Thinking to Believe

In a previous post I addressed the “lottery” objection to the probabilistic argument against a naturalistic origin of life: “Just as the odds of winning the lottery are low, and yet people win the lottery all the time, so too the odds of forming life by chance may be low, but that doesn’t mean it is impossible.”  I argued that unlike a lottery, the probabilistic resources available to form life are so unfathomably low that there is no reason to expect a winner in chance’s game of life.  To prove my point, I compared the number of possible events in the whole history of the universe (10¹³⁹)—the probabilistic resources—to the probability of a 250 gene organism forming by chance (1:10^41,000).  The odds of life forming by chance came up trillions upon trillions upon trillions of times short, and thus there is no rational basis on which to affirm that life originated by chance.  What I didn’t realize then was that I had severely over-estimated the odds.

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In a previous post I argued that chance cannot account for the origin of the first living cell because the odds are too low to have any reasonable chance of being met.  The odds of a single, functional protein forming by chance is 1 in 10¹⁶⁴.  That’s 1 chance in 100 trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion trillion.  But the simplest life form would need at least 250 different proteins, lowering the odds to 1 in 10^41,000!

While the numbers appear staggering, many people will immediately raise the “lottery objection”: Just as the odds of winning the lottery are low, and yet people win the lottery all the time, so too the odds of forming life by chance may be low, but that doesn’t mean it is impossible.  While I understand the analogy, are the lottery and the OOL truly analogous?  No, not by a long shot.

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(Note: Read Part 3a of the series before reading this post)

Viruses

The HIV virus mutates at the evolutionary speed limit: 10,000 times faster than most cells such as malaria.[1] And its genome is rather small (nine genes versus thousands in malaria).[2] Its small size combined with a short generation time (1-2 days) and super-rapid mutation rate means every single nucleotide in the HIV genome will mutate 10,000 to 100,000 times in every infected person every day, and thus double point mutations like the one that made malaria immune to Chloroquine occur in every person every day.  In fact, over the past several decades every possible combination of up to six point mutations has occurred in HIV somewhere in the world.  If RM drives macroevolutionary changes in organisms, then we should observe macroevolution in the HIV virus since it experiences more mutations than any other organism.  But we don’t.  HIV has run the gamut of all possible mutations to its genome, and yet with all of these mutations in a population of 100 billion billion viruses, no new cellular machinery has been created, and no new organism has developed! HIV is still HIV.  It still contains the same number of proteins, still performs the same function, and still binds to its host the same way it always has.  There have been no significant biochemical changes.  Even gene duplication has failed to produce any new biological information.

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(Read parts 1 and 2 in the series)

The heart of the neo-Darwinian synthesis is that evolution advances via the process of natural selection working on random mutations (RM+NS).  Natural selection itself lacks any creative power – it only eliminates what doesn’t work.  Eliminating the unfit, however, does nothing to “explain the origin of the fit”![1]  The burden falls entirely on RM to create the biological novelties required by Darwinism to drive evolution forward.  It must be asked, then, whether RM has the creative power required by Darwin’s theory.  Can RM produce the new biological information necessary to drive evolution forward and explain the diversification of all life?  What exactly can RM do? 

When the neo-Darwinian synthesis was set forth some 70 years ago, answers to these questions could not be ascertained.  While the theory was plausible on a conceptual level, there was no real way of testing its biological plausibility.  Over the last 30 years, however, we have been able to observe both the power and limits of RM+NS at the biological level.  What have we discovered?  We discovered that while RM can produce variability within an organism, it is not capable of producing the kind of changes required by Darwin’s theory.  RM is severely limited in what it can accomplish. 

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(For part 1 in the series, click here)

If macroevolution occurs, it must do so at the biochemical level.  Additional genetic information is needed to build the new proteins and biological systems required for large-scale changes.  Where does the new biological information come from?  Mutations?  No.  Point mutations such as inserting, inverting, or substituting nucleotides in existing genes cannot increase the information content of DNA even if they occur in protein-coding regions, and even if the mutations are beneficial to the organism.  At best they can only replace existing information/function with different information/function, so that the overall information content is merely preserved.[1]  For macroevolution to occur a net increase of information is required, not just a change in existing information.

The origination of new genetic information requires new proteins, which requires hundreds of additional nucleotides arranged in a highly specified order.  How likely is it that chance processes can get the job done?  Next to none.  The chances of producing a functional amino acid sequence of a mere 150 nucleotide bases (which would sequence one of the smallest proteins) is 1:10¹⁶⁷.[2]  To put this number in perspective, consider that there have only been 10¹³⁹ events in the entire universe since the Big Bang.[3]  So even if every event in the history of the universe was devoted to building a single functional protein, the number of sequences produced thus far would be less than 1 out of a trillion trillion of the total number of events needed to give it even a 50% chance of success!  Any reasonable person must conclude, then, that it is beyond the reach of chance to create even the smallest amount of new biological information in an organism.  Add to this the fact that many new proteins are needed to produce new biological systems, and the scenario becomes all the more fantastical.  If chance alone cannot produce the gene for even one protein—yet alone many—macroevolution becomes impossible.

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Several months ago I blogged my way through Stephen Meyer’s Signature in the Cell, summarizing his devastating critique of naturalistic origin-of-life theories and powerful argument for the intelligent design of the first life (parts 1, 2, 3, 4, 5, 6, 7a, 7b).  But what about the proliferation of life?  Can a fully naturalistic theory like neo-Darwinian evolution account for the proliferation and variety of life once it began?  To answer this question I am going to summarize Michael Behe’s key argument against a Darwinian account of evolution in The Edge of Evolution (paperback only $6 through Amazon right now, regular $15). 

What Needs to be Explained

To properly evaluate Darwin’s theory of the evolution of life, we must clarify what is meant by “evolution.”  Evolution can refer merely to small biological changes within a species over time.  Called “microevolution,” or the special theory of evolution, this definition of evolution is relatively uncontroversial and has been confirmed empirically (e.g. drug resistance in bacteria, changes in the size of finch beaks, etc.).  Evolution can also refer to large-scale biological changes[1] that, over time, transform one species into another into another ad infinitum.  This kind of evolution is called macroevolution, or the general theory of evolution.  Darwin’s theory entails this latter definition, and thus proof for his theory requires evidence that there are no natural limits to the amount of variation an organism can experience.

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In the human genome, only 1.5% of our 3.2 billion base pairs of DNA codes for proteins.  For a long time evolutionists though the other 98.5% was “junk” DNA: DNA that was preserved in the genome, but had no function; the byproduct of billions of years of aimless mutations.  Over the past seven years, however, scientists keep discovering more and more function for this “junk.”  For example, it has been discovered that ~90% of our genome codes for RNA products.  Junk DNA also:

1. Regulates DNA replication
2. Regulates transcription
3. Marks sites for programmed rearrangement of genetic material
4. Influences the proper folding and maintenance of chromosomes
5. Controls the interactions of chromosomes with the nuclear membrane
6. Controls RNA processing, editing, and splicing
7. Modulates translation
8. Regulates embryological development
9. Repairs DNA
10. Aids in fighting disease^[1]

And now, biologist Richard Sternberg has brought my attention to a very interesting find related to a specific kind of “junk” DNA called Short Interspersed Nuclear Elements (SINEs).  SINEs are mobile DNA that can insert themselves in various locations within the genome, and are thought to be functionless according to evolutionary biologists.

The rat and mouse are said to have diverged from one another 22 million years ago.  Since that time, each is thought to have experienced hundreds of thousands—if not millions—of SINE insertion events.  Given so many insertion events, we would expect for the location of SINEs to be very different in the mouse genome than in the rate genome (in the same way we would expect a moon that split in two 22 million years ago to evidence a very different asteroid bombardment pattern on its surface).  And yet, when we compare the location of SINEs in the mouse and rate genomes this is what we find:

They are virtually identical!  This is not what we would expect from a degenerative process like mutations and random insertions over millions of years.  We would expect radical divergence, not a nearly-identical pattern.  While the SINE sequences are not the same in the rat and mouse genomes, the placement of the SINEs is nearly identical (and they are concentrated in gene-coding regions of the genome).

How do we account for this pattern?  Can it be the result of a degenerative process?  Surely not.  Patterns are indicative of design, and hence purpose.  Contrary to the expectations of evolutionary biologists, SINEs do have purpose and function, even if we are only beginning to understand them.