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Andrew F. Boe

Bio: Andrew F. Boe is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Neocortex & Gene. The author has an hindex of 6, co-authored 6 publications receiving 6549 citations.

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Journal ArticleDOI
Ed S. Lein1, Michael Hawrylycz1, Nancy Ao2, Mikael Ayres1, Amy Bensinger1, Amy Bernard1, Andrew F. Boe1, Mark S. Boguski3, Mark S. Boguski1, Kevin S. Brockway1, Emi J. Byrnes1, Lin Chen1, Li Chen2, Tsuey-Ming Chen2, Mei Chi Chin1, Jimmy Chong1, Brian E. Crook1, Aneta Czaplinska2, Chinh Dang1, Suvro Datta1, Nick Dee1, Aimee L. Desaki1, Tsega Desta1, Ellen Diep1, Tim A. Dolbeare1, Matthew J. Donelan1, Hong-Wei Dong1, Jennifer G. Dougherty1, Ben J. Duncan1, Amanda Ebbert1, Gregor Eichele4, Lili K. Estin1, Casey Faber1, Benjamin A.C. Facer1, Rick Fields2, Shanna R. Fischer1, Tim P. Fliss1, Cliff Frensley1, Sabrina N. Gates1, Katie J. Glattfelder1, Kevin R. Halverson1, Matthew R. Hart1, John G. Hohmann1, Maureen P. Howell1, Darren P. Jeung1, Rebecca A. Johnson1, Patrick T. Karr1, Reena Kawal1, Jolene Kidney1, Rachel H. Knapik1, Chihchau L. Kuan1, James H. Lake1, Annabel R. Laramee1, Kirk D. Larsen1, Christopher Lau1, Tracy Lemon1, Agnes J. Liang2, Ying Liu2, Lon T. Luong1, Jesse Michaels1, Judith J. Morgan1, Rebecca J. Morgan1, Marty Mortrud1, Nerick Mosqueda1, Lydia Ng1, Randy Ng1, Geralyn J. Orta1, Caroline C. Overly1, Tu H. Pak1, Sheana Parry1, Sayan Dev Pathak1, Owen C. Pearson1, Ralph B. Puchalski1, Zackery L. Riley1, Hannah R. Rockett1, Stephen A. Rowland1, Joshua J. Royall1, Marcos J. Ruiz2, Nadia R. Sarno1, Katherine Schaffnit1, Nadiya V. Shapovalova1, Taz Sivisay1, Clifford R. Slaughterbeck1, Simon Smith1, Kimberly A. Smith1, Bryan I. Smith1, Andy J. Sodt1, Nick N. Stewart1, Kenda-Ruth Stumpf1, Susan M. Sunkin1, Madhavi Sutram1, Angelene Tam2, Carey D. Teemer1, Christina Thaller2, Carol L. Thompson1, Lee R. Varnam1, Axel Visel4, Axel Visel5, Ray M. Whitlock1, Paul Wohnoutka1, Crissa K. Wolkey1, Victoria Y. Wong1, Matthew J.A. Wood2, Murat B. Yaylaoglu2, Rob Young1, Brian L. Youngstrom1, Xu Feng Yuan1, Bin Zhang2, Theresa A. Zwingman1, Allan R. Jones1 
11 Jan 2007-Nature
TL;DR: An anatomically comprehensive digital atlas containing the expression patterns of ∼20,000 genes in the adult mouse brain is described, providing an open, primary data resource for a wide variety of further studies concerning brain organization and function.
Abstract: Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of approximately 20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.

4,944 citations

Journal ArticleDOI
20 Sep 2012-Nature
TL;DR: A transcriptional atlas of the adult human brain is described, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals, to form a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.
Abstract: Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography—the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

2,204 citations

Journal ArticleDOI
11 May 2018-Science
TL;DR: The Ivy Glioblastoma Atlas is presented, an anatomically based transcriptional atlas of human gliOBlastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor.
Abstract: Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor’s molecular and cellular landscapes are complex, and their relationships to histologic features routinely used for diagnosis are unclear. We present the Ivy Glioblastoma Atlas, an anatomically based transcriptional atlas of human glioblastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor. The atlas and its clinical and genomic database are freely accessible online data resources that will serve as a valuable platform for future investigations of glioblastoma pathogenesis, diagnosis, and treatment.

349 citations

Journal ArticleDOI
Trygve E. Bakken1, Jeremy A. Miller1, Songlin Ding1, Susan M. Sunkin1, Kimberly A. Smith1, Lydia Ng1, Aaron Szafer1, Rachel A. Dalley1, Joshua J. Royall1, Tracy Lemon1, Sheila Shapouri1, Kaylynn Aiona1, James M. Arnold1, Jeffrey L. Bennett2, Darren Bertagnolli1, Kristopher Bickley1, Andrew F. Boe1, Krissy Brouner1, Stephanie Butler1, Emi J. Byrnes1, Shiella Caldejon1, Anita Carey1, Shelby Cate1, Mike Chapin1, Jefferey Chen1, Nick Dee1, Tsega Desta1, Tim A. Dolbeare1, Nadia Dotson1, Amanda Ebbert1, Erich Fulfs1, Garrett Gee1, Terri L. Gilbert1, Jeff Goldy1, Lindsey Gourley1, Ben W. Gregor1, Guangyu Gu1, Jon Hall1, Zeb Haradon1, David R. Haynor3, Nika Hejazinia1, Anna Hoerder-Suabedissen4, Robert Howard1, Jay Jochim1, Marty Kinnunen1, Ali Kriedberg1, Chihchau L. Kuan1, Christopher Lau1, Changkyu Lee1, Felix Lee1, Lon T. Luong1, Naveed Mastan1, Ryan May1, Jose Melchor1, Nerick Mosqueda1, Erika Mott1, Kiet Ngo1, Julie Nyhus1, Aaron Oldre1, Eric Olson1, Jody Parente1, Patrick D. Parker1, Sheana Parry1, Julie Pendergraft1, Lydia Potekhina1, Melissa Reding1, Zackery L. Riley1, Tyson Roberts1, Brandon Rogers1, Kate Roll1, David Rosen1, David Sandman1, Melaine Sarreal1, Nadiya V. Shapovalova1, Shu Shi1, Nathan Sjoquist1, Andy J. Sodt1, Robbie Townsend1, Lissette Velasquez1, Udi Wagley1, Wayne Wakeman1, Cassandra White1, Crissa Bennett1, Jennifer Wu1, R.D. Young1, Brian L. Youngstrom1, Paul Wohnoutka1, Richard A. Gibbs5, Jeffrey Rogers5, John G. Hohmann1, Michael Hawrylycz1, Robert F. Hevner6, Zoltán Molnár4, John W. Phillips1, Chinh Dang1, Allan R. Jones1, David G. Amaral2, Amy Bernard1, Ed S. Lein1 
21 Jul 2016-Nature
TL;DR: A high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development is described that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease.
Abstract: The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.

315 citations

Journal ArticleDOI
TL;DR: A marker‐based phenotyping approach is described to reexamine the cytoarchitectural consequences of Reelin deficiency, using high‐throughput histology and newly identified panels of highly specific molecular markers to reveal novel features of abnormal patterning in the male reeler mouse.
Abstract: The disrupted cortical lamination phenotype in reeler mice and subsequent identification of the Reelin signaling pathway have strongly informed models of cortical development. We describe here a marker-based phenotyping approach to reexamine the cytoarchitectural consequences of Reelin deficiency, using high-throughput histology and newly identified panels of highly specific molecular markers. The resulting cell-type-level cytoarchitectural analysis revealed novel features of abnormal patterning in the male reeler mouse not obvious with less specific markers or histology. The reeler cortex has been described as a rough laminar inversion, but the data presented here are not compatible with this model. The reeler cortex is disrupted in a more complex fashion, with some regions showing a mirror-image laminar phenotype. Major rostrocaudal and cell-type-specific differences in the laminar phenotype between cortical areas are detailed. These and similar findings in hippocampus and amygdala have implications for mechanisms of normal brain development and abnormalities in neurodevelopmental disorders. J. Comp. Neurol. 519:2061–2089, 2011. © 2011 Wiley-Liss, Inc.

88 citations


Cited by
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TL;DR: A set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra is generated and enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo.
Abstract: The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universally responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in several Cre-driver lines, including new Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation.

5,365 citations

Journal ArticleDOI
11 Apr 2013-Cell
TL;DR: In this article, the ESC master transcription factors form unusual enhancer domains at most genes that control the pluripotent state, called super-enhancers, which consist of clusters of enhancers that are densely occupied by the master regulators and Mediator.

2,978 citations

Journal ArticleDOI
TL;DR: These findings call into question the concept of a “glial” cell class as the gene profiles of astrocyte and oligodendrocytes are as dissimilar to each other as they are to neurons, for better understanding of neural development, function, and disease.
Abstract: Understanding the cell–cell interactions that control CNS development and function has long been limited by the lack of methods to cleanly separate neural cell types. Here we describe methods for the prospective isolation and purification of astrocytes, neurons, and oligodendrocytes from developing and mature mouse forebrain. We used FACS (fluorescent-activated cell sorting) to isolate astrocytes from transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of an S100β promoter. Using Affymetrix GeneChip Arrays, we then created a transcriptome database of the expression levels of >20,000 genes by gene profiling these three main CNS neural cell types at various postnatal ages between postnatal day 1 (P1) and P30. This database provides a detailed global characterization and comparison of the genes expressed by acutely isolated astrocytes, neurons, and oligodendrocytes. We found that Aldh1L1 is a highly specific antigenic marker for astrocytes with a substantially broader pattern of astrocyte expression than the traditional astrocyte marker GFAP. Astrocytes were enriched in specific metabolic and lipid synthetic pathways, as well as the draper/Megf10 and Mertk/integrin αvβ5 phagocytic pathways suggesting that astrocytes are professional phagocytes. Our findings call into question the concept of a “glial” cell class as the gene profiles of astrocytes and oligodendrocytes are as dissimilar to each other as they are to neurons. This transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes provides a resource to the neuroscience community by providing improved cell-type-specific markers and for better understanding of neural development, function, and disease.

2,838 citations

Journal ArticleDOI
06 Mar 2015-Science
TL;DR: Large-scale single-cell RNA sequencing is used to classify cells in the mouse somatosensory cortex and hippocampal CA1 region and found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex.
Abstract: The mammalian cerebral cortex supports cognitive functions such as sensorimotor integration, memory, and social behaviors. Normal brain function relies on a diverse set of differentiated cell types, including neurons, glia, and vasculature. Here, we have used large-scale single-cell RNA sequencing (RNA-seq) to classify cells in the mouse somatosensory cortex and hippocampal CA1 region. We found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex. We identified numerous marker genes, which allowed alignment with known cell types, morphology, and location. We found a layer I interneuron expressing Pax6 and a distinct postmitotic oligodendrocyte subclass marked by Itpr2. Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.

2,675 citations

Journal ArticleDOI
TL;DR: Harmony, for the integration of single-cell transcriptomic data, identifies broad and fine-grained populations, scales to large datasets, and can integrate sequencing- and imaging-based data.
Abstract: The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony ( https://github.com/immunogenomics/harmony ), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data. Harmony, for the integration of single-cell transcriptomic data, identifies broad and fine-grained populations, scales to large datasets, and can integrate sequencing- and imaging-based data.

2,459 citations