Cis‐regulator runaway and divergence in asexuals. (1st March 2018)

• Record Type: Journal Article
• Authors: Fyon, Frédéric; Lenormand, Thomas
• Is Part Of: Evolution. Volume 72:Number 3(2018)
• Page Start: 426
• Page End: 439
• Publication Date: 2018-03-01
• Subjects: Allele‐specific expression -- asexuality -- degeneration -- enhancers -- gene expression -- gene regulation evolution -- parthenogenesis -- self‐fertilization -- silencing; Evolution -- Periodicals; Heredity -- Periodicals; Évolution (Biologie) -- Périodiques; Hérédité -- Périodiques; 338.47004094
• DOI: 10.1111/evo.13424
• Languages: English
• ISSNs: 0014-3820

Abstract

Abstract: With the advent of new sequencing technologies, the evolution of gene expression is becoming a subject of intensive genomic research, with sparking debates upon the role played by these kinds of changes in adaptive evolution and speciation. In this article, we model expression evolution in species differing by their reproductive systems. We consider different rates of sexual versus asexual reproduction and the different type of parthenogenesis (apomixis and the various modes of automixis). We show that competition for expression leads to two selective processes on cis ‐regulatory regions that act independently to organism‐level adaptation. Coevolution within regulatory networks allows these processes to occur without strongly modifying expression levels. First, cis ‐regulatory regions such as enhancers evolve in a runaway fashion because they automatically become associated to chromosomes purged from deleterious mutations ("Enhancer Runaway process"). Second, in clonal or nearly clonal species, homologous cis ‐regulatory regions tend to diverge, which leads to haploidization of expression, when they are sufficiently isolated from one another ("Enhancer Divergence process"). We show how these two processes cooccur and vary depending on the level of outcrossing, gene conversion, mitotic recombination, or recombination in automictic species. This study offers thus a baseline to understand patterns of expression evolution across the diversity of eukaryotic species.