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Charles Boone

Bio: Charles Boone is an academic researcher from University of Toronto. The author has contributed to research in topics: Synthetic genetic array & Gene. The author has an hindex of 100, co-authored 294 publications receiving 42217 citations. Previous affiliations of Charles Boone include Canadian Institute for Advanced Research & Queen's University.


Papers
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Journal ArticleDOI
22 Jan 2010-Science
TL;DR: 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.
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 ~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.

2,225 citations

Journal ArticleDOI
14 Dec 2001-Science
TL;DR: A method for systematic construction of double mutants, termed synthetic genetic array (SGA) analysis, in which a query mutation is crossed to an array of ∼4700 deletion mutants is developed, which should produce a global map of gene function.
Abstract: In Saccharomyces cerevisiae, more than 80% of the ∼6200 predicted genes are nonessential, implying that the genome is buffered from the phenotypic consequences of genetic perturbation. To evaluate function, we developed a method for systematic construction of double mutants, termed synthetic genetic array (SGA) analysis, in which a query mutation is crossed to an array of ∼4700 deletion mutants. Inviable double-mutant meiotic progeny identify functional relationships between genes. SGA analysis of genes with roles in cytoskeletal organization (BNI1,ARP2, ARC40, BIM1), DNA synthesis and repair (SGS1, RAD27), or uncharacterized functions (BBC1, NBP2) generated a network of 291 interactions among 204 genes. Systematic application of this approach should produce a global map of gene function.

2,164 citations

Journal ArticleDOI
06 Feb 2004-Science
TL;DR: Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.
Abstract: A genetic interaction network containing approximately 1000 genes and approximately 4000 interactions was mapped by crossing mutations in 132 different query genes into a set of approximately 4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

2,037 citations

01 Jan 2003
TL;DR: A method called Synthetic Genetic Array (SGA) analysis was developed in this paper, which automates yeast genetics and enables a systematic and high- throughput construction of double mutants from an ordered array of ~4700 viable gene deletion mutants.
Abstract: budding yeast Saccharomyces cerevisiae, ~80% of the ~6000 genes are nonessential, indi- cating that many biological processes are buffered from the phenotypic consequences of genetic per- turbation. To examine these functional relation- ships we developed a method called Synthetic Genetic Array (SGA) analysis, which automates yeast genetics and enables a systematic and high- throughput construction of double mutants from an ordered array of ~4700 viable gene deletion mutants. In particular, double mutants showing reduced fitness (a synthetic sick phenotype) or lethality (a synthetic lethal phenotype) define functional relationships between genes and their corresponding pathways. We have undertaken a project to generate a synthetic genetic interaction network for the yeast cell with the expectation that it will represent a global map of functional relationships amongst most genes. We found that synthetic genetic interactions are more common than anticipated previously, with an average query gene displaying ~30 different interactions. Cluster analysis of a compendium of ~132 SGA screens revealed that genes displaying similar patterns of genetic interactions often encode proteins within the same pathway or complex; therefore, the yeast genetic interaction network predicts precise molec- ular roles of previously uncharacterized genes. Moreover, because a gene deletion mutation pro- vides a model for the effect of a compound that inhibits its corresponding gene product, our com- pendium of synthetic genetic profiles provides a key for determining the cellular targets of small molecules and drugs. Finally, the surprisingly large number of synthetic genetic interactions observed for defined mutations of inbred laboratory yeast strains suggests that digenic interactions of this type may also occur frequently amongst different alleles of genes found within the individuals of an outbred population and thus similar genetic inter- actions may underlie many of the inherited pheno- types in other organisms.

1,927 citations

Journal ArticleDOI
03 Oct 2008-Science
TL;DR: A comparative quality assessment of current yeast interactome data sets is carried out, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information.
Abstract: Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering approximately 20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

1,452 citations


Cited by
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Journal ArticleDOI
TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Abstract: Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

32,980 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: A method that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements is described, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
Abstract: Microarrays can measure the expression of thousands of genes to identify changes in expression between different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. We describe a method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and 84% by using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation and 3 in apoptosis. Surprisingly, four nucleotide excision repair genes were induced, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.

12,102 citations

Journal ArticleDOI
TL;DR: The latest version of STRING more than doubles the number of organisms it covers, and offers an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input.
Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

10,584 citations

Journal ArticleDOI
23 Feb 2007-Cell
TL;DR: The surface of nucleosomes is studded with a multiplicity of modifications that can dictate the higher-order chromatin structure in which DNA is packaged and can orchestrate the ordered recruitment of enzyme complexes to manipulate DNA.

10,046 citations