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Evolutionary tradeoffs and the geometry of gene expression space
Published on November 4, 2014 36 min
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Hi. My name is Uri Alon from the Weizmann Institute in Israel. Today I'm going to talk with you about evolutionary trade-offs and the geometry of gene expression space.
The basic idea is that when you have trade-offs between tasks, they lead to simplicity, a simple geometry of the phenotypes in trait space.
Now, when we think about evolution and evolutionary theory, we usually think about a simple picture where the DNA, the genotype, through developmental processes gives rise to the organism's shape, the phenotype. And the phenotype does something to give you fitness. For example, the bird's beak eats the seeds. The better it eats the seeds, the more fit the organism, the more viable babies that it makes.
And conceptually, we can describe this in terms of a fitness landscape. So we think about things we can measure about the beak. We take a ruler, and we measure its height and its width and its lengths. And each trait like that is an axis, and so we have the trait space describes all possible beak shapes. And for each point in that space, we can imagine the fitness of a bird with that beak. And if we can imagine a fitness landscape, it might have a peak or several peaks. And natural selection tends to maximize fitness and bring you to the maximum of the fitness landscape.
But in this talk we'll talk about a different situation. What happens if the same beak needs to do more than one task? For example, if you need to eat both the seeds and you need to pick insects or pollen from inside flowers. Now, the problem is that a single phenotype can't be optimal at two tasks at once. Maybe to eat the seeds you need something like a heavy plier. And to pick out the pollen you need something like a pincers or a nose plier. And a single phenotype can't be two different shapes at once. That leads to a fundamental trade-off.