It's all about energy ...

A rendering of a light-harvesting complex from a bacterium.Credit...Iain Johnston

Life's economical. It takes the easy way out in stealing energy from the environment in order to survive. A smart way to do it lies with symmetry as repeats and system modularity saves energy by doing repeats and not build anew in order to stay alive.

Symmetry runs rampant in nature. It’s present wherever mirror images are repeated, like in the right and left halves of elephants or butterflies, or in the repeating patterns of flower petals and starfish arms around a central point. It’s even hiding in the structures of tiny things like proteins and RNA. While asymmetry certainly exists in nature (like how your heart is off to one side in your chest, or how male fiddler crabs have one enlarged claw), symmetrical forms crop up too often in living things to just be random.

Recursion and feedback loops rule.

In a paper published this month in Proceedings of the National Academy of Sciences, researchers analyzed thousands of protein complexes and RNA structures as well as a model network of molecules that control how genes switch on and off. They found that evolution tends toward symmetry because the instructions to produce symmetry are easier to embed in genetic code and follow. Symmetry is maybe the most fundamental application of the adage “work smarter, not harder.”

“People often are quite amazed that evolution can make these incredible structures, and what we’re showing is that it’s actually easier than you might think,” said Ard Louis, a physicist at the University of Oxford and an author of the study.

As proof ...

Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution

Why does evolution favor symmetric structures when they only represent a minute subset of all possible forms? Just as monkeys randomly typing into a computer language will preferentially produce outputs that can be generated by shorter algorithms, so the coding theorem from algorithmic information theory predicts that random mutations, when decoded by the process of development, preferentially produce phenotypes with shorter algorithmic descriptions. Since symmetric structures need less information to encode, they are much more likely to appear as potential variation. Combined with an arrival-of-the-frequent mechanism, this algorithmic bias predicts a much higher prevalence of low-complexity (high-symmetry) phenotypes than follows from natural selection alone and also explains patterns observed in protein complexes, RNA secondary structures, and a gene regulatory network.

As often stated, for life, it's all about harvesting and using energy in the most efficient way possible. :)

Conway's game of life applies, does it not? :)

Red glider on the square lattice with periodic boundary conditions