Accurate phenotypic self-replication as a necessary cause for biological evolution.

Allele fixation Average relative fitness Evolutionary theory Mathematical analysis Selection coefficient Self-replication

Journal

Bio Systems
ISSN: 1872-8324
Titre abrégé: Biosystems
Pays: Ireland
ID NLM: 0430773

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 27 10 2023
revised: 29 01 2024
accepted: 09 02 2024
medline: 18 3 2024
pubmed: 13 2 2024
entrez: 12 2 2024
Statut: ppublish

Résumé

Since the Origin of Species, it has been known that evolution depends on what Darwin called the "strong principle of inheritance." Highly accurate replication of cellular phenotype is a universal phenomenon in all of life since LUCA and is often taken for granted as a constant in evolutionary theory. It is not known how self-replication arose during the origin of life. In this report I use the simple mathematics of evolutionary theory to investigate the dynamics of self-replication accuracy and allelic selection. Results indicate that the degree of self-replication accuracy must be greater than a threshold related to the selection coefficients of the alleles in a population in order for evolution to occur. Accurate replication of cellular phenotype and of the molecules involved in genotype/phenotype linkage is necessary for the origin of evolution and may be considered the fundamental principle of life.

Identifiants

pubmed: 38346554
pii: S0303-2647(24)00039-X
doi: 10.1016/j.biosystems.2024.105154
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105154

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The author has no competing interests to declare.

Auteurs

Seymour Garte (S)

Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, 160 Frelinghuysen Road, Piscataway, NJ, 08854-8020, USA. Electronic address: sy.garte@rutgers.edu.

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Classifications MeSH