Literature DB >> 33359635

Incorporating antagonistic pleiotropy into models for molecular replicators.

Tianjiao Qu1, Peter Calabrese2, Pratik Singhavi1, John Tower3.   

Abstract

In modern cells, chromosomal genes composed of DNA encode multi-subunit protein/RNA complexes that catalyze the replication of the chromosome and cell. One prevailing theory for the origin of life posits an early stage involving self-replicating macromolecules called replicators, which can be considered genes capable of self-replication. One prevailing theory for the genetics of aging in humans and other organisms is antagonistic pleiotropy, which posits that a gene can be beneficial in one context, and detrimental in another context. We previously reported that the conceptual simplicity of molecular replicators facilitates the generation of two simple models involving antagonistic pleiotropy. Here a third model is proposed, and each of the three models is presented with improved definition of the time variable. Computer simulations were used to calculate the proliferation of a hypothetical two-subunit replicator (AB), when one of the two subunits (B) exhibits antagonistic pleiotropy, leading to an advantage for B to be unstable. In model 1, instability of B yields free A subunits, which in turn stimulate the activity of other AB replicators. In model 2, B is lost and sometimes replaced by a more active mutant form, B'. In model 3, B becomes damaged and loses activity, and its instability allows it to be replaced by a new B. For each model, conditions were identified where instability of B was detrimental, and where instability of B was beneficial. The results are consistent with the hypothesis that antagonistic pleiotropy can promote molecular instability and system complexity, and provide further support for a model linking aging and evolution.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aging; Complexity; Evolution; Origin of life

Mesh:

Year:  2020        PMID: 33359635      PMCID: PMC7870564          DOI: 10.1016/j.biosystems.2020.104333

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  83 in total

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