Copy number variants (CNVs) are regions of the genome that vary in integer copy number. CNVs, which comprise both amplifications and deletions of DNA sequence, have been identified across all domains of life, from bacteria and archaea to plants and animals. CNVs are an important source of genetic diversity, and can drive rapid adaptive evolution and progression of heritable and somatic human diseases, such as cancer. However, despite their evolutionary importance and clinical relevance, CNVs remain understudied compared to single-nucleotide variants (SNVs). This is a consequence of the inherent difficulties in detecting CNVs at low-to-intermediate frequencies in heterogeneous populations of cells. Here, we discuss molecular methods used to detect CNVs, the limitations associated with using these techniques, and the application of new and emerging technologies that present solutions to these challenges. The goal of this short review and perspective is to highlight aspects of CNV biology that are understudied and define avenues for further research that address specific gaps in our knowledge of these complex alleles. We describe our recently developed method for CNV detection in which a fluorescent gene functions as a single-cell CNV reporter and present key findings from our evolution experiments in Saccharomyces cerevisiae. Using a CNV reporter, we found that CNVs are generated at a high rate and undergo selection with predictable dynamics across independently evolving replicate populations. Many CNVs appear to be generated through DNA replication-based processes that are mediated by the presence of short, interrupted, inverted-repeat sequences. Our results have important implications for the role of CNVs in evolutionary processes and the molecular mechanisms that underlie CNV formation. We discuss the possible extension of our method to other applications, including tracking the dynamics of CNVs in models of human tumors.
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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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