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Benjamin Ouellette

Bio: Benjamin Ouellette is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Connectome & Gene. The author has an hindex of 12, co-authored 14 publications receiving 3476 citations. Previous affiliations of Benjamin Ouellette include Ontario Institute for Cancer Research & McGill University.
Topics: Connectome, Gene, Chromosome 19, Chromosome 21, Genome

Papers
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Journal ArticleDOI
10 Apr 2014-Nature
TL;DR: A brain-wide, cellular-level, mesoscale connectome for the mouse, using enhanced green fluorescent protein-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain.
Abstract: Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

2,051 citations

Journal ArticleDOI
TL;DR: The Biomolecular Interaction Network Database (BIND) archives biomolecular interaction, reaction, complex and pathway information and provides users with methods to discover interactions and molecular mechanisms.
Abstract: The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues.

635 citations

Journal ArticleDOI
30 Oct 2019-Nature
TL;DR: Using mouse lines in which subsets of neurons are genetically labelled, the authors provide generalized anatomical rules for connections within and between the cortex and thalamus, showing that cell-class-specific connections are organized in a shallow hierarchy within the mouse corticothalamic network.
Abstract: The mammalian cortex is a laminar structure containing many areas and cell types that are densely interconnected in complex ways, and for which generalizable principles of organization remain mostly unknown. Here we describe a major expansion of the Allen Mouse Brain Connectivity Atlas resource1, involving around a thousand new tracer experiments in the cortex and its main satellite structure, the thalamus. We used Cre driver lines (mice expressing Cre recombinase) to comprehensively and selectively label brain-wide connections by layer and class of projection neuron. Through observations of axon termination patterns, we have derived a set of generalized anatomical rules to describe corticocortical, thalamocortical and corticothalamic projections. We have built a model to assign connection patterns between areas as either feedforward or feedback, and generated testable predictions of hierarchical positions for individual cortical and thalamic areas and for cortical network modules. Our results show that cell-class-specific connections are organized in a shallow hierarchy within the mouse corticothalamic network. Using mouse lines in which subsets of neurons are genetically labelled, the authors provide generalized anatomical rules for connections within and between the cortex and thalamus.

379 citations

Journal ArticleDOI
TL;DR: A high-throughput in situ hybridization (ISH), imaging and data processing pipeline to describe whole brain gene expression patterns in Cre driver mice is established and publicly available via the Allen Institute's Transgenic Characterization database.
Abstract: Significant advances in circuit-level analyses of the brain require tools that allow for labeling, modulation of gene expression, and monitoring and manipulation of cellular activity in specific cell types and/or anatomical regions. Large-scale projects and individual laboratories have produced hundreds of gene-specific promoter-driven Cre mouse lines invaluable for enabling genetic access to subpopulations of cells in the brain. However, the potential utility of each line may not be fully realized without systematic whole brain characterization of transgene expression patterns. We established a high-throughput in situ hybridization, imaging and data processing pipeline to describe whole brain gene expression patterns in Cre driver mice. Currently, anatomical data from over 100 Cre driver lines are publicly available via the Allen Institute’s Transgenic Characterization database, which can be used to assist researchers in choosing the appropriate Cre drivers for functional, molecular, or connectional studies of different regions and/or cell types in the brain.

376 citations

Journal ArticleDOI
01 Mar 2011-Mbio
TL;DR: Genetic comparisons revealed that the genomes of the two representative C. gattii strains (genotypes VGI and VGIIa) are colinear for the majority of chromosomes, with some minor rearrangements, however, multiortholog phylogenetic analysis and an evaluation of gene/sequence conservation support the existence of speciation within the C. Gattii complex.
Abstract: Cryptococcus gattii recently emerged as the causative agent of cryptococcosis in healthy individuals in western North America, despite previous characterization of the fungus as a pathogen in tropical or subtropical regions. As a foundation to study the genetics of virulence in this pathogen, we sequenced the genomes of a strain (WM276) representing the predominant global molecular type (VGI) and a clinical strain (R265) of the major genotype (VGIIa) causing disease in North America. We compared these C. gattii genomes with each other and with the genomes of representative strains of the two varieties of Cryptococcus neoformans that generally cause disease in immunocompromised people. Our comparisons included chromosome alignments, analysis of gene content and gene family evolution, and comparative genome hybridization (CGH). These studies revealed that the genomes of the two representative C. gattii strains (genotypes VGI and VGIIa) are colinear for the majority of chromosomes, with some minor rearrangements. However, multiortholog phylogenetic analysis and an evaluation of gene/sequence conservation support the existence of speciation within the C. gattii complex. More extensive chromosome rearrangements were observed upon comparison of the C. gattii and the C. neoformans genomes. Finally, CGH revealed considerable variation in clinical and environmental isolates as well as changes in chromosome copy numbers in C. gattii isolates displaying fluconazole heteroresistance.

190 citations


Cited by
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Journal ArticleDOI
25 Oct 1996-Science
TL;DR: The genome of the yeast Saccharomyces cerevisiae has been completely sequenced through a worldwide collaboration and provides information about the higher order organization of yeast's 16 chromosomes and allows some insight into their evolutionary history.
Abstract: The genome of the yeast Saccharomyces cerevisiae has been completely sequenced through a worldwide collaboration. The sequence of 12,068 kilobases defines 5885 potential protein-encoding genes, approximately 140 genes specifying ribosomal RNA, 40 genes for small nuclear RNA molecules, and 275 transfer RNA genes. In addition, the complete sequence provides information about the higher order organization of yeast's 16 chromosomes and allows some insight into their evolutionary history. The genome shows a considerable amount of apparent genetic redundancy, and one of the major problems to be tackled during the next stage of the yeast genome project is to elucidate the biological functions of all of these genes.

4,254 citations

Journal ArticleDOI
TL;DR: BioGRID is a freely accessible database of physical and genetic interactions that includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens.
Abstract: Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.

3,794 citations

Journal ArticleDOI
01 Dec 1996-Genetics
TL;DR: A novel multienzyme approach was used to generate a set of highly representative genomic libraries from S. cerevisiae and a unique host strain was created that contains three easily assayed reporter genes, each under the control of a different inducible promoter.
Abstract: The two-hybrid system is a powerful technique for detecting protein-protein interactions that utilizes the well-developed molecular genetics of the yeast Saccharomyces cerevisiae. However, the full potential of this technique has not been realized due to limitations imposed by the components available for use in the system. These limitations include unwieldy plasmid vectors, incomplete or poorly designed two-hybrid libraries, and host strains that result in the selection of large numbers of false positives. We have used a novel multienzyme approach to generate a set of highly representative genomic libraries from S. cerevisiae. In addition, a unique host strain was created that contains three easily assayed reporter genes, each under the control of a different inducible promoter. This host strain is extremely sensitive to weak interactions and eliminates nearly all false positives using simple plate assays. Improved vectors were also constructed that simplify the construction of the gene fusions necessary for the two-hybrid system. Our analysis indicates that the libraries and host strain provide significant improvements in both the number of interacting clones identified and the efficiency of two-hybrid selections.

2,705 citations

Journal ArticleDOI
TL;DR: The most important new developments in STRING 8 over previous releases include a URL-based programming interface, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures.
Abstract: Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein–protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a metadatabase that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein–protein interactions currently available. STRING can be reached at http://string-db.org/.

2,394 citations

Journal ArticleDOI
10 Apr 2014-Nature
TL;DR: A brain-wide, cellular-level, mesoscale connectome for the mouse, using enhanced green fluorescent protein-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain.
Abstract: Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

2,051 citations