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The genomic distribution of transposable elements is driven by spatially variable purifying selection

It is widely accepted that the genomic distribution of transposable elements (TEs) mainly reflects the outcome of purifying selection and insertion bias (1). Nevertheless, the relative importance of these two evolutionary forces could not be tested thoroughly. Here, we introduce an experimental syst...

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Detalles Bibliográficos
Autores principales: Langmüller, Anna M, Nolte, Viola, Dolezal, Marlies, Schlötterer, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516647/
https://www.ncbi.nlm.nih.gov/pubmed/37560917
http://dx.doi.org/10.1093/nar/gkad635
Descripción
Sumario:It is widely accepted that the genomic distribution of transposable elements (TEs) mainly reflects the outcome of purifying selection and insertion bias (1). Nevertheless, the relative importance of these two evolutionary forces could not be tested thoroughly. Here, we introduce an experimental system, which allows separating purifying selection from TE insertion bias. We used experimental evolution to study the TE insertion patterns in Drosophila simulans founder populations harboring 1040 insertions of an active P-element. After 10 generations at a large population size, we detected strong selection against P-element insertions. The exception were P-element insertions in genomic regions for which a strong insertion bias has been proposed (2–4). Because recurrent P-element insertions cannot explain this pattern, we conclude that purifying selection, with variable strength along the chromosomes, is the major determinant of the genomic distribution of P-elements. Genomic regions with relaxed purifying selection against P-element insertions exhibit normal levels of purifying selection against base substitutions. This suggests that different types of purifying selection operate on base substitutions and P-element insertions. Our results highlight the power of experimental evolution to understand basic evolutionary processes, which are difficult to infer from patterns of natural variation alone.