Emerging evidence reveals that ribosomes are not monolithic but dynamic machines with heterogeneous protein compositions that can reshape ribosomal translational abilities and cellular adaptation to environmental changes. Duplications of ribosomal protein (RP) genes are ubiquitous among organisms and are believed to affect cell function through paralog-specific regulation (e.g., by generating heterogeneous ribosomes) and/or gene dose amplification. However, direct evaluations of their impacts on cell function remain elusive due to the highly heterogeneous cellular RP pool. Here, we engineered a yeast with homogeneous 40S RP paralog compositions, designated homo-40S, by deleting the entire set of alternative duplicated genes encoding yeast 40S RP paralogs. Homo-40S displayed mild growth defects along with high sensitivity to the translation inhibitor paromomycin and a significantly increased stop codon readthrough. Moreover, doubling of the remaining RP paralogous genes in homo-40S rescued these phenotypes markedly, although not fully, compared to the wild-type phenotype, indicating that the dose of 40S RP genes together with the heterogeneity of the contents was vital for maintaining normal translational functionalities and growth robustness. Additional experiments revealed that homo-40S improved paromomycin tolerance via acquisition of bypass mutations or evolved to be diploid to generate fast-growing derivatives, highlighting the mutational robustness of engineered yeast to accommodate environmental and genetic changes. In summary, our work demonstrated that duplicated RP paralogs impart robustness and phenotypic plasticity through both gene dose amplification and paralog-specific regulation, paving the way for the direct study of ribosome biology through monotypic ribosomes with a homogeneous composition of specific RP paralogs.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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