Protein Synthesis Analogy (see below) ..
In the assembly of the brain, as in the assembly of other organs, one of the most important ideas is that of a cascade, one gene influencing another, which influences another, which influences another, and so on. Rather than acting in absolute isolation, most genes act as parts of elaborate networks in which the expression of one gene is a precondition for the expression of the next. The THEN of one gene can satisfy the IF of another and thus induce it to turn on. Regulatory proteins are proteins (themselves the product of genes) that control the expression of other genes and thus tie the whole genetic system together. A single regulatory gene at the top of a complex network can indirectly launch a cascade of hundreds or thousands of other genes leading to, for example, the development of an eye or a limb.
In the words of Swiss biologist Walter Gehring, such genes can serve as "master control genes" and exert enormous power on a growing system. PAX6, for example, is a regulatory protein that plays a role in eye development, and Gehring has shown that artificially activating it in the right spot on a fruit fly's antenna can lead to an extra eye, right there on the antenna-thus, a simple regulatory gene leads directly and indirectly to the expression of approximately 2,500 other genes. What is true for the fly's eye is also true for its brain-and also for the human brain: by compounding and coordinating their effects, genes can exert enormous influence on biological structure.
Reflection 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). If a whole series of pixels are of exactly the same color, the software that creates GIF files will assign a code that represents the color of those pixels, followed by a number to indicate how many pixels in a row are of the same color. Instead of having to list every blue pixel individually, the GIF format saves space by storing only two numbers: the code for blue and the number of repeated blue pixels. When you "open" a GIF file, the computer converts those codes back into the appropriate strings of identical bits; in the meantime, the computer has saved a considerable amount of memory. 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.
From: Making the Mind, , December 2003/January 2004. Also see Marcus' new book: The Birth of the Mind: How a Tiny Number of Genes Creates the Complexity of Human Thought. Basic Books 2004.