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Evidence ID: BIO-EV02
Evidence: Insufficient Generic Propagation Rates
Summary: Research in Population Genetics enables scientists to model genetic propagation in terms of mutation rates, population sizes and reproductive rates. Research in Genetic Engineering enables scientists to explore the viability of different combinations of amino-acid sequences. The outcome of these areas of research suggests that there is not enough time for Darwin's theory of random mutation to produce complex, distinct phyla that originated during the Cambrian Explosion.
Description: In theory, Darwin's process of random mutation and natural selection can produce complex life given enough time. The question is how much time is required to produce complex organisms that are both viable and heritable? Essentially, what is the efficacy of the Darwin's process of random mutations?
Population Genetics is a field of study that is concerned with how genetic mutations propagate for a given species [REF-POP01]. It was pioneered by Sewall Wright, J. B. S. Haldane, and Ronald Fisher in the early 1900s. Their collective work in genetics, animal breeding and statistics formed the basis for early theories and models in Population Genetics.
Population Genetics models the propagation of beneficial genetic mutations over time. These models account for many factors, most notably mutation rates, population sizes and reproductive rates.
Collectively, these factors determine how well a species thrives and survives.
Taken together, the time to propagate a single generic change within a population may be extremely low.
This problem of genetic propagation is further complicated by the potential lack of viability and heritability of a single genetic mutation [REF-SCM01]. In general, a single mutation is not beneficial or viable, and therefore will not propagate successfully regardless of population sizes, reproductive rates, or conditions. Often times, multiple, coordinated genetic mutations are required to ensure viability and heritability of the species. This is certainly the case with the generation of new phyla which are genetically diverse.
The generation of new phyla using Population Genetics models troubled J. B. S. Haldane. With the invention of DNA sequencing in the 1957, Haldane questioned the speed of beneficial evolution necessary to produce new phyla [REF-HAL02] [REF-BAT01]. In his paper, The Cost of Natural Selection [REF-HAL03], Haldane asserted that there is insufficient time to bring about beneficial evolutionary change given the population constraints outlined above.
Haldane refers to this dilemma as the cost of generic substitution. Fundamentally, natural selection requires the substitution of genetic traits into a population. Those traits must increase over time and eventually prevail to ensure successful propagation.
Haldane's dilemma has been widely debated for the past 60 years.
Researchers have been unable to resolve Haldane's dilemma because they cannot agree
on the fundamental issues.
Many biologists such as George Williams assert that Haldane's dilemma will never be solved [REF-WIL01].
Mathematician David Berlinski refers to this problem of genetic mutation
as combinatorial inflation.
Combinatorial refers to the many possible ways nucleotides in a DNA sequence
are combined and arranged to produce
functional DNA, or amino acids in a protein sequence.
While inflation refers to the astronomical inflation in the combinations or arrangements given the
number of nucleotides found in DNA, or amino acids found in an average length protein.
In the 1960s, mathematician Murray Eden of MIT
estimated that the combinations of amino acids in an average length protein consisting
of 250 amino acids is 10325.
But do all 10325 combinations of amino acids produce viable, functional proteins?
According to molecular biologist Robert Sauer of MIT, the number of viable protein sequences is rare [REF-SAU01].
Using techniques to manipulate gene sequences developed in the late 1970s,
Sauer altered DNA sequences to produce proteins with different amino acid sequences.
After much experimentation, he estimated that the ratio of functional to non-functional amino acid sequences is
1 in 1090
for a protein of 100 amino-acids in length [REF-SCM01].
By comparison, there are an estimated 1080 atoms
in the known universe [REF-MAP01], [REF-WHI01].
Therefore, the odds of 1 chance in 1090
is equivalent to randomly
selecting a singly marked atom in the universe the first time.
Did the processes of mutation and selection have enough time to produce functional proteins? No!
When we compare man's "closest living relative" the chimpanzee,
we discover that the genome sequence is only 96% similar,
not 99% similar as previously estimated [REF-DEW01] [REF-DEW02].
According to David DeWitt of Liberty University, there are an estimated
40 million mutation events required to produce 125 million differences in the DNA sequences
that separate humans and chimpanzees.
This estimate accounts for all nucleotide substitutions, deletions, and insertions in the genomes for which the previous studies did not account.
Based on Population Genetics models, the genetic "distance" between the two species would require approximately 300,000 generations to become fixed in the population.
Given the factors that govern genetic propagation, there would not have been
enough time for this scale of evolution to occur (Haldane’s Dilemma).
These analyses illustrate the shortcomings of Darwin's theory of random mutation.
The search spaces are so astronomically large that is virtually
impossible to randomly select a viable protein sequence in
a reasonable amount of time to affect the necessary level of genetic change observed during the
Cambrian Explosion.
Resources: Copyright@2025 Mainstream ApologeticsCombinatorial Inflation
Dissimilarity of Man and Chimpanzee Genomes
Observations