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Sharp NP, Smith DR, Driscoll G, Sun K, Vickerman CM, Martin SCT. Contribution of Spontaneous Mutations to Quantitative and Molecular Variation at the Highly Repetitive rDNA Locus in Yeast. Genome Biol Evol 2023; 15:evad179. [PMID: 37847861 PMCID: PMC10581546 DOI: 10.1093/gbe/evad179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
The ribosomal DNA array in Saccharomyces cerevisiae consists of many tandem repeats whose copy number is believed to be functionally important but highly labile. Regulatory mechanisms have evolved to maintain copy number by directed mutation, but how spontaneous variation at this locus is generated and selected has not been well characterized. We applied a mutation accumulation approach to quantify the impacts of mutation and selection on this unique genomic feature across hundreds of mutant strains. We find that mutational variance for this trait is relatively high, and that unselected mutations elsewhere in the genome can disrupt copy number maintenance. In consequence, copy number generally declines gradually, consistent with a previously proposed model of rDNA maintenance where a downward mutational bias is normally compensated by mechanisms that increase copy number when it is low. This pattern holds across ploidy levels and strains in the standard lab environment but differs under some stressful conditions. We identify several alleles, gene categories, and genomic features that likely affect copy number, including aneuploidy for chromosome XII. Copy number change is associated with reduced growth in diploids, consistent with stabilizing selection. Levels of standing variation in copy number are well predicted by a balance between mutation and stabilizing selection, suggesting this trait is not subject to strong diversifying selection in the wild. The rate and spectrum of point mutations within the rDNA locus itself are distinct from the rest of the genome and predictive of polymorphism locations. Our findings help differentiate the roles of mutation and selection and indicate that spontaneous mutation patterns shape several aspects of ribosomal DNA evolution.
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Affiliation(s)
- Nathaniel P Sharp
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Denise R Smith
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Gregory Driscoll
- Department of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Kexin Sun
- Present address: Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Sterling C T Martin
- Present address: Department of Biology, Washington University, St. Louis, Missouri, USA
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Razdaibiedina A, Brechalov A, Friesen H, Usaj MM, Masinas MPD, Suresh HG, Wang K, Boone C, Ba J, Andrews B. PIFiA: Self-supervised Approach for Protein Functional Annotation from Single-Cell Imaging Data. bioRxiv 2023:2023.02.24.529975. [PMID: 36909656 PMCID: PMC10002629 DOI: 10.1101/2023.02.24.529975] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
Fluorescence microscopy data describe protein localization patterns at single-cell resolution and have the potential to reveal whole-proteome functional information with remarkable precision. Yet, extracting biologically meaningful representations from cell micrographs remains a major challenge. Existing approaches often fail to learn robust and noise-invariant features or rely on supervised labels for accurate annotations. We developed PIFiA, (Protein Image-based Functional Annotation), a self-supervised approach for protein functional annotation from single-cell imaging data. We imaged the global yeast ORF-GFP collection and applied PIFiA to generate protein feature profiles from single-cell images of fluorescently tagged proteins. We show that PIFiA outperforms existing approaches for molecular representation learning and describe a range of downstream analysis tasks to explore the information content of the feature profiles. Specifically, we cluster extracted features into a hierarchy of functional organization, study cell population heterogeneity, and develop techniques to distinguish multi-localizing proteins and identify functional modules. Finally, we confirm new PIFiA predictions using a colocalization assay, suggesting previously unappreciated biological roles for several proteins. Paired with a fully interactive website (https://thecellvision.org/pifia/), PIFiA is a resource for the quantitative analysis of protein organization within the cell.
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Affiliation(s)
- Anastasia Razdaibiedina
- Department of Molecular Genetics, University of Toronto, Toronto ON, Canada
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
- Vector Institute for Artificial Intelligence, Toronto ON, Canada
| | - Alexander Brechalov
- Department of Molecular Genetics, University of Toronto, Toronto ON, Canada
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
| | - Helena Friesen
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
| | | | | | | | - Kyle Wang
- Department of Molecular Genetics, University of Toronto, Toronto ON, Canada
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
| | - Charles Boone
- Department of Molecular Genetics, University of Toronto, Toronto ON, Canada
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
- RIKEN Center for Sustainable Resource Science, 2-1 Hirosawa, Wako, Saitama, Japan
| | - Jimmy Ba
- Department of Computer Science, University of Toronto, Toronto ON, Canada
- Vector Institute for Artificial Intelligence, Toronto ON, Canada
| | - Brenda Andrews
- Department of Molecular Genetics, University of Toronto, Toronto ON, Canada
- The Donnelly Centre, University of Toronto, Toronto ON, Canada
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Abstract
In addition to the canonical right-handed double helix, other DNA structures, termed 'non-B DNA', can form in the genomes across the tree of life. Non-B DNA regulates multiple cellular processes, including replication and transcription, yet its presence is associated with elevated mutagenicity and genome instability. These discordant cellular roles fuel the enormous potential of non-B DNA to drive genomic and phenotypic evolution. Here we discuss recent studies establishing non-B DNA structures as novel functional elements subject to natural selection, affecting evolution of transposable elements (TEs), and specifying centromeres. By highlighting the contributions of non-B DNA to repeated evolution and adaptation to changing environments, we conclude that evolutionary analyses should include a perspective of not only DNA sequence, but also its structure.
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Affiliation(s)
- Kateryna D Makova
- Department of Biology, Penn State University, 310 Wartik Laboratory, University Park, PA 16802, USA.
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Bowater RP, Bohálová N, Brázda V. Interaction of Proteins with Inverted Repeats and Cruciform Structures in Nucleic Acids. Int J Mol Sci 2022; 23:ijms23116171. [PMID: 35682854 PMCID: PMC9180970 DOI: 10.3390/ijms23116171] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 05/26/2022] [Accepted: 05/30/2022] [Indexed: 01/27/2023] Open
Abstract
Cruciforms occur when inverted repeat sequences in double-stranded DNA adopt intra-strand hairpins on opposing strands. Biophysical and molecular studies of these structures confirm their characterization as four-way junctions and have demonstrated that several factors influence their stability, including overall chromatin structure and DNA supercoiling. Here, we review our understanding of processes that influence the formation and stability of cruciforms in genomes, covering the range of sequences shown to have biological significance. It is challenging to accurately sequence repetitive DNA sequences, but recent advances in sequencing methods have deepened understanding about the amounts of inverted repeats in genomes from all forms of life. We highlight that, in the majority of genomes, inverted repeats are present in higher numbers than is expected from a random occurrence. It is, therefore, becoming clear that inverted repeats play important roles in regulating many aspects of DNA metabolism, including replication, gene expression, and recombination. Cruciforms are targets for many architectural and regulatory proteins, including topoisomerases, p53, Rif1, and others. Notably, some of these proteins can induce the formation of cruciform structures when they bind to DNA. Inverted repeat sequences also influence the evolution of genomes, and growing evidence highlights their significance in several human diseases, suggesting that the inverted repeat sequences and/or DNA cruciforms could be useful therapeutic targets in some cases.
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Affiliation(s)
- Richard P. Bowater
- School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK;
| | - Natália Bohálová
- Department of Biophysical Chemistry and Molecular Oncology, Institute of Biophysics of the Czech Academy of Sciences, 61265 Brno, Czech Republic;
- Department of Experimental Biology, Faculty of Science, Masaryk University, Kamenice 5, 62500 Brno, Czech Republic
| | - Václav Brázda
- Department of Biophysical Chemistry and Molecular Oncology, Institute of Biophysics of the Czech Academy of Sciences, 61265 Brno, Czech Republic;
- Correspondence:
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