Is There Purpose in Biology?: The Cost of Existence and the God of Love. By Denis Alexander,
Chapter 4: Biology, Randomness, Chance and Purpose (Part 2)
We are reviewing the book: Is There Purpose in Biology? The Cost of Existence and the God of Love. By Denis Alexander. Chapter 4: Biology, Randomness, Chance and Purpose, Part 2 is the continuation from last week. In the first part of Chapter 4, Denis defines the terms “random”, “chance”, and “chaos” as they are used in the scientific community as opposed to the common parlance. Denis begins this part of the chapter by recounting the story of a medical student coming up to him after a lecture on evolution and religion. This student wanted to know, given evolution, how the first anatomically modern human could be born out of an ape. This is a common misconception – evolution means, at some point, an ape couple gives birth to a human baby because of genetic mutations. However, he states the basic idea of evolution can be stated as:
· GENETIC VARIATION HAPPENS
· INDIVIDUALS ARE SELECTED
· POPULATIONS EVOLVE
It’s this third aspect that trips up so many, like Denis’ medical student. Most people do not understand how evolution purports to work. They think it involves substantial changes in multiple organisms in the same generation for a change to pass down over time. Such changes are wildly improbable and so they conclude evolution is wildly improbable. If evolution worked that way, they’d be right. But evolution involves the shifting of average characteristics of populations over long periods of time. Individuals DO NOT evolve, populations do.
The answer to the question, “So how did we go from zero (humans) to thousands” is that we didn’t. There was always a population of thousands. As the average characteristics of the ancestral population to humans and chimpanzees changed, the group of thousands that eventually became human became more human-like generation after generation. The change from one generation to the next would not be immediately recognizable as it would be a subtle shift in the AVERAGE characteristics of the population as a whole. It is a continuum over millions of years, and most people cannot imagine the time frame. There was NO one point where daddy and mommy were apes and the little baby was a human. Dennis Venema, in the book Adam and the Genome, gives a very useful analogy in the evolution of the Anglo-Saxon language to Modern English. You can find a description of that analogy in my review of the book here .
That being said, in the present context, it is the first and second aspects of the process that are the most relevant if we are to address satisfactorily the claim that “evolution is not a theory of chance”. Genetic variation provides the “raw material” of evolution. It generates much of the innovation involved in the process. Most people do not realize how much genetic variation there is in different living organisms, much less within our own human species. Denis notes that we all vary from each other in around 0.5% of our total 3.2 billion genetic letters – that’s around 16 million letters. New mutations come into the human population at every new birth. This has been demonstrated most clearly in large family studies in which whole genomes from individuals within families – father, mother, and child – were sequenced and compared. He cites a Dutch study (Francioli et al., 2015) where 250 families had their DNA sequenced. For each offspring in this study, there was an average of 38 mutations. That’s a lot, even if many of the mutations were neutral – neither deleterious nor beneficial. Denis says it is worth considering how many ways there are for a genome to vary, because only then can we begin to address the question as to whether any given change that occurs is random or happens by chance. He notes:
- Point mutations. Changes in a single nucleotide (SNPs)
- Indels. Insertion or deletion of a short section of DNA.
- Transposons. The so-called “jumping genes”. A transposable element is a DNA sequence that can change its position within a genome, sometimes creating or reversing mutations and altering the cell’s genetic identity and genome size.
- Gene duplication. It can be defined as any duplication of a region of DNA that contains a gene. Gene duplications can arise as products of several types of errors in DNA replication and repair machinery as well as through fortuitous capture by selfish genetic elements.
- Structural mutations. This kind of chromosomal mutation usually occurs during larger errors in cell division than indels.
Gene flow is the second mechanism for introducing genetic variation into an interbreeding population. This refers to the flow of new genetic variants that comes into a population when exposed to another population of the same species from which they have been separated for some time by barriers such as mountains or rivers. Lateral or horizontal gene transfer is the movement of genetic material between unicellular and/or multicellular organisms other than by the (“vertical”) transmission of DNA from parent to offspring.
Retroviral insertion: a retrovirus is a type of RNA virus that inserts a copy of its genome into the DNA of a host cell that it invades, thus changing the genome of that cell. Once inside the host cell’s cytoplasm, the virus uses its own reverse transcriptase enzyme to produce DNA from its RNA genome, the reverse of the usual pattern, thus retro (backwards). Viruses are everywhere – 6,000 feet below the surface of the earth, in the sands of the Sahara desert, and in icy lakes. An estimated 1031 viral particles live on the planet (there are roughly 1022 stars estimated in the universe). A kilogram of marine muck was found to contain up to a million genetically variant viruses. Our own guts may contain as many as 1,200 different viruses.
Import of organelles (the term organelle is derived from the word ‘organ’ and refers to compartments within the cell that perform a specific function) containing their own DNA represents a fifth and indeed rather dramatic way in which genetic variation has come into the genome at various critical moments in evolutionary history. This occurred when bacteria that had probably started living symbiotically inside cells then became permanent residents and developed into the mitochondria and chloroplasts that we see in cells today.
Denis says that given this extensive and rather bewildering array of different mechanism for generating variant genomes, it might seem surprising that genetic variation between individual of the same species is no more different than it is. However, with background information in place, we are now in a better position to ask whether the generation of genetic variation is truly random or not.
It will be remembered that there are two distinct meanings of the word “random” in the context of biology. The most commonly used meaning simply refers to the fact that genetic variation comes into the genome without the good or ill the organism in view. This is a banal and obvious definition, how could it be otherwise? It is trivially true.
The second and more interesting meaning involves the mathematical question as to whether each nucleotide in the genome, or each section of the genome, is equally likely to be mutated. This is what would need to be the case if mutations were truly random in the second sense. Denis says the short answer to this question is: NO. He then proceeds to give the long answer – and cites numerous studies that show mutation clustering occurs and that there are sequences of DNA, “mutational hot spots” is how he puts it, that are more likely than others to be the site of changes. It is a complex and detailed discussion beyond the scope of this post and likely for most of you to be eyes-glazing-over in detail. I will spare you the detail, as well as spare myself the task of recounting it, which would involve pretty much typing it out word for word.
With all that as background, Denis can now assess the processes involved in generating genetic variation according to the 3 understandings of “chance” outlined in the previous post. To recap:
1. The first is sometimes called epistemological chance because it refers to all those events that are perfectly lawlike in how they happen, but about which we have insufficient knowledge of their antecedents to make predictions.
2. The second main type of chance we can call ontological chance, because there are no antecedents that could possibly be known that could enable a prediction, even in principle.
3. The third type of chance we might call metaphysical chance. This is the idea that chance somehow rules over everything, almost as if it were an agency or metaphysical principle.
Clearly there is plenty of epistemological chance going on here. The systems are too complex to make any specific predictions as individual mutations are concerned. However, once we start averaging large numbers, well-justified generalization can be made about such items such as mutation rates, where mutations are more likely to occur, and which chromosomes are more likely to undergo structural changes.
What about ontological chance? The emission of radioactive particles, as previously noted, displays quantum uncertainty and is not predictable even in principle. But ionizing radiation causes mutations in DNA and, by the law of averaging large numbers, their average outputs and consequent average effects on DNA can likewise be predicted. But it is impossible, even in principle, to predict the timing of individual mutation events. Could this then contribute to the idea that evolution is a theory of chance? Denis says not really, because natural selection acts as the stringent sieve that selects which mutations will be maintained in a population and which will be discarded.
What about Jacques Monod and the “Lady Luck” personification of metaphysical chance? We now know that many types of mutation are not really random in the mathematical sense in terms of their clustered distribution through the genome. The lack of randomness in the origins of genetic variation highlights the risk of hitching one’s philosophy to scientific theories or understandings. Science moves on very fast and so the philosophy in question can be quickly widowed.
Which brings us to the second main phase of the evolutionary process – natural selection. Natural selection is the process by which heritable traits increase an organism’s chances of survival and reproduction. These traits are favored than less beneficial traits. Originally proposed by Charles Darwin, natural selection is the process that results in the evolution of organism. When genetic variation does make a difference for good in the organism, the organism will, over many generations, have greater numbers of offspring – reproductive success, which is what “survival of the fittest” actually is. The key point about natural selection is the successful reproduction which ensures that an individual’s genes are passed on to the next generation.
Natural selection is a rigorous filter that reduces the amount of genetic variation in a population. It is a very conservative mechanism. The reason for this is that the great majority of genetic changes, if not neutral, are likely to be deleterious and will be removed from the populations after some generations. The few beneficial changes will readily pass through the filters of natural selection and quickly spread throughout an interbreeding population as they bestow reproductive benefits on their recipients.
An example of this conservative nature is cytochrome c. Cytochrome c is a highly conserved protein across the spectrum of species, found in plants, animals, and many unicellular organisms. Humans share 97% sequence identity of cytochrome c with rhesus monkeys, 87% with the dog, 82% with the bat, 67% with the fruit fly, 64% with the moth, 44% with yeast, with which we last shared a common ancestor about a billion years ago. 44%!!! Natural selection is a really conservative process. Denis says:
“The conservative nature of natural selection may also be seen in the types of convergent evolution that were surveyed in the previous two chapters. The same or similar adaptations keep popping up in evolutionary history in independent lineages for the simple reason that these happen to be the best that you can get under a given set of circumstances. When similar ecological niches occur again with similar environmental properties, natural selection ensures that similar adaptive solutions will found to life’s challenges.
“It should by now be clear why it doesn’t really matter whether variation comes into the genome via the pathway of epistemological chance (most of it) or ontological chance (as in radiation effects), as in both cases the winnowing effects of natural selection are what have the upper hand in bringing about certain constrained outcomes.”
It is a common assumption that a chance process cannot at the same time be one with a purpose. This chapter highlights the implausibility of that suggestion. Two out of the three kinds of chance discussed above have clearly been critical in the evolutionary process. Yet individual animals and plants exist for the purpose of being alive, of feeding, of procreation. Their existence is teleological albeit purpose with a small “p”. The giraffe has a long neck for the purpose of reaching food on high branches; the whale rises to the surface for the purpose of breathing; the polar bear has white fur for the purpose of camouflage; and so on. You cannot avoid telos in biology.
Still, Purpose with a big “P” is not something that can be derived from biology. We’ve critiqued Monod for his attempt to imbue lack-of-purpose by metaphysical extrapolation. By the same token, we cannot infer Purpose simply from the fact that the evolutionary process is highly organized, constrained and, to a limited extend, predictable. Biology is simply not up to the task of providing some overall Purpose and meaning in life that everybody can agree on. It is above evolution’s pay-grade to play that kind of role.
On the other hand, Denis says the evolutionary process is perfectly compatible with having some overall Purpose (which he considers in the next chapter) despite having chance mechanisms involved. Consider, for example, the lottery. All those little balls with numbers bouncing around in the machine are fulfilling their Purpose. The Purpose, designed by the government, to take money from poor people, make a few people rich, and generate a healthy tax for said government. A chance process is used to generate outcomes that are absolutely certain. If someone doesn’t win this week, then they’ll win the next, or whenever, someone will win. Chance processes are by no means incompatible with determined outcomes. Denis says:
“What should be equally clear from this and the previous two chapters is that the claim that evolution is necessarily Purposeless is now looking simply irrational.”