SubscribeReflection on the relation between brain and body immediately vitiates the gene shortage argument: if 30,000 genes weren’t enough to have significant influence on the 20 billion cells in the brain, they surely wouldn’t have much impact on the trillions that are found in the body as a whole. The confusion, once again, can be traced to the mistaken idea of genome as blueprint, to the misguided expectation of a one-to-one mapping from individual genes to individual neurons; in reality, genomes describe processes for building things rather than pictures of finished products: better to think of the genome as a compression scheme than a blueprint.
Computer scientists use compression schemes when they want to store and transmit information efficiently. All compression schemes rely in one way or another on ferreting out redundancy. For instance, programs that use the GIF format look for patterns of repeated pixels (the colored dots of which digital images are made)...Computer scientists have devised dozens of different compression schemes, from JPEGs for photographs to MP3s for music, each designed to exploit a different kind of redundancy. The general procedure is always the same: some end product is converted into a compact description of how to reconstruct that end product; a “decompressor” reconstructs the desired end product from that compact description.
Biology doesn’t know in advance what the end product will be; there’s no StuffIt Compressor to convert a human being into a genome. But the genome is very much akin to a compression scheme, a terrifically efficient description of how to build something of great complexity—perhaps more efficient than anything yet developed in the labs of computer scientists (never mind the complexities of the brain—there are trillions of cells in the rest of the body, and they are all supervised by the same 30,000-gene genome). And although nature has no counterpart to a program that stuffs a picture into a compressed encoding, it does offer a counterpart to the program that performs decompression: the cell. Genome in, organism out. Through the logic of gene expression, cells are self-regulating factories that translate genomes into biological structure.
Cascades are at the heart of this process of decompression, because the regulatory proteins that are at the top of genetic cascades serve as shorthand that can be used over and over again, like the subroutine of a software engineer. For example, the genome of a centipede probably doesn’t specify separate sets of hundreds or thousands of genes for each of the centipede’s legs; instead, it appears that the leg-building “subroutine”—a cascade of perhaps hundreds or thousands of genes—gets invoked many times, once for each new pair of legs. Something similar lies behind the construction of a vertebrate’s ribs. And within the last few years it has become clear that the embryonic brain relies on the same sort of genetic recycling, using the same repeated motifs—such as sets of parallel connections known as topographic maps—over and over again, to supervise the development of thousands or even millions of neurons with each use of a given genetic subroutine. There’s no gene shortage, because every cascade represents the shorthand for a different reuseable subroutine, a different way of creating more from less.
"The proper role of adaptationist thinking here is a heuristic one, which guides empirical work but does not substitute for it. While there are many possible hypotheses about adaptive solutions to environmental hazards, not all hypotheses are equally plausible, and evidence ultimately adjudicates between them."A quick example from a Guardian profile on Robert Trivers:
From abstract notions about the flow of genes he had come up with concrete and testable ideas about the ways our minds work; and it turned out to be demonstrably true that we find it much easier to solve logical puzzles if they are framed as if they are about cheating rather than an emotionally neutral subject, even though the two ways of putting the problem are logically equivalent.This was a hypothesis that came from e.p. as a generative theoretical framework that was then tested and shown to be a real phenomenon.
...racism is actually an unfortunate by-product of another phenomenon—a tendency to assign people to “coalition groups”, and to use whatever cues are available, be they clothing, accent or skin colour, to slot individuals into such groups (or “stereotype” them, as modern usage might term it). The good news is that experiments done by the researchers suggest that such stereotypes are easily dissolved and replaced with others. Racism, in other words, can be eliminated.The linked article has details about the experiments and their result which are quite compelling.
Every decent evolutionary explanation has testable predictions about the design of the trait. For example, the hypothesis that pregnancy sickness is a byproduct of prenatal hormones predicts different patterns of food aversions than the hypothesis that it is an adaptation that evolved to protect the fetus from pathogens and plant toxins in food at the point in embryogenesis when the fetus is most vulnerable – during the first trimester. Evolutionary hypotheses – whether generated to discover a new trait or to explain one that is already known – carry predictions about the design of that trait. The alternative – having no hypothesis about adaptive function – carries no predictions whatsoever. So which is the more constrained and sober scientific approach?(from this interview)
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If fine-grained responses are not heritable then nearly every EP argument goes out the window, because education patterns can change rapidly and therefore aren't influenced much at all by ancient needs. Evolution must not only satisfy needs, it must work within the framework of genetic possibility, which is why birds have not evolved helicopter rotors.
posted by localroger at 3:30 PM on February 4 [2 favorites]