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Dive into the research topics where Lydia Ng is active.

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Featured researches published by Lydia Ng.


Nature Neuroscience | 2010

A robust and high-throughput Cre reporting and characterization system for the whole mouse brain

Linda Madisen; Theresa A. Zwingman; Susan M. Sunkin; Seung Wook Oh; Hatim A. Zariwala; Hong Gu; Lydia Ng; Richard D. Palmiter; Michael Hawrylycz; Allan R. Jones; Ed Lein; Hongkui Zeng

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.


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

A mesoscale connectome of the mouse brain

Seung Wook Oh; Julie A. Harris; Lydia Ng; Brent Winslow; Nicholas Cain; Stefan Mihalas; Quanxin Wang; Chris Lau; Leonard Kuan; Alex Henry; Marty T. Mortrud; Benjamin Ouellette; Thuc Nghi Nguyen; Staci A. Sorensen; Clifford R. Slaughterbeck; Wayne Wakeman; Yang Li; David Feng; Anh Ho; Eric Nicholas; Karla E. Hirokawa; Phillip Bohn; Kevin M. Joines; Hanchuan Peng; Michael Hawrylycz; John Phillips; John G. Hohmann; Paul Wohnoutka; Charles R. Gerfen; Christof Koch

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.


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.


Neuron | 2008

Genomic Anatomy of the Hippocampus

Carol L. Thompson; Sayan D. Pathak; Andreas Jeromin; Lydia Ng; Cameron Ross MacPherson; Marty T. Mortrud; Allison Cusick; Zackery L. Riley; Susan M. Sunkin; Amy Bernard; Ralph B. Puchalski; Fred H. Gage; Allan R. Jones; Vladimir B. Bajic; Michael Hawrylycz; Ed Lein

Availability of genome-scale in situ hybridization data allows systematic analysis of genetic neuroanatomical architecture. Within the hippocampus, electrophysiology and lesion and imaging studies demonstrate functional heterogeneity along the septotemporal axis, although precise underlying circuitry and molecular substrates remain uncharacterized. Application of unbiased statistical component analyses to genome-scale hippocampal gene expression data revealed robust septotemporal molecular heterogeneity, leading to the identification of a large cohort of genes with robust regionalized hippocampal expression. Manual mapping of heterogeneous CA3 pyramidal neuron expression patterns demonstrates an unexpectedly complex molecular parcellation into a relatively coherent set of nine expression domains in the septal/temporal and proximal/distal axes with reciprocal, nonoverlapping boundaries. Unique combinatorial profiles of adhesion molecules within these domains suggest corresponding differential connectivity, which is demonstrated for CA3 projections to the lateral septum using retrograde labeling. This complex, discrete molecular architecture provides a novel paradigm for predicting functional differentiation across the full septotemporal extent of the hippocampus.


Nucleic Acids Research | 2012

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

Susan M. Sunkin; Lydia Ng; Christopher Lau; Tim Dolbeare; Terri L. Gilbert; Carol L. Thompson; Michael Hawrylycz; Chinh Dang

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal.


Nature Neuroscience | 2009

An anatomic gene expression atlas of the adult mouse brain

Lydia Ng; Amy Bernard; Chris Lau; Caroline C. Overly; Hong-Wei Dong; Chihchau Kuan; Sayan D. Pathak; Susan M. Sunkin; Chinh Dang; Jason W. Bohland; Hemant Bokil; Partha P. Mitra; Luis Puelles; John G. Hohmann; David J. Anderson; Ed Lein; Allan R. Jones; Michael Hawrylycz

Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of genes in the Allen Brain Atlas (ABA). The AGEA includes three discovery tools for examining neuroanatomical relationships and boundaries: (1) three-dimensional expression-based correlation maps, (2) a hierarchical transcriptome-based parcellation of the brain and (3) a facility to retrieve from the ABA specific genes showing enriched expression in local correlated domains. The utility of this atlas is illustrated by analysis of genetic organization in the thalamus, striatum and cerebral cortex. The AGEA is a publicly accessible online computational tool integrated with the ABA (http://mouse.brain-map.org/agea).


Nature Neuroscience | 2015

Canonical genetic signatures of the adult human brain

Michael Hawrylycz; Jeremy A. Miller; Vilas Menon; David Feng; Tim Dolbeare; Angela L. Guillozet-Bongaarts; Anil G. Jegga; Bruce J. Aronow; Chang Kyu Lee; Amy Bernard; Matthew F. Glasser; Donna L. Dierker; Jörg Menche; Aaron Szafer; Forrest Collman; Pascal Grange; Kenneth A. Berman; Stefan Mihalas; Zizhen Yao; Lance Stewart; Albert-László Barabási; Jay Schulkin; John Phillips; Lydia Ng; Chinh Dang; David R. Haynor; Allan R. Jones; David C. Van Essen; Christof Koch; Ed Lein

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.


Frontiers in Neural Circuits | 2014

Anatomical characterization of Cre driver mice for neural circuit mapping and manipulation

Julie A. Harris; Karla E. Hirokawa; Staci A. Sorensen; Hong Gu; Maya Mills; Lydia Ng; Phillip Bohn; Marty T. Mortrud; Benjamin Ouellette; Jolene Kidney; Kimberly A. Smith; Chinh Dang; Susan M. Sunkin; Amy Bernard; Seung Wook Oh; Linda Madisen; Hongkui Zeng

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 (ISH), 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 Institutes 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.


IEEE/ACM Transactions on Computational Biology and Bioinformatics | 2007

Neuroinformatics for Genome-Wide 3-D Gene Expression Mapping in the Mouse Brain

Lydia Ng; Sayan D. Pathak; Chihchau Kuan; Christopher Lau; Hong-Wei Dong; Andrew Sodt; Chinh Dang; Brian B. Avants; Paul A. Yushkevich; James C. Gee; David R. Haynor; Ed Lein; Allan R. Jones; Michael Hawrylycz

Large scale gene expression studies in the mammalian brain offer the promise of understanding the topology, networks and ultimately the function of its complex anatomy, opening previously unexplored avenues in neuroscience. High-throughput methods permit genome-wide searches to discover genes that are uniquely expressed in brain circuits and regions that control behavior. Previous gene expression mapping studies in model organisms have employed situ hybridization (ISH), a technique that uses labeled nucleic acid probes to bind to specific mRNA transcripts in tissue sections. A key requirement for this effort is the development of fast and robust algorithms for anatomically mapping and quantifying gene expression for ISH. We describe a neuroinformatics pipeline for automatically mapping expression profiles of ISH data and its use to produce the first genomic scale 3-D mapping of gene expression in a mammalian brain. The pipeline is fully automated and adaptable to other organisms and tissues. Our automated study of over 20,000 genes indicates that at least 78.8% are expressed at some level in the adult C56BL/6J mouse brain. In addition to providing a platform for genomic scale search, high-resolution images and visualization tools for expression analysis are available at the Allen Brain Atlas web site (http://www.brain-map.org).

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Michael Hawrylycz

Allen Institute for Brain Science

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Susan M. Sunkin

Allen Institute for Brain Science

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Chinh Dang

Allen Institute for Brain Science

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Allan R. Jones

Allen Institute for Brain Science

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Sayan D. Pathak

Allen Institute for Brain Science

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Amy Bernard

Allen Institute for Brain Science

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David Feng

Allen Institute for Brain Science

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Ed Lein

Allen Institute for Brain Science

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Christopher Lau

Allen Institute for Brain Science

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Rachel A. Dalley

Allen Institute for Brain Science

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