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Colak R, Kim T, Michaut M, Sun M, Irimia M, Bellay J, Myers CL, Blencowe BJ, Kim PM. Distinct types of disorder in the human proteome: functional implications for alternative splicing. PLoS Comput Biol 2013; 9:e1003030. [PMID: 23633940 PMCID: PMC3635989 DOI: 10.1371/journal.pcbi.1003030] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [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: 05/14/2012] [Accepted: 02/26/2013] [Indexed: 01/07/2023] Open
Abstract
Intrinsically disordered regions have been associated with various cellular processes and are implicated in several human diseases, but their exact roles remain unclear. We previously defined two classes of conserved disordered regions in budding yeast, referred to as "flexible" and "constrained" conserved disorder. In flexible disorder, the property of disorder has been positionally conserved during evolution, whereas in constrained disorder, both the amino acid sequence and the property of disorder have been conserved. Here, we show that flexible and constrained disorder are widespread in the human proteome, and are particularly common in proteins with regulatory functions. Both classes of disordered sequences are highly enriched in regions of proteins that undergo tissue-specific (TS) alternative splicing (AS), but not in regions of proteins that undergo general (i.e., not tissue-regulated) AS. Flexible disorder is more highly enriched in TS alternative exons, whereas constrained disorder is more highly enriched in exons that flank TS alternative exons. These latter regions are also significantly more enriched in potential phosphosites and other short linear motifs associated with cell signaling. We further show that cancer driver mutations are significantly enriched in regions of proteins associated with TS and general AS. Collectively, our results point to distinct roles for TS alternative exons and flanking exons in the dynamic regulation of protein interaction networks in response to signaling activity, and they further suggest that alternatively spliced regions of proteins are often functionally altered by mutations responsible for cancer.
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Affiliation(s)
- Recep Colak
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - TaeHyung Kim
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Magali Michaut
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
| | - Mark Sun
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Manuel Irimia
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
| | - Jeremy Bellay
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Chad L. Myers
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Benjamin J. Blencowe
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
- * E-mail: (BJB); (PMK)
| | - Philip M. Kim
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- * E-mail: (BJB); (PMK)
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Koch EN, Costanzo M, Bellay J, Deshpande R, Chatfield-Reed K, Chua G, D'Urso G, Andrews BJ, Boone C, Myers CL. Conserved rules govern genetic interaction degree across species. Genome Biol 2012; 13:R57. [PMID: 22747640 PMCID: PMC3491379 DOI: 10.1186/gb-2012-13-7-r57] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2011] [Accepted: 07/02/2012] [Indexed: 11/10/2022] Open
Abstract
Background Synthetic genetic interactions have recently been mapped on a genome scale in the budding yeast Saccharomyces cerevisiae, providing a functional view of the central processes of eukaryotic life. Currently, comprehensive genetic interaction networks have not been determined for other species, and we therefore sought to model conserved aspects of genetic interaction networks in order to enable the transfer of knowledge between species. Results Using a combination of physiological and evolutionary properties of genes, we built models that successfully predicted the genetic interaction degree of S. cerevisiae genes. Importantly, a model trained on S. cerevisiae gene features and degree also accurately predicted interaction degree in the fission yeast Schizosaccharomyces pombe, suggesting that many of the predictive relationships discovered in S. cerevisiae also hold in this evolutionarily distant yeast. In both species, high single mutant fitness defect, protein disorder, pleiotropy, protein-protein interaction network degree, and low expression variation were significantly predictive of genetic interaction degree. A comparison of the predicted genetic interaction degrees of S. pombe genes to the degrees of S. cerevisiae orthologs revealed functional rewiring of specific biological processes that distinguish these two species. Finally, predicted differences in genetic interaction degree were independently supported by differences in co-expression relationships of the two species. Conclusions Our findings show that there are common relationships between gene properties and genetic interaction network topology in two evolutionarily distant species. This conservation allows use of the extensively mapped S. cerevisiae genetic interaction network as an orthology-independent reference to guide the study of more complex species.
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Bellay J, Atluri G, Sing TL, Toufighi K, Costanzo M, Ribeiro PSM, Pandey G, Baller J, VanderSluis B, Michaut M, Han S, Kim P, Brown GW, Andrews BJ, Boone C, Kumar V, Myers CL. Putting genetic interactions in context through a global modular decomposition. Genome Res 2011; 21:1375-87. [PMID: 21715556 DOI: 10.1101/gr.117176.110] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Genetic interactions provide a powerful perspective into gene function, but our knowledge of the specific mechanisms that give rise to these interactions is still relatively limited. The availability of a global genetic interaction map in Saccharomyces cerevisiae, covering ∼30% of all possible double mutant combinations, provides an unprecedented opportunity for an unbiased assessment of the native structure within genetic interaction networks and how it relates to gene function and modular organization. Toward this end, we developed a data mining approach to exhaustively discover all block structures within this network, which allowed for its complete modular decomposition. The resulting modular structures revealed the importance of the context of individual genetic interactions in their interpretation and revealed distinct trends among genetic interaction hubs as well as insights into the evolution of duplicate genes. Block membership also revealed a surprising degree of multifunctionality across the yeast genome and enabled a novel association of VIP1 and IPK1 with DNA replication and repair, which is supported by experimental evidence. Our modular decomposition also provided a basis for testing the between-pathway model of negative genetic interactions and within-pathway model of positive genetic interactions. While we find that most modular structures involving negative genetic interactions fit the between-pathway model, we found that current models for positive genetic interactions fail to explain 80% of the modular structures detected. We also find differences between the modular structures of essential and nonessential genes.
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Affiliation(s)
- Jeremy Bellay
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota 55455, USA
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Li Z, Vizeacoumar FJ, Bahr S, Li J, Warringer J, Vizeacoumar FS, Min R, Vandersluis B, Bellay J, Devit M, Fleming JA, Stephens A, Haase J, Lin ZY, Baryshnikova A, Lu H, Yan Z, Jin K, Barker S, Datti A, Giaever G, Nislow C, Bulawa C, Myers CL, Costanzo M, Gingras AC, Zhang Z, Blomberg A, Bloom K, Andrews B, Boone C. Systematic exploration of essential yeast gene function with temperature-sensitive mutants. Nat Biotechnol 2011; 29:361-7. [PMID: 21441928 DOI: 10.1038/nbt.1832] [Citation(s) in RCA: 296] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2011] [Accepted: 03/01/2011] [Indexed: 11/09/2022]
Abstract
Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (∼45%) of the 1,101 essential yeast genes, with ∼30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)-based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes.
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Affiliation(s)
- Zhijian Li
- Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
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Bellay J, Han S, Michaut M, Kim T, Costanzo M, Andrews BJ, Boone C, Bader GD, Myers CL, Kim PM. Bringing order to protein disorder through comparative genomics and genetic interactions. Genome Biol 2011. [PMID: 21324131 DOI: 10.1186/gb‐2011‐12‐2‐r14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Intrinsically disordered regions are widespread, especially in proteomes of higher eukaryotes. Recently, protein disorder has been associated with a wide variety of cellular processes and has been implicated in several human diseases. Despite its apparent functional importance, the sheer range of different roles played by protein disorder often makes its exact contribution difficult to interpret. RESULTS We attempt to better understand the different roles of disorder using a novel analysis that leverages both comparative genomics and genetic interactions. Strikingly, we find that disorder can be partitioned into three biologically distinct phenomena: regions where disorder is conserved but with quickly evolving amino acid sequences (flexible disorder); regions of conserved disorder with also highly conserved amino acid sequences (constrained disorder); and, lastly, non-conserved disorder. Flexible disorder bears many of the characteristics commonly attributed to disorder and is associated with signaling pathways and multi-functionality. Conversely, constrained disorder has markedly different functional attributes and is involved in RNA binding and protein chaperones. Finally, non-conserved disorder lacks clear functional hallmarks based on our analysis. CONCLUSIONS Our new perspective on protein disorder clarifies a variety of previous results by putting them into a systematic framework. Moreover, the clear and distinct functional association of flexible and constrained disorder will allow for new approaches and more specific algorithms for disorder detection in a functional context. Finally, in flexible disordered regions, we demonstrate clear evolutionary selection of protein disorder with little selection on primary structure, which has important implications for sequence-based studies of protein structure and evolution.
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Affiliation(s)
- Jeremy Bellay
- Department of Computer Science and Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, MN 55455, USA
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Bellay J, Han S, Michaut M, Kim T, Costanzo M, Andrews BJ, Boone C, Bader GD, Myers CL, Kim PM. Bringing order to protein disorder through comparative genomics and genetic interactions. Genome Biol 2011; 12:R14. [PMID: 21324131 PMCID: PMC3188796 DOI: 10.1186/gb-2011-12-2-r14] [Citation(s) in RCA: 115] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2010] [Revised: 02/01/2011] [Accepted: 02/16/2011] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Intrinsically disordered regions are widespread, especially in proteomes of higher eukaryotes. Recently, protein disorder has been associated with a wide variety of cellular processes and has been implicated in several human diseases. Despite its apparent functional importance, the sheer range of different roles played by protein disorder often makes its exact contribution difficult to interpret. RESULTS We attempt to better understand the different roles of disorder using a novel analysis that leverages both comparative genomics and genetic interactions. Strikingly, we find that disorder can be partitioned into three biologically distinct phenomena: regions where disorder is conserved but with quickly evolving amino acid sequences (flexible disorder); regions of conserved disorder with also highly conserved amino acid sequences (constrained disorder); and, lastly, non-conserved disorder. Flexible disorder bears many of the characteristics commonly attributed to disorder and is associated with signaling pathways and multi-functionality. Conversely, constrained disorder has markedly different functional attributes and is involved in RNA binding and protein chaperones. Finally, non-conserved disorder lacks clear functional hallmarks based on our analysis. CONCLUSIONS Our new perspective on protein disorder clarifies a variety of previous results by putting them into a systematic framework. Moreover, the clear and distinct functional association of flexible and constrained disorder will allow for new approaches and more specific algorithms for disorder detection in a functional context. Finally, in flexible disordered regions, we demonstrate clear evolutionary selection of protein disorder with little selection on primary structure, which has important implications for sequence-based studies of protein structure and evolution.
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Affiliation(s)
- Jeremy Bellay
- Department of Computer Science and Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, MN 55455, USA
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Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED, Sevier CS, Ding H, Koh JLY, Toufighi K, Mostafavi S, Prinz J, St Onge RP, VanderSluis B, Makhnevych T, Vizeacoumar FJ, Alizadeh S, Bahr S, Brost RL, Chen Y, Cokol M, Deshpande R, Li Z, Lin ZY, Liang W, Marback M, Paw J, San Luis BJ, Shuteriqi E, Tong AHY, van Dyk N, Wallace IM, Whitney JA, Weirauch MT, Zhong G, Zhu H, Houry WA, Brudno M, Ragibizadeh S, Papp B, Pál C, Roth FP, Giaever G, Nislow C, Troyanskaya OG, Bussey H, Bader GD, Gingras AC, Morris QD, Kim PM, Kaiser CA, Myers CL, Andrews BJ, Boone C. The genetic landscape of a cell. Science 2010; 327:425-31. [PMID: 20093466 DOI: 10.1126/science.1180823] [Citation(s) in RCA: 1580] [Impact Index Per Article: 112.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
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Affiliation(s)
- Michael Costanzo
- Banting and Best Department of Medical Research, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada
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