The Digital Revolution of Matter: Emergence of Genetic Coding from Catalytic Imperatives in Autopoietic Systems
Abstract
Previous papers in this series have established a stepwise framework for the origin of living systems: (1) thermodynamic selection generates replicators, (2) kinetic selection optimizes them, and (3) autopoiesis (compartmentalization) resolves cooperation conflicts, instituting multilevel selection and protocellular individuality. This fourth paper addresses the final and most revolutionary transition: the origin of encoded genetic information. We argue that, within an autopoietic protocell, increasing metabolic complexity generates a phenotypic bottleneck: the exploration of new catalytic functions is limited by the requirement that each functional molecule must also be a competent replicator. We demonstrate that the separation between genotype (replicable information-bearing molecule) and phenotype (catalytic function-executing molecule) emerges as the evolutionary solution to this bottleneck. This separation begins with ribozyme systems that weakly mediate peptide formation and is subjected to intense selection for its capacity to increase the robustness and adaptive flexibility of the host system. We propose that the genetic code itself—the arbitrary yet systematic assignment of codons to amino acids—consolidates as a frozen accident (Crick, 1968) of the most successful physico-chemical associations in primordial protocellular ecosystems, its subsequent universalization driven by horizontal transfer and error catastrophe (Koonin & Novozhilov, 2017). Thus, life based on DNA→RNA→protein is not the starting point, but the end state of a cascade of staggered evolutionary transitions, where encoded information emerges as the supreme invention for the efficient exploration of functional space under multilevel selective pressure.
Fields of Study & Subjects
Origins and Evolution of Life
Evolution and Genetic Dynamics
Earth Systems and Cosmic Evolution
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 January 2026
- Language
- EN
- Document type
- Preprint