So the hype now pouring out of the mass media is popularizing what has been lurking in the science all along: a gene-god as an entity with almost supernatural powers. But at the same time, a counter-narrative is building, not from the media but from inside science itself. T he long-suppressed logic of Johansenn that has stalked the gene-god for decades has come home to roost. Scientists now understand that the information in the DNA code can only serve as a template for a protein.
It cannot possibly serve as instructions for the more complex task of putting the proteins together into a fully functioning being, no more than the characters on a typewriter can produce a story. This can seem confusing to those of us indoctrinated in the idea that there must be a set of genetic instructions prior to development: If not in the DNA code, then where?
By the s, research findings started to turn that notion on its head.
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They self-organized, synthesized polymers like RNA and DNA , adapted, and reproduced through interactions among hundreds of components. In this perspective, the genes evolved later, as products of prior systems, not as the original designers and controllers of them.
Then it was slowly appreciated that we inherit just such dynamical systems from our parents, not only our genes. Molecular biologists have been describing how those factors form networks of complex interactions. Together, they self-organize according to changing conditions around them. Being sensitive to statistical patterns in the changes, they anticipate future states, often creating novel, emergent properties to meet them.
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Accordingly, even single cells change their metabolic pathways, and the way they use their genes to suit those patterns. Genes are used as templates for making vital resources, of course. But directions and outcomes of the system are not controlled by genes. Like colonies of ants or bees, there are deeper dynamical laws at work in the development of forms and variations.
Some have likened the process to an orchestra without a conductor. Physiologist Denis Noble has described it as Dancing to the Tune of Life the title of his recent book. It is most stunningly displayed in early development. Within hours, the fertilized egg becomes a ball of identical cells—all with the same genome, of course. But the cells are already talking to each other with storms of chemical signals.
Siddhartha Mukherjee | THE GENE: An Intimate History
Through the statistical patterns within the storms, instructions are, again, created de novo. The cells, all with the same genes, multiply into hundreds of starkly different types, moving in a glorious ballet to find just the right places at the right times. That could not have been specified in the fixed linear strings of DNA. So it has been dawning on us is that there is no prior plan or blueprint for development: Instructions are created on the hoof, far more intelligently than is possible from dumb DNA.
Another wrench in the works has been the discovery that a gene product typically undergoes rearrangements before being put to use. It is such discoveries that are turning our ideas of genetic causation inside out. We have traditionally thought of cell contents as servants to the DNA instructions. I think it is better described as a passive data base which is used by the organism to enable it to make the proteins that it requires. Known for decades, these surely reflect inherited codes pre-determining development and individual differences? It is not dependent on a single gene, however. The statistical relation obscures several streams of chemical synthesis of the dye anthocyanin , controlled and regulated by the cell as a whole, including the products of many genes.
In its absence the flower is white. But more evolved functions—and associated diseases—depend upon the vast regulatory networks mentioned above, and thousands of genes. This explains why humans seem to have only a few more genes than flies or mice around 20, , while a carrot has 45,! But there is a correlation with the evolving complexity of regulatory networks. Counting genes to understand the whole is like judging a body of literature by counting letters. A ll of this provides a fraught background for modern gene association studies.
First, the methods for computing polygenic scores, in which millions of variables are analyzed by statistical manipulation, provides huge opportunities for false positives. Very large databases—even randomly generated ones—can contain large numbers of meaningless correlations; and statistical significance values can be hugely inflated by invalid assumptions. In polygenic score estimations, for example, it is assumed that SNP associations can be simply added together, as if beans in a bag, with no effects on each other, or from the environment.
Then, as the National Institute of Health website reminds us, the majority of SNPs are functionally irrelevant anyway. More importantly, all modern societies have resulted from waves of migration by people whose genetic backgrounds are different in ways that are functionally irrelevant. Different waves have tended to enter the class structure at randomly different levels, creating what is called genetic population stratification.
But different social classes also experience differences in learning opportunities, and much about the design of IQ tests, education, and so on, reflects those differences, irrespective of differences in learning ability as such.
So some spurious correlations are, again, inevitable. As Jeremy J.
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It means that different proteins, with potentially widely different functions, can be produced from the same gene: not one for one, as the central dogma has told us. Again, the instructions for such rearrangements are not in the genes themselves. More startling has been the realization that less than 5 percent of the genome is used to make proteins at all.
Most produce a vast range of different factors RNAs regulating, through the network, how the other genes are used. Increasingly, we are finding that, in complex evolved traits—like human minds—there is little prediction from DNA variation through development to individual differences. The genes are crucial, of course, but nearly all genetic variations are dealt with in the way you can vary your journey from A to B: by constructing alternative routes. Conversely, it is now well known that a group of genetically identical individuals, reared in identical environments—as in pure-bred laboratory animals—do not become identical adults.
Rather, they develop to exhibit the full range of bodily and functional variations found in normal, genetically-variable, groups.
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She argues that we need a new vocabulary that includes concepts such as robustness, fidelity, and evolvability. But more than a new vocabulary, a new awareness is absolutely crucial: that understanding the components of a system be they individual genes, proteins, or even molecules may tell us little about the interactions among these components.
With the Human Genome Project nearing its first and most publicized goal, biologists are coming to realize that they have reached not the end of biology but the beginning of a new era. Indeed, Keller predicts that in the new century we will witness another Cambrian era, this time in new forms of biological thought rather than in new forms of biological life. Proust Questionnaire for Translators. September 30 is the feast day of Saint Jerome, the patron saint of translators.
It is also International Translation Day.
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