Gene duplication is a key mechanism in evolution for generating new functionality, and it is known to have produced a large proportion of genes. Duplication mechanisms include small-scale, or "local", events such as unequal crossing over and retroposition, together with global events, such as chromosomal or whole genome duplication (WGD). In particular, different studies confirmed that the yeast S. cerevisiae arose from a 100-150 million-year old whole-genome duplication. Detection and study of duplications are usually based on sequence alignment, synteny and phylogenetic techniques, but protein domains are also useful in assessing protein homology. We develop a simple and computationally efficient protein domain architecture comparison method based on the domain assignments available from public databases. We test the accuracy and the reliability of this method in detecting instances of gene duplication in the yeast S. cerevisiae. In particular, we analyze the evolution of WGD and non-WGD paralogs from the domain viewpoint, in comparison with a more standard functional analysis of the genes. A large number of domains is shared by genes that underwent local and global duplications, indicating the existence of a common set of "duplicable" domains. On the other hand, WGD and non-WGD paralogs tend to have different functions. We find evidence that this comes from functional migration within similar domain superfamilies, but also from the existence of small sets of WGD and non-WGD specific domain superfamilies with largely different functions. This observation gives a novel perspective on the finding that WGD paralogs tend to be functionally different from small-scale paralogs. WGD and non-WGD superfamilies carry distinct functions. Finally, the Gene Ontology similarity of paralogs tends to decrease with duplication age, while this tendency is weaker or not observable by the comparison of the domain architectures of paralogs. This suggests that the set of domains composing a protein tends to be maintained, while its function, cellular process or localization diversifies. Overall, the gathered evidence gives a different viewpoint on the biological specificity of the WGD and at the same time points out the validity of domain architecture comparison as a tool for detecting homology.
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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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