A feedback mechanism controls rDNA copy number evolution in yeast independently of natural selection

Autor: Vicente Arnau, Marina Barba-Aliaga, Gaurav Singh, Javier Ferri, José García-Martínez, José E. Pérez-Ortín
Přispěvatelé: Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España)
Rok vydání: 2022
Předmět:
Zdroj: Arnau Llombart, Vicente Barba-Aliaga, Marina Singh, Gaurav Ferri, Javier García Martínez, José Pérez Ortín, José Enrique 2022 A feedback mechanism controls rDNA copy number evolution in yeast independently of natural selection Plos One 17 9 e0272878
RODERIC. Repositorio Institucional de la Universitat de Valéncia
instname
ISSN: 1932-6203
Popis: Ribosomal DNA (rDNA) is the genetic loci that encodes rRNA in eukaryotes. It is typically arranged as tandem repeats that vary in copy number within the same species. We have recently shown that rDNA repeats copy number in the yeast Saccharomyces cerevisiae is controlled by cell volume via a feedback circuit that senses cell volume by means of the concentration of the free upstream activator factor (UAF). The UAF strongly binds the rDNA gene promoter, but is also able to repress SIR2 deacetylase gene transcription that, in turn, represses rDNA amplification. In this way, the cells with a smaller DNA copy number than what is optimal evolve to increase that copy number until they reach a number that sequestrates free UAF and provokes SIR2 derepression that, in turn, blocks rDNA amplification. Here we propose a mathematical model to show that this evolutionary process can amplify rDNA repeats independently of the selective advantage of yeast cells having bigger or smaller rDNA copy numbers. We test several variants of this process and show that it can explain the observed experimental results independently of natural selection. These results predict that an autoregulated feedback circuit may, in some instances, drive to non Darwinian deterministic evolution for a limited time period.
This work was supported by a grant from MCIN/AEI/10.13039/501100011033 (grant number PID2020-112853GB-C31 to J.E.P-O).
Databáze: OpenAIRE
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