.com/protein>. Return to text.
- Truman, R., The ubiquitin protein: chance or design?
Journal of Creation 19(3):116–127, 2005, <www.creation.com/ubiquitin>.
Return to text.
- Truman, R., Searching for needles in a haystack, Journal
of Creation 20(2):90–99, 2006. Return
to text.
- ReMine, W.J, Cost theory and the cost of substitution—a
clarification, Journal of Creation 19(1):113–125,
2005, <www.creation.com/cost>.
Return to text.
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