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13 results on '"Krissy Brouner"'

1. Integrated multimodal cell atlas of Alzheimer’s disease

Author

Mariano Gabitto, Kyle Travaglini, Jeannelle Ariza, Eitan Kaplan, Brian Long, Victoria Rachleff, Yi Ding, Joseph Mahoney, Nick Dee, Jeff Goldy, Erica Melief, Krissy Brouner, Jazmin Compos, John Campos, Ambrose Carr, Tamara Casper, Rushil Chakrabarty, Michael Clark, Jonah Cool, Rachel Dalley, Martin Darvas, Tim Dolbeare, Song-Lin Ding, Tom Egdorf, Luke Esposito, Rebecca Ferrer, Rohan Gala, Amanda Gary, Jessica Gloe, Nathan Guilford, Junitta Guzman, Windy Ho, Tim Jarsky, Nelson Johansen, Brian Kalmbach, Lisa Keene, Sarah Khawand, Mitchell Kilgore, Amanda Kirkland, Michael Kunst, Brian Lee, Christine Mac Donald, Jocelin Malone, Zoe Maltzer, Naomi Martin, Rachel McCue, Delissa McMillen, Emma Meyerdierks, Kelly Meyers, Tyler Mollenkopf, Mark Montine, Amber Nolan, Julie Nyhus, Paul Olsen, Maiya Pacleb, Trangthanh Pham, Christina Pom, Nadia Postupna, Augustin Ruiz, Aimee Schantz, Staci Sorensen, Brian Staats, Matt Sullivan, Susan Sunkin, Carol Thompson, Michael Tieu, Jonathan Ting, Amy Torkelson, Tracy Tran, Nasmil Valera Cuevas, Ming-Qiang Wang, Jack Waters, Angela Wilson, David Haynor, Nicole Gatto, Suman Jayadev, Shoaib Mufti, Lydia Ng, Shubhabrata Mukherjee, Paul Crane, Caitlin Latimer, Boaz Levi, Kimberly Smith, Jennie Close, Jeremy Miller, Rebecca Hodge, Eric Larson, Thomas Grabowski, Michael Hawrylycz, C. Keene, and Ed Lein

Abstract

Alzheimer’s disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses the BRAIN Initiative Cell Census Network experimental practices, combining quantitative neuropathology with single cell genomics and spatial transcriptomics, to understand the impact of disease progression on middle temporal gyrus cell types. We used quantitative neuropathology to place 84 cases spanning the spectrum of AD pathology along a continuous disease pseudoprogression score. We used multiomic technologies to profile single nuclei from each donor, mapping their identity to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research at SEA-AD.org.

Published
2023

2. Integrated multimodal cell atlas of Alzheimer’s disease

Author

Mariano I. Gabitto, Kyle J. Travaglini, Victoria M. Rachleff, Eitan S. Kaplan, Brian Long, Jeanelle Ariza, Yi Ding, Joseph T. Mahoney, Nick Dee, Jeff Goldy, Erica J. Melief, Krissy Brouner, Jazmin Campos, John Campos, Ambrose J. Carr, Tamara Casper, Rushil Chakrabarty, Michael Clark, Jonah Cool, Nasmil J. Valera Cuevas, Rachel Dalley, Martin Darvas, Song-Lin Ding, Tim Dolbeare, Christine L. Mac Donald, Tom Egdorf, Luke Esposito, Rebecca Ferrer, Rohan Gala, Amanda Gary, Jessica Gloe, Nathan Guilford, Junitta Guzman, Daniel Hirschstein, Windy Ho, Tim Jarksy, Nelson Johansen, Brian E. Kalmbach, Lisa M. Keene, Sarah Khawand, Mitch Kilgore, Amanda Kirkland, Michael Kunst, Brian R. Lee, Jocelin Malone, Zoe Maltzer, Naomi Martin, Rachel McCue, Delissa McMillen, Emma Meyerdierks, Kelly P. Meyers, Tyler Mollenkopf, Mark Montine, Amber L. Nolan, Julie Nyhus, Paul A. Olsen, Maiya Pacleb, Nicholas Peña, Thanh Pham, Christina Alice Pom, Nadia Postupna, Augustin Ruiz, Aimee M. Schantz, Nadiya V. Shapovalova, Staci A. Sorensen, Brian Staats, Matt Sullivan, Susan M. Sunkin, Carol Thompson, Michael Tieu, Jonathan Ting, Amy Torkelson, Tracy Tran, Ming-Qiang Wang, Jack Waters, Angela M. Wilson, David Haynor, Nicole Gatto, Suman Jayadev, Shoaib Mufti, Lydia Ng, Shubhabrata Mukherjee, Paul K. Crane, Caitlin S. Latimer, Boaz P. Levi, Kimberly Smith, Jennie L. Close, Jeremy A. Miller, Rebecca D. Hodge, Eric B. Larson, Thomas J. Grabowski, Michael Hawrylycz, C. Dirk Keene, and Ed S. Lein

Abstract

Alzheimer’s disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research atSEA-AD.org.

Published
2023

3. Signature morpho-electric properties of diverse GABAergic interneurons in the human neocortex

Author

Brian Lee, Rachel Dalley, Jeremy A Miller, Thomas Chartrand, Jennie Close, Rusty Mann, Alice Mukora, Lindsay Ng, Lauren Alfiler, Katherine Baker, Darren Bertagnolli, Krissy Brouner, Tamara Casper, Eva Csajbok, Nick Dee, Nicholas Donadio, Stan L.W. Driessens, Tom Egdorf, Rachel Enstrom, Anna A Galakhova, Amanda Gary, Emily Gelfand, Jeff Goldy, Kristen Hadley, Tim S. Heistek, Dijon Hill, Nelson Johansen, Nik Jorstad, Lisa Kim, Agnes Katalin Kocsis, Lauren Kruse, Michael Kunst, Gabriela Leon, Brian Long, Matthew Mallory, Michelle Maxwell, Medea McGraw, Delissa McMillen, Erica J Melief, Gabor Molnar, Marty T Mortrud, Dakota Newman, Julie Nyhus, Ximena Opitz-Araya, Trangthanh Pham, Alice Pom, Lydia Potekhina, Ram Rajanbabu, Augustin Ruiz, Susan M Sunkin, Ildiko Szots, Naz Taskin, Bargavi Thyagarajan, Michael Tieu, Jessica Trinh, Sara Vargas, David Vumbaco, Femke Waleboer, Natalie Weed, Grace Williams, Julia Wilson, Shenqin Yao, Thomas Zhou, Pal Barzo, Trygve Bakken, Charles Cobbs, Richard G. Ellenbogen, Luke Esposito, Manuel Ferreira, Nathan W Gouwens, Benjamin Grannan, Ryder P. Gwinn, Jason S. Hauptman, Rebecca Hodge, Tim Jarsky, C.Dirk Keene, Andrew L. Ko, Boaz Levi, Jeffrey G. Ojemann, Anoop Patel, Jacob Ruzevick, Daniel L. Silbergeld, Kim Smith, Jack Waters, Hongkui Zeng, Jim Berg, Natalia A. Goriounova, Brian Kalmbach, Christiaan P.J. de Kock, Huib D Mansvelder, Staci A Sorensen, Gabor Tamas, Ed S. Lein, and Jonathan T Ting

Abstract

Human cortical interneurons have been challenging to study due to high diversity and lack of mature brain tissue platforms and genetic targeting tools. We employed rapid GABAergic neuron viral labeling plus unbiased Patch-seq sampling in brain slices to define the signature morpho-electric properties of GABAergic neurons in the human neocortex. Viral targeting greatly facilitated sampling of the SST subclass, including primate specialized double bouquet cells which mapped to two SST transcriptomic types. Multimodal analysis uncovered an SST neuron type with properties inconsistent with original subclass assignment; we instead propose reclassification into PVALB subclass. Our findings provide novel insights about functional properties of human cortical GABAergic neuron subclasses and types and highlight the essential role of multimodal annotation for refinement of emerging transcriptomic cell type taxonomies.One Sentence SummaryViral genetic labeling of GABAergic neurons in humanex vivobrain slices paired with Patch-seq recording yields an in-depth functional annotation of human cortical interneuron subclasses and types and highlights the essential role of multimodal functional annotation for refinement of emerging transcriptomic cell type taxonomies.

Published
2022

4. Morpho-electric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex

Author

Thomas Chartrand, Rachel Dalley, Jennie Close, Natalia A. Goriounova, Brian R. Lee, Rusty Mann, Jeremy A. Miller, Gabor Molnar, Alice Mukora, Lauren Alfiler, Katherine Baker, Trygve E. Bakken, Jim Berg, Darren Bertagnolli, Thomas Braun, Krissy Brouner, Tamara Casper, Eva Adrienn Csajbok, Nick Dee, Tom Egdorf, Rachel Enstrom, Anna A. Galakhova, Amanda Gary, Emily Gelfand, Jeff Goldy, Kristen Hadley, Tim S. Heistek, DiJon Hill, Nik Jorstad, Lisa Kim, Agnes Katalin Kocsis, Lauren Kruse, Michael Kunst, Gabriela Leon, Brian Long, Matthew Mallory, Medea McGraw, Delissa McMillen, Erica J. Melief, Norbert Mihut, Lindsay Ng, Julie Nyhus, Victoria Omstead, Zoltan Peterfi, Alice Pom, Lydia Potekhina, Ramkumar Rajanbabu, Marton Rozsa, Augustin Ruiz, Joanna Sandle, Susan M. Sunkin, Ildiko Szots, Michael Tieu, Martin Toth, Jessica Trinh, Sara Vargas, David Vumbaco, Grace Williams, Julia Wilson, Zizhen Yao, Pal Barzo, Charles Cobbs, Richard G. Ellenbogen, Luke Esposito, Manuel Ferreira, Nathan W. Gouwens, Benjamin Grannan, Ryder P. Gwinn, Jason S. Hauptman, Tim Jarsky, C.Dirk Keene, Andrew L. Ko, Christof Koch, Jeffrey G. Ojemann, Anoop Patel, Jacob Ruzevick, Daniel L. Silberberg, Kimberly Smith, Staci A. Sorensen, Bosiljka Tasic, Jonathan T. Ting, Jack Waters, Christiaan P.J. de Kock, Huib D. Mansvelder, Gabor Tamas, Hongkui Zeng, Brian Kalmbach, and Ed S. Lein

Abstract

Neocortical layer 1 (L1) is a site of convergence between pyramidal neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neuron types with extensive branching in L1, but whether L1 interneurons are similarly diverse is underexplored. Using patch-seq recordings from human neurosurgically resected tissues, we identified four transcriptomically defined subclasses, unique subtypes within those subclasses and additional types with no mouse L1 homologue. Compared with mouse, human subclasses were more strongly distinct from each other across all modalities. Accompanied by higher neuron density and more variable cell sizes compared with mouse, these findings suggest L1 is an evolutionary hotspot, reflecting the increasing demands of regulating the expanding human neocortical circuit.One Sentence SummaryUsing transcriptomics and morpho-electric analyses, we describe innovations in human neocortical layer 1 interneurons.

Published
2022

5. A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex

Author

Kat North, Jasmin Bomben, Shenqin Yao, Bosiljka Tasic, Nicole Hancock, Shea Ransford, Thuyanh V. Nguyen, Ali Williford, Karla E. Hirokawa, Wayne Wakeman, Stefan Mihalas, Lydia Ng, Fiona Griffin, Robert Howard, Julie A. Harris, Rachel Enstrom, Tom Egdorf, Nadezhda Dotson, Eric Lee, Kyla Mace, Amanda Gary, Peter A. Groblewski, Michelle Maxwell, Lydia Potekhina, Tanya L. Daigle, Nhan-Kiet Ngo, Medea McGraw, Krissy Brouner, Philip R. Nicovich, Benjamin Ouellette, Jennifer Luviano, Emily Gelfand, Sam Seid, Chelsea Nayan, Maitham Naeemi, Marty Mortrud, Jackie Swapp, Cho A, Ali Cetin, Hong Gu, Hongkui Zeng, M. J. Taormina, Sophie Lambert, Leonard Kuan, Ruweida Ahmed, Thomas Zhou, Melissa Gorham, Augustin Ruiz, Linzy Casal, Shiella Caldejon, and Quanxin Wang

Subjects
General Neuroscience, Rabies virus, Tracing, Biology, medicine.disease_cause, Entire visual cortex, Visual cortex, medicine.anatomical_structure, medicine, Connectome, Excitatory postsynaptic potential, Neuron, Neuroscience, Brain function
Abstract

Identification of the structural connections between neurons is a prerequisite to understanding brain function. We developed a pipeline to systematically map brain-wide monosynaptic inputs to specific neuronal populations using Cre-driver mouse lines and the recombinant rabies tracing system. We first improved the rabies virus tracing strategy to accurately identify starter cells and to efficiently quantify presynaptic inputs. We then mapped brain-wide presynaptic inputs to different excitatory and inhibitory neuron subclasses in the primary visual cortex and seven higher visual areas. Our results reveal quantitative target-, layer- and cell-class-specific differences in the retrograde connectomes, despite similar global input patterns to different neuronal populations in the same anatomical area. The retrograde connectivity we define is consistent with the presence of the ventral and dorsal visual information processing streams and reveals further subnetworks within the dorsal stream. The hierarchical organization of the entire visual cortex can be derived from intracortical feedforward and feedback pathways mediated by upper- and lower-layer input neurons, respectively. This study expands our knowledge of the brain-wide inputs regulating visual areas and demonstrates that our improved rabies virus tracing strategy can be used to scale up the effort in dissecting connectivity of genetically defined cell populations in the whole mouse brain.

Published
2021

6. Classification of electrophysiological and morphological neuron types in the mouse visual cortex

Author

David Sandman, Brian Lee, Michael Hawrylycz, Sara Kebede, Tom Egdorf, David Reid, Rob Young, Nivretta Thatra, Stefan Mihalas, David Feng, John W. Phillips, Rebecca de Frates, DiJon Hill, Cliff Slaughterbeck, Samuel R Josephsen, Tamara Casper, Xiaoxiao Liu, Hanchuan Peng, Peter Chong, Colin Farrell, Zhi Zhou, Sheana Parry, Jed Perkins, Brian Long, Susan M. Sunkin, Matthew Kroll, Krissy Brouner, Melissa Gorham, Aaron Szafer, Wayne Wakeman, Hong Gu, Marissa Garwood, Daniel Park, Kristen Hadley, Michael S. Fisher, Lydia Potekhina, Ed Lein, Alice Mukora, Hongkui Zeng, Nick Dee, Aaron Oldre, Lindsay Ng, Thomas Braun, Grace Williams, Tracy Lemon, Julie A. Harris, Medea McGraw, Nadezhda Dotson, Philip R. Nicovich, Amanda Gary, Rusty Mann, Alex M. Henry, Caroline Habel, Samuel Dingman, Katherine E. Link, Nathalie Gaudreault, Gilberto J. Soler-Llavina, Thuc Nghi Nguyen, Nicole Blesie, Bosiljka Tasic, Lydia Ng, Christine Cuhaciyan, Tim Jarsky, Keith B. Godfrey, Costas A. Anastassiou, Kirsten Crichton, Josef Sulc, Martin Schroedter, Dan Castelli, Miranda Robertson, Amy Bernard, Lisa Kim, Songlin Ding, Alyse Doperalski, Nathan W. Gouwens, Herman Tung, Tsega Desta, Corinne Teeter, James Harrington, Jonathan T. Ting, Kris Bickley, Anton Arkhipov, Kiet Ngo, Changkyu Lee, Jim Berg, Agata Budzillo, Emma Garren, Tanya L. Daigle, Christof Koch, Rachel A. Dalley, Eliza Barkan, Staci A. Sorensen, Gabe J. Murphy, Shiella Caldejon, and Naz Taskin

Subjects
0301 basic medicine, Genetically modified mouse, Cell type, Patch-Clamp Techniques, Databases, Factual, Action Potentials, Datasets as Topic, Mice, Transgenic, Biology, Article, Neuron types, Mice, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Genes, Reporter, Biocytin, medicine, Animals, Cell shape, Cell Shape, Visual Cortex, Neurons, General Neuroscience, Laboratory mouse, Electrophysiology, 030104 developmental biology, Visual cortex, medicine.anatomical_structure, chemistry, Transcriptome, Neuroscience, 030217 neurology & neurosurgery
Abstract

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

Published
2019

7. Local Connectivity and Synaptic Dynamics in Mouse and Human Neocortex

Author

Michael Tieu, Amy Bernard, Lisa Kim, Samuel Dingman Lee, Tim Jarsky, Corinne Teeter, Martin Schroedter, Alex Hoggarth, Kimberly A. Smith, Amanda Gary, Charles Cobb, John W. Phillips, Christina A. Pom, Herman Tung, Hongkui Zeng, Daniel Carey, Phillip Bohn, Colin Farrell, Bosiljka Tasic, Rusty Nicovich, Medea McGraw, Krissy Brouner, Andrew L. Ko, Katherine Wadhwani, Lauren Ellingwood, Tom Egdorf, Anton Arkhipov, Aaron Szafer, Michael Clark, Kirsten Crichton, Kyla Berry, Josef Sulc, Nick Dee, Gabe J. Murphy, Luke Esposito, Trangthanh Pham, Thomas Chartrand, Alex M. Henry, Rachel A. Dalley, Rachel Enstrom, Thomas Braun, Luke Campagnola, Cristina Radaelli, C. Dirk Keene, Tanya L. Daigle, Cliff Slaughterbeck, Sara Kebede, Rachael Larsen, Jeffrey G. Ojemann, Juia Andrade, Michelle Maxwell, Staci A. Sorensen, Jeff Goldy, Jessica Gloe, David Sandman, Shinya Ito, Susan M. Sunkin, Wayne Wakeman, Travis A. Hage, Melissa Gorham, Ryder P. Gwinn, Pasha A. Davoudian, Augustin Ruiz, Grace Williams, Clare Gamlin, Christof Koch, La'Akea Siverts, Stephanie C. Seeman, Jasmine Bomben, Florence D’Orazi, Madie Hupp, Ed S. Lein, Nadia Dotson, Shea Ransford, Nika Hejazinia, Mean Hwan Kim, Delissa McMillen, David Feng, Jessica Trinh, Lydia Potekhina, Alice Mukora, Lauren Alfiler, Tamara Casper, Shu Shi, Matthew Kroll, Kiet Ngo, Richard G. Ellenbogen, Daniel L. Silbergeld, and Miranda Walker

Subjects
Synapse, Cell type, Neocortex, medicine.anatomical_structure, Excitatory synapse, Cortex (anatomy), medicine, Excitatory postsynaptic potential, Biology, Inhibitory postsynaptic potential, Neuroscience, Subclass
Abstract

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.

Published
2021

8. Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells

Author

Kris Bickley, Anton Arkhipov, Osnat Penn, Hanchuan Peng, Shea Ransford, Sara Kebede, Kara Ronellenfitch, Matthew Mallory, Krissy Brouner, Madie Hupp, Lydia Ng, Daniel Park, Staci A. Sorensen, Alice Pom, Susan M. Sunkin, Tanya L. Daigle, Fahimeh Baftizadeh, Wayne Wakeman, Aaron Oldre, Amanda Gary, Herman Tung, Brian Lee, Ed S. Lein, Medea McGraw, Rachel A. Dalley, Bosiljka Tasic, Hong Gu, Miranda Robertson, Katherine Baker, Lindsay Ng, David Sandman, Jasmine Bomben, Uygar Sümbül, Tae Kyung Kim, David Reid, Eliza Barkan, Luke Esposito, Kirsten Crichton, DiJon Hill, Zoran Popović, Josef Sulc, Nathan W. Gouwens, Ramkumar Rajanbabu, Lydia Potekhina, Thomas Braun, Alexandra Glandon, Tim Jarsky, Darren Bertagnolli, Tom Egdorf, Olivia Fong, Alice Mukora, Rebecca de Frates, Lauren Ellingwood, Jonathan T. Ting, Gabe J. Murphy, Katelyn Ward, Delissa McMillen, Samuel Dingman Lee, Melissa Gorham, Michelle Maxwell, Clare Gamlin, Zhi Zhou, Jeff Goldy, Rachel Enstrom, Kyla Berry, Colin Farrell, Katherine E. Link, Christine Rimorin, Zizhen Yao, Hongkui Zeng, Kristen Hadley, Augustin Ruiz, Grace Williams, Amy Torkelson, Kimberly A. Smith, Lisa Kim, Aaron Szafer, Nick Dee, Alex M. Henry, Rohan Gala, David Feng, Jessica Trinh, Tamara Casper, Matthew Kroll, Christof Koch, Michael Tieu, Michael Hawrylycz, Lauren Alfiler, Kiet Ngo, Philip R. Nicovich, Thanh Pham, Nadezhda Dotson, Rusty Mann, Tsega Desta, Lucas T. Graybuck, Changkyu Lee, Jim Berg, and Agata Budzillo

Subjects
0303 health sciences, Cell type, biology, Interneuron, General Biochemistry, Genetics and Molecular Biology, Transcriptome, 03 medical and health sciences, Electrophysiology, 0302 clinical medicine, medicine.anatomical_structure, Visual cortex, medicine, biology.protein, GABAergic, Axon, Neuroscience, 030217 neurology & neurosurgery, Parvalbumin, 030304 developmental biology
Abstract

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.

Published
2020

9. Conserved cell types with divergent features between human and mouse cortex

Author

Jeff Goldy, Sheana Parry, Jeremy A. Miller, Brian Long, Susan M. Sunkin, Saroja Somasundaram, Rebecca D. Hodge, Hongkui Zeng, Aaron Oldre, Kimberly A. Smith, Zoe Maltzer, Brian D. Aevermann, Mohamed Keshk, Jeroen Eggermont, Ed Lein, Daniel Hirschstein, Darren Bertagnolli, Jennie L. Close, Osnat Penn, John W. Phillips, Rachel A. Dalley, Allan R. Jones, Ahmed Mahfouz, Olivia Fong, Allison Beller, Soraya I. Shehata, Thuc Nghi Nguyen, Jeffrey G. Ojemann, Shannon Reynolds, Eliza Barkan, Michael Tieu, Christof Koch, Michael Hawrylycz, Songlin Ding, Richard H. Scheuermann, Ryder P. Gwinn, Elliot R. Thomsen, Medea McGraw, Emma Garren, Christine Rimorin, Lydia Ng, Boudewijn P. F. Lelieveldt, C. Dirk Keene, Amy Bernard, Richard G. Ellenbogen, Rafael Yuste, David Feng, Boaz P. Levi, Trygve E. Bakken, Tamara Casper, Bosiljka Tasic, Aaron Szafer, Nick Dee, Nadiya V. Shapovalova, Kanan Lathia, Lucas T. Graybuck, Charles Cobbs, Julie Nyhus, Thomas Höllt, Zizhen Yao, Krissy Brouner, and Andrew L. Ko

Subjects
0303 health sciences, Cell type, Neocortex, Cellular architecture, Middle temporal gyrus, Cell, Human brain, Biology, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Cerebral cortex, medicine, Neuroscience, Nucleus, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

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.

Published
2018

10. Author response: Neuropathological and transcriptomic characteristics of the aged brain

Author

Lydia Ng, Shubhabrata Mukherjee, Amy Bernard, Mindy L Chua, Jeff Goldy, Fiona Griffin, Darren Bertagnolli, Shu Shi, Ed S. Lein, Susan M. Sunkin, Nika Hejazinia, Justin Johal, Krissy Brouner, Jeremy A. Miller, Steve Horvath, Zeb Haradon, Natalie M Coleman, Jose Melchor, Desiree A. Marshall, Samuel R Josephsen, Paul K. Crane, Kristopher Bickley, Tim A. Dolbeare, Kim Howard, Michael S. Fisher, C. Dirk Keene, Angela M. Wilson, Tracy Lemon, Aaron Szafer, Eiron Cudaback, Nick Dee, Eric B. Larson, Elizabeth Rha, Chris Barber, Julie Nyhus, Michael Tieu, Lydia Potekhina, Caroline Habel, Nathalie Gaudreault, Kimberly A. Smith, Shannon E. Rose, Nikolas L. Jorstad, Angela L. Guillozet-Bongaarts, Terri L. Gilbert, Felix Lee, Nivretta Thatra, Florence Lai, Julie Pendergraft, Elaine Shen, Eric Lee, Christine Cuhaciyan, Chihchau L. Kuan, Mike Chapin, Richard G. Ellenbogen, Andy J. Sodt, Leanne L Hellstern, Shiella Caldejon, Nadia Postupna, David Rosen, Emily Sherfield, Tsega Desta, Anne Renz, Xianwu Li, Abharika Sapru, Robert Howard, Rachel A. Dalley, Aimee Schantz, Allison Beller, Samantha Rice, Nadezhda Dotson, Laura E. Gibbons, Garrett Gee, and Thomas J. Montine

Subjects
0301 basic medicine, Transcriptome, 03 medical and health sciences, 030104 developmental biology, business.industry, Medicine, business, Neuroscience
Published
2017

11. A comprehensive transcriptional map of primate brain development

Author

Songlin Ding, R.D. Young, Paul Wohnoutka, Anna Hoerder-Suabedissen, Brian L. Youngstrom, Rachel A. Dalley, Terri L. Gilbert, Stephanie Butler, Lydia Potekhina, Jody Parente, Shiella Caldejon, Shu Shi, Kimberly A. Smith, Lon T. Luong, Chinh Dang, Aaron Oldre, Shelby Cate, Emi J. Byrnes, Susan M. Sunkin, Joshua J. Royall, Jefferey Chen, Amanda Ebbert, Jeffrey Rogers, Zeb Haradon, Lindsey Gourley, Ryan May, Naveed Mastan, Aaron Szafer, Chihchau L. Kuan, Kristopher Bickley, Tracy Lemon, Nick Dee, Nerick Mosqueda, Ed S. Lein, David Rosen, Mike Chapin, John W. Phillips, Guangyu Gu, Crissa Bennett, Nadia Dotson, Kate Roll, Ali Kriedberg, Nika Hejazinia, Nadiya V. Shapovalova, Brandon Rogers, Jon Hall, David G. Amaral, Robert Howard, Melaine Sarreal, Sheana Parry, Kaylynn Aiona, Tim A. Dolbeare, Michael Hawrylycz, Allan R. Jones, Robert F. Hevner, Nathan Sjoquist, Tyson Roberts, Marty Kinnunen, Lissette Velasquez, Jay Jochim, Richard A. Gibbs, Anita Carey, Tsega Desta, Jennifer Wu, Kiet Ngo, Julie Nyhus, Julie Pendergraft, Ben W. Gregor, Sheila Shapouri, Amy Bernard, Lydia Ng, Darren Bertagnolli, Eric Olson, Jeff Goldy, Udi Wagley, Changkyu Lee, Christopher Lau, David R. Haynor, Krissy Brouner, Erika Mott, Jeremy A. Miller, Andy J. Sodt, Jeffrey L. Bennett, Jose Melchor, Patrick D. Parker, Cassandra White, Zoltán Molnár, Andrew F. Boe, Zackery L. Riley, Trygve E. Bakken, David Sandman, Garrett Gee, James M. Arnold, Erich Fulfs, Robbie Townsend, Wayne Wakeman, John G. Hohmann, Felix Lee, and Melissa Reding

Subjects
0301 basic medicine, Male, Microcephaly, Aging, Transcription, Genetic, Autism Spectrum Disorder, Neocortex, Molecular neuroscience, Transcriptome, 0302 clinical medicine, Risk Factors, 2.1 Biological and endogenous factors, Primate, Conserved Sequence, Pediatric, Multidisciplinary, biology, Neurogenesis, Brain, Mental Health, medicine.anatomical_structure, Autism spectrum disorder, Neurological, Stem Cell Research - Nonembryonic - Non-Human, Female, Transcription, Biotechnology, General Science & Technology, Intellectual and Developmental Disabilities (IDD), 1.1 Normal biological development and functioning, Article, 03 medical and health sciences, Spatio-Temporal Analysis, Species Specificity, Genetic, biology.animal, Intellectual Disability, Genetics, medicine, Cell Adhesion, Animals, Humans, Cell projection, Human Genome, Neurosciences, Stem Cell Research, medicine.disease, Macaca mulatta, Brain Disorders, 030104 developmental biology, Neurodevelopmental Disorders, Schizophrenia, Neuroscience, 030217 neurology & neurosurgery
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.

Published
2016

12. An anatomic transcriptional atlas of human glioblastoma

Author

Greg Foltz, Parvinder Hothi, Ali Kriedberg, Krissy Brouner, David Feng, Chantal Murthy, Robert Howard, Robert C. Rostomily, David Sandman, Eric Olson, Nadezhda Dotson, Nameeta Shah, Guangyu Gu, Kris Bickley, Lydia Ng, Nika Hejazinia, John W. Phillips, Leonard Kuan, Charles Cobbs, Garrett Gee, Tim A. Dolbeare, Tsega Desta, Shiella Caldejon, Kiet Ngo, Haley Gittleman, Andrew F. Boe, Hwahyung Lee, Rachel A. Dalley, Steven J. White, Chris Lau, Bart Keogh, Graham Stockdale, Lindsey Gourley, Fuhui Long, Darren Bertagnolli, Andrew Sodt, Michael Hawrylycz, Amanda Ebbert, Jill S. Barnholtz-Sloan, David Rosen, Michael S. Fisher, Antonio Iavarone, Ed S. Lein, Stephanie Butler, Patrick J. Cimino, Tracy Lemon, Zack Riley, Allan R. Jones, Megha S Uppin, Mike Chapin, Naveed Mastan, Kimberly A. Smith, Michael E. Berens, Clifford R. Slaughterbeck, Aaron Szafer, Nick Dee, Wayne Wakeman, John G. Hohmann, Benjamin W. Gregor, Suvro Datta, Felix Lee, Ralph B. Puchalski, Melissa Reding, Nadiya V. Shapovalova, Xu Feng, Amy Bernard, Jae Guen Yoon, Erika Mott, Jeremy A. Miller, Justin D. Lathia, Steve R. Nomura, Steven Rostad, Kevin M. Joines, Paul Wohnoutka, Jeff Goldy, Don Marsh, Farrokh Farrokhi, Michael Lankerovich, C. Dirk Keene, and Chinh Dang

Subjects
0301 basic medicine, Poor prognosis, Multidisciplinary, Extramural, Brain Neoplasms, Gene Expression Profiling, Brain tumor, Computational biology, Biology, medicine.disease, Prognosis, Genomic databases, Data resources, Article, nervous system diseases, Gene expression profiling, 03 medical and health sciences, 030104 developmental biology, Atlases as Topic, Databases, Genetic, medicine, Humans, Glioblastoma, neoplasms
Abstract

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

Published
2016

13. Transcriptional landscape of the prenatal human brain

Author

Amy Bernard, Phil Lesnar, Daniel H. Geschwind, Sheana Parry, Ed S. Lein, Benjamin W. Gregor, Theresa Naluai-Cecchini, John W. Phillips, Elaine H. Shen, Julie Nyhus, Chinh Dang, Rachel A. Dalley, Susan M. Sunkin, Nerick Mosqueda, Mark Gerstein, Lydia Ng, Hao Huang, Guangyu Gu, Lindsey Gourley, Tim A. Dolbeare, Darren Bertagnolli, Ian A. Glass, Bergen McMurray, Melaine Sarreal, Allison Stevens, Tim P. Fliss, Crissa Bennet, Clifford R. Slaughterbeck, Aaron Szafer, Mihovil Pletikos, Nenad Sestan, Benjamin A.C. Facer, Nick Dee, David Feng, Jody Parente, Paul Wohnoutka, Andy J. Sodt, Robert Howard, Christopher Lau, Tracy Lemon, Aaron Oldre, Robert F. Hevner, Nathan Sjoquist, Michael Hawrylycz, Nadiya V. Shapovalova, Joshua J. Royall, Pat Levitt, Zackery L. Riley, Anita Carey, John G. Hohmann, Kaylynn Aiona, Bruce Fischl, James A. Knowles, Felix Lee, Lilla Zöllei, Sheila Shapouri, Eric Olson, Melissa Reding, Christine Cuhaciyan, Shiella Caldejon, Songlin Ding, Derric Williams, Chihchau L. Kuan, Jayson M. Jochim, Michael W. Smith, Krissy Brouner, Allan R. Jones, Patrick D. Parker, Garrett Gee, Kate Roll, David Sandman, Stephanie Butler, James M. Arnold, Kimberly A. Smith, Jeremy A. Miller, Jeff Goldy, Nhan Kiet Ngo, Amanda Ebbert, Changkyu Lee, and Naveed Mastan

Subjects
Evolution, General Science & Technology, 1.1 Normal biological development and functioning, Neocortex, Biology, Human brain, Microarray, Development, Article, Transcriptome, Mice, Fetus, Atlases as Topic, Species Specificity, Stem Cell Research - Nonembryonic - Human, Underpinning research, Subplate, medicine, Genetics, Animals, Humans, Artistic, Developmental, Gene Regulatory Networks, Anatomy, Artistic, Conserved Sequence, Regulation of gene expression, Pediatric, Multidisciplinary, Microarray analysis techniques, Neurosciences, Gene Expression Regulation, Developmental, Brain, Stem Cell Research, Human Fetal Tissue, medicine.anatomical_structure, Frontal lobe, Gene Expression Regulation, Cerebral cortex, Neurological, Gene expression, Anatomy, Neuroscience, Biotechnology
Abstract

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.

Published
2014

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