Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution

Abstract

Significance 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.

Symmetry and asymmetry in biological structures

“…Therefore, we argue that the view presented in the very interesting paper by Johnston et al. ( 1 ) is too one-sided. To fully understand how symmetry develops in biological systems, the trade-off between the spontaneous emergence of symmetry and evolutionary pressures toward asymmetry needs to be integrated in a balanced way.…”

“…The argument brought forward by the authors ( 1 ) is very compelling but omits a critical point. While symmetry may arise more commonly in biological structures with low complexity, there is evolutionary pressure to develop asymmetry in many biological structures with high complexity.…”

Reply to Ocklenburg and Mundorf: The interplay of developmental bias and natural selection

“…In our paper ( 1 ), we argue for strong bias in the arrival of variation toward phenotypes with simple descriptions. Evaluating evidence for such hypotheses about developmental bias is hard because one needs to answer counterfactual questions ( 2 , 3 ).…”

Perturbations of a causal synaptic molecular network in autism and schizophrenia revealed with multiplexed imaging

“…A similar constraint induced dimensionality reduction is considered to stabilize symmetric phenotypes in genotype-phenotype maps 88 . In the context of ASD- and schizophrenia-associated genotypes mapping to a synaptic phenotype space with reduced dimensionality caused by interaction-based constraints, this means that a multitude of seemingly unrelated disease-associated mutations, can drive similar perturbations to the lower-dimensional stable/allowed-state landscape, as measured in synaptic protein networks.…”