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- W3088446573 abstract "Abstract Background Mitochondrial function requires numerous genetic interactions between mitochondrial- and nuclear- encoded genes. While selection for optimal mitonuclear interactions should result in coevolution between both genomes, evidence for mitonuclear coadaptation is challenging to document. Genetic models where mitonuclear interactions can be explored are needed. Results We systematically exchanged mtDNAs between 15 Saccharomyces cerevisiae isolates from a variety of ecological niches to create 225 unique mitochondrial-nuclear genotypes. Analysis of phenotypic profiles confirmed that environmentally-sensitive interactions between mitochondrial and nuclear genotype contributed to growth differences. Exchanges of mtDNAs between strains of the same or different clades were just as likely to demonstrate mitonuclear epistasis although epistatic effect sizes increased with genetic distances. Strains with their original mtDNAs were more fit than strains with synthetic mitonuclear combinations when grown in media that resembled isolation habitats. Conclusions This study shows that natural variation in mitonuclear interactions contributes to fitness landscapes. Multiple examples of coadapted mitochondrial-nuclear genotypes suggest that selection for mitonuclear interactions may play a role in helping yeasts adapt to novel environments and promote coevolution." @default.
- W3088446573 created "2020-10-01" @default.
- W3088446573 creator A5019393394 @default.
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- W3088446573 creator A5061077501 @default.
- W3088446573 creator A5086160189 @default.
- W3088446573 creator A5086375967 @default.
- W3088446573 date "2020-09-25" @default.
- W3088446573 modified "2023-10-03" @default.
- W3088446573 title "Mitochondrial-nuclear coadaptation revealed through mtDNA replacements in Saccharomyces cerevisiae" @default.
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- W3088446573 doi "https://doi.org/10.1186/s12862-020-01685-6" @default.
- W3088446573 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7517635" @default.
- W3088446573 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32977769" @default.
- W3088446573 hasPublicationYear "2020" @default.
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