Biology subjects

Tasic, B.

Publications and source records attributed to Tasic, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their "volume transmission" output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

neuroscience↗

bioRxiv2024

Data-driven fine-grained region discovery in the mouse brain with transformers

Spatial transcriptomics offers unique opportunities to define the spatial organization of tissues and organs, such as the mouse brain. We address a key bottleneck in the analysis of organ-scale spatial transcriptomic data by establishing a workflow for self-supervised spatial domain detection that is scalable to multimillion cell datasets. This workflow uses a self-supervised framework for learning latent representations of tissue spatial domains or niches. We use a novel encoder-decoder architecture, which we named CellTransformer, to hierarchically learn higher-order tissue features from lower-level cellular and molecular statistical patterns. Coupling our representation learning workflow with minibatched GPU-accelerated clustering algorithms allows us to scale to multi-million cell MERFISH datasets where other methods cannot. CellTransformer is effective at integrating cells across tissue sections, identifying domains highly similar to ones in existing ontologies such as Allen Mouse Brain Common Coordinate Framework (CCF) while allowing discovery of hundreds of uncataloged areas with minimal loss of domain spatial coherence. CellTransformer domains recapitulate previous neuroanatomical studies of areas in the subiculum and superior colliculus, and characterize putatively uncataloged subregions in subcortical areas which currently lack subregion annotation. CellTransformer is also capable of domain discovery in whole-brain Slide-seqV2 datasets. Our workflows enable complex multi-animal analyses, achieving nearly perfect consistency of up to 100 spatial domains in a dataset of four individual mice with nine million cells across more than 200 tissue sections. CellTransformer advances the state of the art for spatial transcriptomics, by providing a performant solution for detection of fine-grained tissue domains from spatial transcriptomics data.

bioinformatics↗

bioRxiv2023

Brain-wide topographic coordination of traveling spiral waves

Traveling waves of activity are a prevalent phenomenon within neural networks of diverse brain regions and species, and have been implicated in myriad brain functions including sensory perception, memory, spatial navigation, and motor control. However, their spatial organization, anatomical basis, and whether they are locally confined versus distributed across the brain, remains unclear. Here we used cortex-wide imaging and large-scale electrophysiology in awake mice to reveal the organization of traveling waves across spatial scales. Traveling waves formed spiral patterns predominantly centered on somatosensory cortex, sweeping across somatotopic maps. Strikingly, the local axonal architecture of neurons in sensory cortex exhibited a matching circular arrangement. At the cortex-wide scale, these spiral waves were mirrored between hemispheres and between sensory and motor cortex, reflecting topographic long-range axons. At the brain-wide scale, cortical spiral waves were coordinated with subcortical spiking patterns in the thalamus, striatum, and midbrain. These results establish that traveling waves are shaped by axonal pathways into coordinated spiral patterns that globally impact neural activity across diverse brain systems, revealing a distributed, multi-sensory organizational principle for propagating neural activity.

neuroscience↗

bioRxiv2023

epDevAtlas: Mapping GABAergic cells and microglia in postnatal mouse brains

During development, brain regions follow encoded growth trajectories. Compared to classical brain growth charts, high-definition growth charts could quantify regional volumetric growth and constituent cell types, improving our understanding of typical and pathological brain development. Here, we create high-resolution 3D atlases of the early postnatal mouse brain, using Allen CCFv3 anatomical labels, at postnatal days (P) 4, 6, 8, 10, 12, and 14, and determine the volumetric growth of different brain regions. We utilize 11 different cell type-specific transgenic animals to validate and refine anatomical labels. Moreover, we reveal region-specific density changes in {gamma}-aminobutyric acid-producing (GABAergic), cortical layer-specific cell types, and microglia as key players in shaping early postnatal brain development. We find contrasting changes in GABAergic neuronal densities between cortical and striatal areas, stabilizing at P12. Moreover, somatostatin-expressing cortical interneurons undergo regionally distinct density reductions, while vasoactive intestinal peptide-expressing interneurons show no significant changes. Remarkably, microglia transition from high density in white matter tracks to gray matter at P10, and show selective density increases in sensory processing areas that correlate with the emergence of individual sensory modalities. Lastly, we create an open-access web-visualization (https://kimlab.io/brain-map/epDevAtlas) for cell-type growth charts and developmental atlases for all postnatal time points.

neuroscience↗

bioRxiv2023

Topographical and cell type-specific connectivity of rostral and caudal forelimb corticospinal neuron populations

Corticospinal neurons (CSNs) synapse directly on spinal neurons, a diverse group of neurons with unique structural and functional properties necessary for body movements. CSNs modulating forelimb behavior fractionate into caudal forelimb area (CFA) and rostral forelimb area (RFA) motor cortical populations. Despite their prominence, no studies have mapped the diversity of spinal cell types targeted by CSNs, let alone compare CFA and RFA populations. Here we use anatomical and RNA-sequencing methods to show that CSNs synapse onto a remarkably selective group of spinal cell types, favoring inhibitory populations that regulate motoneuron activity and gate sensory feedback. CFA and RFA CSNs target similar spinal cell types, with notable exceptions that suggest these populations differ in how they influence behavior. Finally, axon collaterals of CFA and RFA CSNs target similar brain regions yet receive surprisingly divergent inputs. These results detail the rules of CSN connectivity throughout the brain and spinal cord for two regions critical for forelimb behavior.

neuroscience↗

bioRxiv2023

Cell-type specific molecular signatures of aging revealed in a brain-wide transcriptomic cell-type atlas

Biological aging can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function. Aging is a complex and dynamic process which influences distinct cell types in a myriad of ways. The cellular architecture of the mammalian brain is heterogeneous and diverse, making it challenging to identify precise areas and cell types of the brain that are more susceptible to aging than others. Here, we present a high-resolution single-cell RNA sequencing dataset containing [~]1.2 million high-quality single-cell transcriptomic profiles of brain cells from young adult and aged mice across both sexes, including areas spanning the forebrain, midbrain, and hindbrain. We find age-associated gene expression signatures across nearly all 130+ neuronal and non-neuronal cell subclasses we identified. We detect the greatest gene expression changes in non-neuronal cell types, suggesting that different cell types in the brain vary in their susceptibility to aging. We identify specific, age-enriched clusters within specific glial, vascular, and immune cell types from both cortical and subcortical regions of the brain, and specific gene expression changes associated with cell senescence, inflammation, decrease in new myelination, and decreased vasculature integrity. We also identify genes with expression changes across multiple cell subclasses, pointing to certain mechanisms of aging that may occur across wide regions or broad cell types of the brain. Finally, we discover the greatest gene expression changes in cell types localized to the third ventricle of the hypothalamus, including tanycytes, ependymal cells, and Tbx3+ neurons found in the arcuate nucleus that are part of the neuronal circuits regulating food intake and energy homeostasis. These findings suggest that the area surrounding the third ventricle in the hypothalamus may be a hub for aging in the mouse brain. Overall, we reveal a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal aging that will serve as a foundation for the investigation of functional changes in the aging process and the interaction of aging and diseases.

neuroscience↗

bioRxiv2023

Brain-wide Correspondence Between Neuronal Epigenomics and Long-Distance Projections

Single-cell genetic and epigenetic analyses parse the brains billions of neurons into thousands of "cell-type" clusters, each residing in different brain structures. Many of these cell types mediate their unique functions by virtue of targeted long-distance axonal projections to allow interactions between specific cell types. Here we have used Epi-Retro-Seq to link single cell epigenomes and associated cell types to their long-distance projections for 33,034 neurons dissected from 32 different source regions projecting to 24 different targets (225 source [->]target combinations) across the whole mouse brain. We highlight uses of this large data set for interrogating both overarching principles relating projection cell types to their transcriptomic and epigenomic properties and for addressing and developing specific hypotheses about cell types and connections as they relate to genetics. We provide an overall synthesis of the data set with 926 statistical comparisons of the discriminability of neurons projecting to each target for every dissected source region. We integrate this dataset into the larger, annotated BICCN cell type atlas composed of millions of neurons to link projection cell types to consensus clusters. Integration with spatial transcriptomic data further assigns projection-enriched clusters to much smaller source regions than afforded by the original dissections. We exemplify these capabilities by presenting in-depth analyses of neurons with identified projections from the hypothalamus, thalamus, hindbrain, amygdala, and midbrain to provide new insights into the properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription factor binding motifs, and neurotransmitter usage.

neuroscience↗

bioRxiv2023

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brains 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brains cellular-spatial and regulatory genome diversity.

genomics↗

bioRxiv2023

Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing

Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4,130 retrogradely labeled cells and 2,914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.

neuroscience↗

bioRxiv2023

Unsupervised pattern discovery in spatial gene expression atlas reveals mouse brain regions beyond established ontology

The rapid growth of large-scale spatial gene expression data demands efficient and reliable computational tools to extract major trends of gene expression in their native spatial context. Here, we used stability-driven unsupervised learning (i.e. staNMF) to identify principal patterns (PPs) of 3D gene expression profiles and understand spatial gene distribution and anatomical localization at the whole mouse brain level. Our subsequent spatial correlation analysis systematically compared the PPs to known anatomical regions and ontology from the Allen Mouse Brain Atlas using spatial neighborhoods. We demonstrate that our stable and spatially coherent PPs, whose linear combinations accurately approximate the spatial gene data, are highly correlated with combinations of expert-annotated brain regions. These PPs yield a new brain ontology based purely on spatial gene expression. Our PP identification approach outperforms principal component analysis (PCA) and typical clustering algorithms on the same task. Moreover, we show that the stable PPs reveal marked regional imbalance of brainwide genetic architecture, leading to region-specific marker genes and gene co-expression networks. Our findings highlight the advantages of stability-driven machine learning for plausible biological discovery from dense spatial gene expression data that are infeasible by conventional manual approaches.

neuroscience↗

bioRxiv2023

A molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in [~]8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to [~]300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.

neuroscience↗

bioRxiv2021

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes

Integrating single-cell transcriptomes and epigenomes across diverse cell types can link genes with the cis-regulatory elements (CREs) that control expression. Gene co-expression across cell types confounds simple correlation-based analysis and results in high false prediction rates. We developed a procedure that controls for co-expression between genes and integrates multiple molecular modalities, and used it to identify >10,000 gene-CRE pairs that contribute to gene expression programs in different cell types in the mouse brain.

bioinformatics↗

bioRxiv2021

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

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.

neuroscience↗

bioRxiv2021

Motion/direction-sensitive thalamic neurons project extensively to the middle layers of primary visual cortex

The motion/direction-sensitive and location-sensitive neurons are two major functional types in mouse visual thalamus that project to the primary visual cortex (V1). It has been proposed that the motion/direction-sensitive neurons mainly target the superficial layers in V1, in contrast to the location-sensitive neurons which mainly target the middle layers. Here, by imaging calcium activities of motion/direction-sensitive and location-sensitive axons in V1, we find no evidence for these cell-type specific laminar biases at population level. Furthermore, using a novel approach to reconstruct single-axon structures with identified in vivo response types, we show that, at single-axon level, the motion/direction-sensitive axons have middle layer preferences and project more densely to the middle layers than the location-sensitive axons. Overall, our results demonstrate that Motion/direction-sensitive thalamic neurons project extensively to the middle layers of V1, challenging the current view of the thalamocortical organizations in the mouse visual system.

neuroscience↗

bioRxiv2021

Dense Functional and Molecular Readout of a Circuit Hub in Sensory Cortex

Information processing in the neocortex is carried out by neuronal circuits composed of different cell types. Recent census of the neocortex using single cell transcriptomic profiling has uncovered more than 100 putative cell types which subdivide major classes of excitatory and inhibitory neurons into distinct subclasses. The extent to which this molecular classification predicts distinct functional roles during behavior is unclear. Here, we combined population recordings using two-photon calcium imaging with spatial transcriptomics using multiplexed fluorescent in situ hybridization to achieve dense functional and molecular readout of cortical circuits during behavior. We characterized task-related responses across major transcriptomic neuronal subclasses and types in layer 2/3 of primary somatosensory cortex as mice performed a tactile working memory task. We find that as neurons are segregated into increasingly discrete molecular types, their task-related properties continue to differentiate. We identify an excitatory cell type, Baz1a, that is highly driven by tactile stimuli. Baz1a neurons homeostatically maintain stimulus responsiveness during altered sensory experience and show persistent enrichment of subsets of immediately early genes including Fos. Measurements of functional and anatomical connectivity reveal that upper layer 2/3 Baz1a neurons preferentially innervate somatostatin-expressing inhibitory neurons. We propose that this connection motif reflects a sensory-driven circuit hub that orchestrates local sensory processing in superficial layers of the neocortex.

neuroscience↗

bioRxiv2020

Single-cell RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates and humans

Abundant anatomical and physiological evidence supports the presence of at least three distinct types of relay glutamatergic neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex. Relay neuron diversity has also been described in the mouse dLGN (also known as LGd). Different types of relay neurons in mice, humans and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to other cellular properties and differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of relay neurons in the primate dLGN, magnocellular neurons, parvocellular neurons, and two cell types expressing canonical marker genes for koniocellular neurons. Surprisingly, despite extensive documented morphological and physiological differences between magno- and parvocellular neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. We also detected strong donor-specific gene expression signatures in both macaque and human relay neurons. Likewise, the dominant feature of relay neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to striking differences in morphology and cortical projection targets. Finally, we align cellular expression profiles across species and find homologous types of relay neurons in macaque and human, and distinct relay neurons in mouse.

neuroscience↗

bioRxiv2020

High fidelity electrophysiological, morphological, and transcriptomic cell characterization using a refined Patch-seq protocol

The Patch-seq approach is a powerful variation of the standard patch clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at a scale and quality that can be integrated with high-throughput dissociated cell transcriptomic data, we have optimized the technique by identifying and refining key factors that contribute to the efficient collection of high-quality data. To rapidly generate high-quality electrophysiology data, we developed patch clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized a substantial improvement in transcriptomic data quality when the nucleus was extracted following the recording. For morphology success, the importance of maximizing the neurons membrane integrity during the extraction of the nucleus was much more critical to success than varying the duration of the electrophysiology recording. We compiled the lab protocol with the analysis and acquisition software at https://github.com/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate Patch-seq data across diverse mammalian species and that is compatible with recent large-scale publicly available Allen Institute Patch-seq datasets.

neuroscience↗

bioRxiv2020

Signature morpho-electric, transcriptomic, and dendritic properties of extratelencephalic-projecting human layer 5 neocortical pyramidal neurons

In the neocortex, subcerebral axonal projections originate largely from layer 5 (L5) extratelencephalic-projecting (ET) neurons. The highly distinctive morpho-electric properties of these neurons have mainly been described in rodents, where ET neurons can be labeled by retrograde tracers or transgenic lines. Similar labeling strategies are not possible in the human neocortex, rendering the translational relevance of findings in rodents unclear. We leveraged the recent discovery of a transcriptomically-defined L5 ET neuron type to study the properties of human L5 ET neurons in neocortical brain slices derived from neurosurgeries. Patch-seq recordings, where transcriptome, physiology and morphology are assayed from the same cell, revealed many conserved morpho-electric properties of human and rodent L5 ET neurons. Divergent properties were also apparent but were often smaller than differences between cell types within these two species. These data suggest a conserved function of L5 ET neurons in the neocortical hierarchy, but also highlight marked phenotypic divergence possibly related to functional specialization of human neocortex.

neuroscience↗