Biology subjects

Kebschull, J. M.

Publications and source records attributed to Kebschull, J. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Robust and accessible in situ sequencing with an open-source automated sequencer

Targeted in situ sequencing underlies many spatial transcriptomic, barcoded connectomic, and multiplexed perturbation techniques. Each experiment requires many cycles of chemical reactions and imaging that are time-consuming and error-prone to perform manually, and few commercial platforms can sequence highly diverse RNA barcodes in situ at cellular resolution across large tissue sections. Here we present Seq-o-Matic, an open-source automated in situ sequencer built entirely from commercially available components, which integrates fluidics, heated incubation, and imaging of up to three continuous 18 mm x 50 mm areas on standard microscope slides. Relative to manual sequencing, Seq-o-Matic reduced hands-on time 6- to 17.5-fold and total run time about 2.6-fold. Across three runs spanning two mouse strains and a neonatal marmoset, sequencing quality, measured by signal retention, channel specificity, and phasing, was similar to that of four manually sequenced mouse brains. In four mouse hemispheres sequenced in separate runs (two C57BL/6J, one NOD, and one WSB), consensus cell types were present in every brain and corresponded to those of a manually sequenced C57BL/6J brain. Within cortical excitatory neurons, the two C57BL/6J brains were more similar to each other than were brains of different strains, suggesting that technical variation between runs was small relative to strain differences. Seq-o-Matic thus makes consistent, high-throughput in situ sequencing accessible to laboratories without specialized in situ sequencing expertise.

genomics↗

bioRxiv2026

Evolution of new cerebellar nuclei by excitatory progenitor diversification in the early rhombic lip

The cerebellar nuclei, the output regions of the cerebellum, have evolved via repeated duplication of a conserved cell type set to produce different numbers of nuclei across species. Here, we investigate the mechanism underlying this process using developmental single-cell and spatial transcriptomics time courses in mouse and chicken. We show that new nuclei formation is governed by excitatory neurons born from nucleus-specific progenitors in the early and late rhombic lip (RL), with inhibitory neurons incorporating into established nuclear territories. Evolutionarily newer canonical cerebellar nuclei with increasingly higher-order functions are produced by diversification of the early RL, where nuclear identity and spatial organization are established in part by co-option of border formation programs in conserved progenitor cell types. In contrast, the late RL generates the higher-order subnuclei of the medial nucleus and forms a non-canonical olivocerebellar circuit. Together, our findings suggest that new brain regions can evolve through developmental diversification of excitatory progenitors and spatial segregation of conserved sister cell types with generic inhibitory neurons filling in after.

neuroscience↗

bioRxiv2026

Conserved and specialized features of thalamocortical wiring revealed by single-cell projection mapping in mouse and marmoset

Across mammals, brain regions can duplicate, expand, and diversify, requiring long-range connectivity to accommodate species-specific specializations while preserving globally ordered wiring. This challenge is especially pronounced in primate thalamocortical circuits, where select cortical fields and their thalamic partners have expanded disproportionately. Although gene expression in the thalamus follows broad and conserved gradients, how thalamocortical projections are organized at single-neuron resolution, and how this organization is reshaped by expansion, remain unknown. Here, we investigate thalamocortical projection organization by in situ sequencing and BARseq projection mapping in marmosets and mice. We profiled the gene expression of 1.5 million marmoset neurons and jointly measured gene expression and cortical projections in 708 marmoset and 1,518 mouse neurons that spanned multiple thalamic nuclei. In both species, projections of individual neurons targeted diverse areas that together spanned a large fraction of the cortex. Comparing projections at the single-neuron level and local neighborhood level revealed that marmoset thalamocortical projections were more spatially segregated, producing a point-to-point architecture. Strikingly, this local specialization coexisted with a conserved gradient that predominated over discrete anatomical borders: In the higher-order sensory thalamus of both species, gene expression and projections varied continuously across nucleus borders, and borders had only a small effect on projections. Furthermore, in both marmoset and mouse, gene expression gradients were associated with the anteroposterior locations of cortical targets. These results reconcile discrete nucleus and gradient-based models of thalamic organization and suggest that primate circuit specialization is superimposed on a conserved molecular-projection gradient.

neuroscience↗

bioRxiv2026

Generation and validation of an Acan-Cre mouse line to selectively label Class-B excitatory neurons of the cerebellar nuclei

The cerebellar nuclei form the main output structures of the cerebellum and are composed of a deeply conserved set of cell types. Two excitatory cell classes, Class-A and -B, are present in each cerebellar nucleus and mediate all excitatory output of the cerebellum. To provide genetic access to these cell types, here we identified Acan as a marker gene for Class-B cells and generated a knock-in Acan-P2A-Cre mouse line. We demonstrate that this Acan-Cre line selectively labels Class-B neurons in the cerebellar nuclei and validate its use in viral projection tracing. This new mouse line provides a valuable genetic tool to study cerebellar nuclei organization and function.

neuroscience↗

bioRxiv2026

BARseq3: a modular system for integrating spatial multi-omics and cellular barcoding in single cells

Understanding cellular identity requires multimodal measurements in single cells. Cellular barcoding provides powerful tools for recording the properties or history of individual cells in nucleic acids, while spatial omics techniques enable the measurement of a growing list of molecular features at micron resolution in tissue. However, existing methods that integrate these approaches in single samples are limited in the modalities they support, their flexibility, and efficiency. Here, we present BARseq3, a modular system that combines cellular barcoding with high-efficiency spatial transcriptomics and translatomics at subcellular resolution in tissue. BARseq3 is compatible with fixed samples, immunostaining, diverse species, and can be easily extended to include other spatial assays, enabling a multimodal understanding of cellular identity.

genomics↗

bioRxiv2025

DART: A GUI Pipeline for Aligning Histological Brain Sections to 3D Atlases and Automating Laser Microdissection

The precise dissection of anatomically defined brain regions is the basis of many workflows in neurobiology. Traditionally, brain regions of interest are defined by visual inspection of tissue sections, followed by manual dissection. Recently, laser capture microscopes have been employed for more accurate dissection, but region identification is still challenging. This paper presents an open-source software pipeline DART (Dissecting Atlas-Registered Tissue) that aligns histological brain sections to three-dimensional reference atlases and exports the resulting region-of-interest (ROI) contours for dissection by Leica Laser Microdissection (LMD) instruments. By integrating well-established image-processing libraries with a user-friendly graphical user interface, the software automates the traditionally time-consuming workflow of defining the boundaries of brain regions for dissection. With this pipeline, researchers can streamline tissue sampling for molecular analyses, while ensuring reproducibility and precision in ROI selection.

bioengineering↗

bioRxiv2025

Mapping the projectional architecture of the mouse midbrain dopaminergic system using cell type-specific barcoding

Brain-wide neural circuits are formed by the diverse axonal branching patterns of neurons of different cell types. Here we introduce POINTseq (projections of interest by sequencing), a cell type-specific barcoded connectomics method that uses selective barcoding and sequencing to rapidly map single-cell projections of a cell type of interest for thousands of neurons per animal. POINTseq leverages pseudotyping of Sindbis virus and a specific alphavirus-cellular receptor pair to make Sindbis infections cell type specific. It thus integrates MAPseq-style high-throughput barcoded projection mapping with the established viral-genetic neural circuit analysis toolbox. We validated POINTseq by mapping genetically and projection-defined cell populations in the mouse motor cortex. We then applied POINTseq to midbrain dopaminergic neurons and reconstructed the brain-wide single-cell projections of 5,902 dopaminergic neurons in ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). These neurons cluster into over 25 connectomic cell types, vastly exceeding the known diversity of dopaminergic cells, and form stereotyped projection motifs that may mediate parallel dopamine signaling. This data constitutes the anatomical substrate on which the diverse functions of dopamine in the brain are built. HIGHLIGHTSO_LIWe develop POINTseq, which uses pseudotyped Sindbis virus and cell type-specific expression of a viral receptor for cell type-specific barcoding. C_LIO_LIPOINTseq enables massively multiplexed single-cell projection mapping of cell types of interest. C_LIO_LIWe map the brain-wide projections of 5,902 individual VTA and SNc dopaminergic neurons. C_LIO_LIVTA and SNc dopaminergic neurons form over 25 connectomic cell types. C_LIO_LIProjections are organized into stereotyped motifs that may mediate the distinct functions of dopamine. C_LI

neuroscience↗

bioRxiv2025

MAPseq2: a sensitive and cost-effective barcoded connectomics method

The barcoded connectomics tool MAPseq enables highly multiplexed projection mapping of individual neurons by translating neuroanatomy into a format solvable by DNA sequencing. Here we present MAPseq2, a user-friendly protocol with up to [~]10-fold increased sensitivity compared to the current state of the art and [~]10-fold decreased cost. As MAPseq workflows are used across a range of barcoded connectomics methods, including BARseq, BRICseq, and ConnectID, all improvements in MAPseq2 directly transfer to these technologies.

neuroscience↗

bioRxiv2023

Alignment of spatial transcriptomics data using diffeomorphic metric mapping

Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we developed STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. We show that STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over landmark-based affine alignments. Applying STalign to align ST datasets of the mouse brain to the 3D common coordinate framework from the Allen Brain Atlas, we highlight how STalign can be used to lift over brain region annotations and enable the interrogation of compositional heterogeneity across anatomical structures. STalign is available as an open-source Python toolkit at https://github.com/JEFworks-Lab/STalign and as supplementary software with additional documentation and tutorials available at https://jef.works/STalign.

bioinformatics↗

bioRxiv2021

Wiring logic of the early rodent olfactory system revealed by high-throughput sequencing of single neuron projections

The structure of neuronal connectivity often provides insights into the relevant stimulus features, such as spatial location, orientation, sound frequency, etc1-6. The olfactory system, however, appears to lack structured connectivity as suggested by reports of broad and distributed connections both from the olfactory bulb to the piriform cortex7-22 and within the cortex23-25. These studies have inspired computational models of circuit function that rely on random connectivity26-33. It remains, nonetheless, unclear whether the olfactory connectivity contains spatial structure. Here, we use high throughput anatomical methods (MAPseq and BARseq)34-38 to analyze the projections of 5,309 bulb and 30,433 piriform cortex output neurons in the mouse at single-cell resolution. We identify previously unrecognized spatial organization in connectivity along the anterior-posterior axis (A-P) of the piriform cortex. We find that both the bulb projections to the cortex and the cortical outputs are not random, but rather form gradients along the A-P axis. Strikingly, these gradients are matched: bulb neurons targeting a given location within the piriform cortex co-innervate extra-piriform regions that receive strong inputs from neurons within that piriform locus. We also identify signatures of local connectivity in the piriform cortex. Our findings suggest an organizing principle of matched direct and indirect olfactory pathways that innervate extra-piriform targets in a coordinated manner, thus supporting models of information processing that rely on structured connectivity within the olfactory system.

neuroscience↗

bioRxiv2020

Single-cell transcriptomes of developing and adult olfactory receptor neurons in Drosophila

Recognition of environmental cues is essential for the survival of all organisms. Precise transcriptional changes occur to enable the generation and function of the neural circuits underlying sensory perception. To gain insight into these changes, we generated single-cell transcriptomes of Drosophila olfactory receptor neurons (ORNs), thermosensory and hygrosensory neurons from the third antennal segment at an early developmental and adult stage. We discovered that ORNs maintain expression of the same olfactory receptors across development. Using these receptors and computational approaches, we matched transcriptomic clusters corresponding to anatomically and physiologically defined neuronal types across multiple developmental stages. Cell-type-specific transcriptomes, in part, reflected axon trajectory choices in early development and sensory modality in adults. Our analysis also uncovered type-specific and broadly expressed genes that could modulate adult sensory responses. Collectively, our data reveal important transcriptomic features of sensory neuron biology and provides a resource for future studies of their development and physiology.

neuroscience↗

bioRxiv2020

Cerebellar nuclei evolved by repeatedly duplicating a conserved cell type set

How have complex brains evolved from simple circuits? Here we investigated brain region evolution at cell type resolution in the cerebellar nuclei (CN), the output structures of the cerebellum. Using single-nucleus RNA sequencing in mice, chickens, and humans, as well as STARmap spatial transcriptomic analysis and whole-CNS projection tracing in mice, we identified a conserved cell type set containing two classes of region-specific excitatory neurons and three classes of region-invariant inhibitory neurons. This set constitutes an archetypal CN that was repeatedly duplicated to form new regions. Interestingly, the excitatory cell class that preferentially funnels information to lateral frontal cortices in mice becomes predominant in the massively expanded human Lateral CN. Our data provide the first characterization of CN transcriptomic cell types in three species and suggest a model of brain region evolution by duplication and divergence of entire cell type sets.

neuroscience↗

bioRxiv2020

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks

Single-cell transcriptomics has been widely applied to classify neurons in the mammalian brain, while systems neuroscience has historically analyzed the encoding properties of cortical neurons without considering cell types. Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) projection neurons relate to axonal projections and encoding properties across multiple cognitive tasks. We found that most types projected to multiple targets, and most targets received projections from multiple types, except PFC[->]PAG (periaqueductal gray). By comparing Ca2+-activity of the molecularly homogeneous PFC[->]PAG type against two heterogeneous classes in several two-alternative choice tasks in freely-moving mice, we found that all task-related signals assayed were qualitatively present in all examined classes. However, PAG-projecting neurons most potently encoded choice in cued tasks, whereas contralateral PFC-projecting neurons most potently encoded reward context in an uncued task. Thus, task signals are organized redundantly, but with clear quantitative biases across cells of specific molecular-anatomical characteristics.

neuroscience↗

bioRxiv2019

Mapping Mesoscale Axonal Projections in the Mouse Brain Using A 3D Convolutional Network

The projection targets of a neuronal population are a key feature of its anatomical characterization. Historically, tissue sectioning, confocal microscopy, and manual scoring of specific regions of interest have been used to generate coarse summaries of mesoscale projectomes. We present here TrailMap, a 3D convolutional network for extracting axonal projections from intact cleared mouse brains imaged by light-sheet microscopy. TrailMap allows region-based quantification of total axon content in large and complex 3D structures after registration to a standard reference atlas. The identification of axonal structures as thin as one voxel benefits from data augmentation but also requires a loss function that tolerates errors in annotation. A network trained with volumes of serotonergic axons in all major brain regions can be generalized to map and quantify axons from thalamocortical, deep cerebellar, and cortical projection neurons, validating transfer learning as a tool to adapt the model to novel categories of axonal morphology. Speed of training, ease of use, and accuracy improve over existing tools without a need for specialized computing hardware. Given the recent emphasis on genetically and functionally defining cell types in neural circuit analysis, TrailMap will facilitate automated extraction and quantification of axons from these specific cell types at the scale of the entire mouse brain, an essential component of deciphering their connectivity.

neuroscience↗

bioRxiv2018

SYNPLA: A synapse-specific method for identifying learning-induced synaptic plasticity loci

Which neural circuits undergo synaptic changes when an animal learns? Although it is widely accepted that changes in synaptic strength underlie many forms of learning and memory, it remains challenging to connect changes in synaptic strength at specific neural pathways to specific behaviors and memories. Here we introduce SYNPLA (SYNaptic Proximity Ligation Assay), a synapse-specific, high-throughput and potentially brain-wide method capable of detecting circuit-specific learning-induced synaptic plasticity.

neuroscience↗

bioRxiv2018

Single-cell molecular connectomics of intracortically-projecting neurons

The neocortex is organized into distinct areas, whose interconnectivity underlies sensorimotor transformations and integration1-7. These behaviorally critical functions are mediated by intracortically-projecting neurons (ICPN), which are a heterogeneous population of cells sending axonal branches to distinct cortical areas as well as to subcortical targets8-10. Although population-based11-14 and single-cell15-19 intracortical wiring diagrams are being identified, the transcriptional signatures corresponding to single-cell axonal projections of ICPN to multiple sites remain unknown. To address this question, we developed a high-throughput approach, \"ConnectID\", to link connectome and transcriptome in single neurons. ConnectID combines MAPseq projection mapping17,20 (to identify single-neuron multiplex projections) with single-cell RNA sequencing (to identify corresponding gene expression). Using primary somatosensory cortex (S1) ICPN as proof-of-principle neurons, we identify three cardinal targets: (1) the primary motor cortex (M1), (2) the secondary somatosensory cortex (S2) and (3) subcortical targets (Sub). Using ConnectID, we identify transcriptional modules whose combined activities reflect multiplex projections to these cardinal targets. Based on these findings, we propose that the combinatorial activity of connectivity-defined transcriptional modules serves as a generic molecular mechanism to create diverse axonal projection patterns within and across neuronal cell types.

neuroscience↗

bioRxiv2018

Spatial organization of projection neurons in the mouse auditory cortex identified by in situ barcode sequencing

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single neuron resolution and high throughput, a challenging combination with conventional methods. Here we introduce BARseq, a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain, and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (IT, PT-like and CT) of projection neurons. In depth analysis uncovered a novel projection type restricted almost exclusively to transcriptionally-defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

neuroscience↗

bioRxiv2017

A single-cell anatomical blueprint for intracortical information transfer from primary visual cortex

The wiring diagram of the neocortex determines how information is processed across dozens of cortical areas. Each area communicates with multiple others via extensive long-range axonal projections 1-6, but the logic of inter-area information transfer is unresolved. Specifically, the extent to which individual neurons send dedicated projections to single cortical targets or distribute their signals across multiple areas remains unclear5,7-20. Distinguishing between these possibilities has been challenging because axonal projections of only a few individual neurons have been reconstructed. Here we map the projection patterns of axonal arbors from 591 individual neurons in mouse primary visual cortex (V1) using two complementary methods: whole-brain fluorescence-based axonal tracing21,22 and high-throughput DNA sequencing of genetically barcoded neurons (MAPseq)23. Although our results confirm the existence of dedicated projections to certain cortical areas, we find these are the exception, and that the majority of V1 neurons broadcast information to multiple cortical targets. Furthermore, broadcasting cells do not project to all targets randomly, but rather comprise subpopulations that either avoid or preferentially innervate specific subsets of cortical areas. Our data argue against a model of dedicated lines of intracortical information transfer via \"one neuron - one target area\" mapping. Instead, long-range communication between a sensory cortical area and its targets may be based on a principle whereby individual neurons copy information to, and potentially coordinate activity across, specific subsets of cortical areas.

neuroscience↗