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Dive into the research topics where Darren Bertagnolli is active.

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Featured researches published by Darren Bertagnolli.


Nature | 2012

An anatomically comprehensive atlas of the adult human brain transcriptome

Michael Hawrylycz; Ed Lein; Angela L. Guillozet-Bongaarts; Elaine H. Shen; Lydia Ng; Jeremy A. Miller; Louie N. van de Lagemaat; Kimberly A. Smith; Amanda Ebbert; Zackery L. Riley; Chris Abajian; Christian F. Beckmann; Amy Bernard; Darren Bertagnolli; Andrew F. Boe; Preston M. Cartagena; M. Mallar Chakravarty; Mike Chapin; Jimmy Chong; Rachel A. Dalley; Barry Daly; Chinh Dang; Suvro Datta; Nick Dee; Tim Dolbeare; Vance Faber; David Feng; David Fowler; Jeff Goldy; Benjamin W. Gregor

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.


Nature | 2014

Transcriptional landscape of the prenatal human brain

Jeremy A. Miller; Song Lin Ding; Susan M. Sunkin; Kimberly A. Smith; Lydia Ng; Aaron Szafer; Amanda Ebbert; Zackery L. Riley; Joshua J. Royall; Kaylynn Aiona; James M. Arnold; Crissa Bennet; Darren Bertagnolli; Krissy Brouner; Stephanie Butler; Shiella Caldejon; Anita Carey; Christine Cuhaciyan; Rachel A. Dalley; Nick Dee; Tim Dolbeare; Benjamin Facer; David Feng; Tim P. Fliss; Garrett Gee; Jeff Goldy; Lindsey Gourley; Benjamin W. Gregor; Guangyu Gu; Robert Howard

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.


Nature Neuroscience | 2016

Adult mouse cortical cell taxonomy revealed by single cell transcriptomics

Bosiljka Tasic; Vilas Menon; Thuc Nghi Nguyen; Tae Kyung Kim; Tim Jarsky; Zizhen Yao; Boaz P. Levi; Lucas T. Gray; Staci A. Sorensen; Tim Dolbeare; Darren Bertagnolli; Jeff Goldy; Nadiya V. Shapovalova; Sheana Parry; Chang-Kyu Lee; Kimberly A. Smith; Amy Bernard; Linda Madisen; Susan M. Sunkin; Michael Hawrylycz; Christof Koch; Hongkui Zeng

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type–specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.


Nature | 2016

A comprehensive transcriptional map of primate brain development

Trygve E. Bakken; Jeremy A. Miller; Song Lin Ding; Susan M. Sunkin; Kimberly A. Smith; Lydia Ng; Aaron Szafer; Rachel A. Dalley; Joshua J. Royall; Tracy Lemon; Sheila Shapouri; Kaylynn Aiona; James M. Arnold; Jeffrey L. Bennett; Darren Bertagnolli; Kristopher Bickley; Andrew F. Boe; Krissy Brouner; Stephanie Butler; Emi J. Byrnes; Shiella Caldejon; Anita Carey; Shelby Cate; Mike Chapin; Jefferey Chen; Nick Dee; Tsega Desta; Tim Dolbeare; Nadia Dotson; Amanda Ebbert

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.


Proceedings of the National Academy of Sciences of the United States of America | 2010

Divergent and nonuniform gene expression patterns in mouse brain

John A. Morris; Joshua J. Royall; Darren Bertagnolli; Andrew F. Boe; Josh J. Burnell; Emi J. Byrnes; Cathy Copeland; Tsega Desta; Shanna R. Fischer; Jeff Goldy; Katie J. Glattfelder; Jolene Kidney; Tracy Lemon; Geralyn J. Orta; Sheana Parry; Sayan D. Pathak; Owen C. Pearson; Melissa Reding; Sheila Shapouri; Kimberly A. Smith; Chad Soden; Beth M. Solan; John R. Weller; Joseph S. Takahashi; Caroline C. Overly; Ed Lein; Michael Hawrylycz; John G. Hohmann; Allan R. Jones

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs.


Human Molecular Genetics | 2015

Spatiotemporal dynamics of the postnatal developing primate brain transcriptome

Trygve E. Bakken; Jeremy A. Miller; Rui Luo; Amy Bernard; Jeffrey L. Bennett; Chang Kyu Lee; Darren Bertagnolli; Neelroop N. Parikshak; Kimberly A. Smith; Susan M. Sunkin; David G. Amaral; Daniel H. Geschwind; Ed Lein

Developmental changes in the temporal and spatial regulation of gene expression drive the emergence of normal mature brain function, while disruptions in these processes underlie many neurodevelopmental abnormalities. To solidify our foundational knowledge of such changes in a primate brain with an extended period of postnatal maturation like in human, we investigated the whole-genome transcriptional profiles of rhesus monkey brains from birth to adulthood. We found that gene expression dynamics are largest from birth through infancy, after which gene expression profiles transition to a relatively stable state by young adulthood. Biological pathway enrichment analysis revealed that genes more highly expressed at birth are associated with cell adhesion and neuron differentiation, while genes more highly expressed in juveniles and adults are associated with cell death. Neocortex showed significantly greater differential expression over time than subcortical structures, and this trend likely reflects the protracted postnatal development of the cortex. Using network analysis, we identified 27 co-expression modules containing genes with highly correlated expression patterns that are associated with specific brain regions, ages or both. In particular, one module with high expression in neonatal cortex and striatum that decreases during infancy and juvenile development was significantly enriched for autism spectrum disorder (ASD)-related genes. This network was enriched for genes associated with axon guidance and interneuron differentiation, consistent with a disruption in the formation of functional cortical circuitry in ASD.


Nature | 2018

Shared and distinct transcriptomic cell types across neocortical areas

Bosiljka Tasic; Zizhen Yao; Lucas T. Graybuck; Kimberly A. Smith; Thuc Nghi Nguyen; Darren Bertagnolli; Jeff Goldy; Emma Garren; Michael N. Economo; Sarada Viswanathan; Osnat Penn; Trygve E. Bakken; Vilas Menon; Jeremy A. Miller; Olivia Fong; Karla E. Hirokawa; Kanan Lathia; Christine Rimorin; Michael Tieu; Rachael Larsen; Tamara Casper; Eliza Barkan; Matthew Kroll; Sheana Parry; Nadiya V. Shapovalova; Daniel Hirschstein; Julie Pendergraft; Heather A. Sullivan; Tae Kyung Kim; Aaron Szafer

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.Single-cell transcriptomics of more than 20,000 cells from two functionally distinct areas of the mouse neocortex identifies 133 transcriptomic types, and provides a foundation for understanding the diversity of cortical cell types.


eLife | 2017

Neuropathological and transcriptomic characteristics of the aged brain

Jeremy A. Miller; Angela L. Guillozet-Bongaarts; Laura E. Gibbons; Nadia Postupna; Anne Renz; Allison Beller; Susan M. Sunkin; Lydia Ng; Shannon E. Rose; Kimberly A. Smith; Aaron Szafer; Chris Barber; Darren Bertagnolli; Kristopher Bickley; Krissy Brouner; Shiella Caldejon; Mike Chapin; Mindy L Chua; Natalie M Coleman; Eiron Cudaback; Christine Cuhaciyan; Rachel A. Dalley; Nick Dee; Tsega Desta; Tim Dolbeare; Nadezhda Dotson; Michael Fisher; Nathalie Gaudreault; Garrett Gee; Terri L. Gilbert

As more people live longer, age-related neurodegenerative diseases are an increasingly important societal health issue. Treatments targeting specific pathologies such as amyloid beta in Alzheimer’s disease (AD) have not led to effective treatments, and there is increasing evidence of a disconnect between traditional pathology and cognitive abilities with advancing age, indicative of individual variation in resilience to pathology. Here, we generated a comprehensive neuropathological, molecular, and transcriptomic characterization of hippocampus and two regions cortex in 107 aged donors (median = 90) from the Adult Changes in Thought (ACT) study as a freely-available resource (http://aging.brain-map.org/). We confirm established associations between AD pathology and dementia, albeit with increased, presumably aging-related variability, and identify sets of co-expressed genes correlated with pathological tau and inflammation markers. Finally, we demonstrate a relationship between dementia and RNA quality, and find common gene signatures, highlighting the importance of properly controlling for RNA quality when studying dementia.


Science | 2018

An anatomic transcriptional atlas of human glioblastoma

Ralph B. Puchalski; Nameeta Shah; Jeremy A. Miller; Rachel A. Dalley; Steve R. Nomura; Jae-Guen Yoon; Kimberly A. Smith; Michael Lankerovich; Darren Bertagnolli; Kris Bickley; Andrew F. Boe; Krissy Brouner; Stephanie Butler; Shiella Caldejon; Mike Chapin; Suvro Datta; Nick Dee; Tsega Desta; Tim Dolbeare; Nadezhda Dotson; Amanda Ebbert; David Feng; Xu Feng; Michael Fisher; Garrett Gee; Jeff Goldy; Lindsey Gourley; Benjamin W. Gregor; Guangyu Gu; Nika Hejazinia

Anatomically correct tumor genomics Glioblastoma is the most lethal form of human brain cancer. The genomic alterations and gene expression profiles characterizing this tumor type have been widely studied. Puchalski et al. created the Ivy Glioblastoma Atlas, a freely available online resource for the research community. The atlas, a collaborative effort between bioinformaticians and pathologists, maps molecular features of glioblastomas, such as transcriptional signatures, to histologically defined anatomical regions of the tumors. The relationships identified in this atlas, in conjunction with associated databases of clinical and genomic information, could provide new insights into the pathogenesis, diagnosis, and treatment of glioblastoma. Science, this issue p. 660 An online resource maps the molecular genetic features of glioblastoma, a lethal brain cancer, to its anatomic features. 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.


bioRxiv | 2018

Conserved cell types with divergent features between human and mouse cortex

Rebecca Hodge; Trygve E. Bakken; Jeremy A. Miller; Kimberly A. Smith; Eliza Barkan; Lucas T. Graybuck; Jennie L. Close; Brian Long; Osnat Penn; Zizhen Yao; Jeroen Eggermont; Thomas Hollt; Boaz P. Levi; Soraya I. Shehata; Brian D. Aevermann; Allison Beller; Darren Bertagnolli; Krissy Brouner; Tamara Casper; Charles S. Cobbs; Rachel A. Dalley; Nick Dee; Song-Lin Ding; Richard G. Ellenbogen; Olivia Fong; Emma Garren; Jeff Goldy; Ryder P Gwinn; Daniel Hirschstein; C. Dirk Keene

Elucidating the cellular architecture of the human neocortex is central to understanding our cognitive abilities and susceptibility to disease. Here we applied single nucleus RNA-sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cerebral cortex. We identify a highly diverse set of excitatory and inhibitory neuronal types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to a similar mouse cortex single cell RNA-sequencing dataset revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous human and mouse cell types, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain.

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Kimberly A. Smith

Allen Institute for Brain Science

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Jeff Goldy

Allen Institute for Brain Science

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Jeremy A. Miller

Allen Institute for Brain Science

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Nick Dee

Allen Institute for Brain Science

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Rachel A. Dalley

Allen Institute for Brain Science

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Tim Dolbeare

Allen Institute for Brain Science

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Krissy Brouner

Allen Institute for Brain Science

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Susan M. Sunkin

Allen Institute for Brain Science

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Trygve E. Bakken

Allen Institute for Brain Science

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Aaron Szafer

Allen Institute for Brain Science

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