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Crossover interference mechanism: New lessons from plants.
Rafiei, Nahid; Ronceret, Arnaud.
  • Rafiei N; Plant Molecular Biology Department, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Mexico.
  • Ronceret A; Plant Molecular Biology Department, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Mexico.
Front Cell Dev Biol ; 11: 1156766, 2023.
Article en En | MEDLINE | ID: mdl-37274744
Plants are the source of our understanding of several fundamental biological principles. It is well known that Gregor Mendel discovered the laws of Genetics in peas and that maize was used for the discovery of transposons by Barbara McClintock. Plant models are still useful for the understanding of general key biological concepts. In this article, we will focus on discussing the recent plant studies that have shed new light on the mysterious mechanisms of meiotic crossover (CO) interference, heterochiasmy, obligatory CO, and CO homeostasis. Obligatory CO is necessary for the equilibrated segregation of homologous chromosomes during meiosis. The tight control of the different male and female CO rates (heterochiasmy) enables both the maximization and minimization of genome shuffling. An integrative model can now predict these observed aspects of CO patterning in plants. The mechanism proposed considers the Synaptonemal Complex as a canalizing structure that allows the diffusion of a class I CO limiting factor linearly on synapsed bivalents. The coarsening of this limiting factor along the SC explains the interfering spacing between COs. The model explains the observed coordinated processes between synapsis, CO interference, CO insurance, and CO homeostasis. It also easily explains heterochiasmy just considering the different male and female SC lengths. This mechanism is expected to be conserved in other species.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article