2007/08/11 by Tsvi Tlusty · 5 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · #Bacterial Genetics and Biotechnology #DNA and Biological Computing #RNA and protein synthesis mechanisms #cond-mat.stat-mech #cs.IT #math.IT #physics.bio-ph #q-bio.QM
paper · pdf · doi:10.1016/j.jtbi.2007.07.029
published as Journal of Theoretical Biology Volume 249, Issue 2, 21 November 2007, Pages 331-342 · Keywords: genetic code, rate-distortion theory, biological information channels
openalex publication_date 2007/08/11 · arxiv created 2010/07/23 · arxiv updated 2010/07/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The genetic code maps the sixty-four nucleotide triplets (codons) to twenty amino-acids. Some argue that the specific form of the code with its twenty amino-acids might be a 'frozen accident' because of the overwhelming effects of any further change. Others see it as a consequence of primordial biochemical pathways and their evolution. Here we examine a scenario in which evolution drives the emergence of a genetic code by selecting for an amino-acid map that minimizes the impact of errors. We treat the stochastic mapping of codons to amino-acids as a noisy information channel with a natural fitness measure. Organisms compete by the fitness of their codes and, as a result, a genetic code emerges at a supercritical transition in the noisy channel, when the mapping of codons to amino-acids becomes nonrandom. At the phase transition, a small expansion is valid and the emergent code is governed by smooth modes of the Laplacian of errors. These modes are in turn governed by the topology of the error-graph, in which codons are connected if they are likely to be confused. This topology sets an upper bound - which is related to the classical map-coloring problem - on the number of possible amino-acids. The suggested scenario is generic and may describe a mechanism for the formation of other error-prone biological codes, such as the recognition of DNA sites by proteins in the transcription regulatory network.