Hi everyone,
People here have been arguing for years about random gene variation and Natural Selection...while I have been trying to argue for some kind of a direction and progress in evolution.
Here is an article about evolvability or the increasing ability to evolve in a particular way.
http://www.bbc.com/earth/story/20170301-life-may-actually-be-getting-better-at-evolving***************
Creatures do not seem to be merely at the mercy of random changes, or mutations, in their genes over time. Instead, they actually seem to "improve" their ability to adapt. It seemed this ability was not explained solely by the process of natural selection, in which the best traits are passed on by the most successful organisms.
His ideas could help explain why animals are so good at evolving: a trait called their "evolvability".
Many people will be familiar with the idea that genes are passed from parent to offspring, and those genes that help their hosts survive and reproduce have a better chance of getting passed on. This is the essence of evolution and natural selection.
But there is more to it, because genes often work together. They form "gene networks", and those gene networks can also sometimes be passed intact down the generations.
His contribution is largely to do with the way natural selection acts on those networks.
He believes it does not just act like a partial barrier, letting some adaptations through over others. Instead, the impact of this filtering allows gene networks in animals to actually "learn" what works and what does not over time. This way, they can improve their performance – in much the same way that the artificial neural networks used by computer scientists can "learn" to solve problems.
"Gene networks evolve like neural networks learn," he says. "That's the thing that's novel."
Watson's basis for this claim is the idea that the connections between genes can be strengthened or weakened as a species evolves and changes – and it is the strength of those connections in gene networks that allow organisms to adapt.
This process is similar to how human-made artificial neural networks on computers work.
the connections between adjacent neurons that have similar outputs are strengthened over time. In short: "neurons that fire together, wire together". The network "learns" by creating strong links within itself.
If an organism has certain genes firing together in this way, and that organism proves successful enough to reproduce, then its offspring will not simply inherit its beneficial genes, argues Watson. They will also inherit the connectivity between those genes.
To begin with, this process of trial-and-error updating might work reasonably well. But over time, updating the code this way would become ever more cumbersome. The code would begin to look messy, making it difficult to work out what impact a particular addition might have.
If organisms actually evolved this way, says Watson, "their evolvability – their ability to adapt to new stresses or environments – would be rubbish." But in fact, "the ability of natural organisms to evolve to new selective environments or challenges is awesome."
Watson has also suggested that gene networks can contain "memories" of past adaptations, which can be expressed when required by the environment.
Watson's idea means that organisms would be imbued with multiple options for adapting.
It also implies that gene networks have evolved – in all animals – to be adaptable to Earth's natural world. That is why organisms are so good at responding to the environment: the stresses and strains of living in Earth's environments have been imprinted in the regulatory connections between genes, over the course of millions of years.
The gene networks, he argues, have gradually learned to respond in similar ways in similar situations. Those modular features, such as a butterfly's wing pattern, might be more likely solutions for the learning system than others.
In other words, when given a few necessary conditions, evolution will perform the same tricks again and again.
All of this raises some rather philosophical questions. For one thing, is evolution functioning like a big, natural computer? And does "evolvability" suggest that life is in some sense programmed to improve – at the genetic level at least?
Some biologists flinch at the idea, but if the capacity of organisms to adapt is getting better and better over time, if evolution is learning as it goes, then might it just as well be described this way?
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He doesn't seem to talk of epigenetics specifically which is funny. But the idea that organisms are learning to evolve in certain ways to improve their adaptability, seems to indicate a built in 'Intelligence' and ability to evolve in certain ways.
Cheers.
Sriram