Biology subjects

Zeisel, A.

Publications and source records attributed to Zeisel, A..

11 recordsLinked to original sources

bioRxiv2025

Behavioral age-detection in individuals reconstructs minute-scale developmental transcriptomics

Capturing rapid changes in gene-expression across development time is crucial for uncovering the molecular pathways that organize dynamic developmental processes. Here, we introduce BehaveSeq, a method that enables time reconstruction of minute-resolution developmental patterns of gene-expression by integrating longitudinal behavioral monitoring for precise age detection with genome-wide transcriptomic profiling in single individuals. By densely sampling individuals every [~]3 minutes during hours of C. elegans development, we uncovered thousands of genes exhibiting rapid and temporally structured expression trajectories. These genes were organized into distinct dynamical patterns associated with specific developmental functions. Moreover, time-reconstruction of transcriptional trajectories in serotonin-deficient individuals revealed time-specific neuromodulatory effects on developmental expression programs. Interestingly, using the same single-animal datasets, we were able to train a neural network model that accurately predicts the developmental age of each individual based on its individual-specific molecular signature. Overall, our method provides a new framework for revealing dynamic gene regulation with high temporal precision across developmental timescales.

developmental biology↗

bioRxiv2024

Brain-wide monosynaptic connectivity mapping with ROInet-seq

Viral projection tracing strategies help establish regional connectomes of mammalian brains. Monosynaptic connectivity tracing with G-deleted rabies virus (RV) establishes synaptic input connectivity, but cannot distinguish networks at cell resolution. We implemented a barcoded {Delta}G rabies virus to introduce unique molecular tags - and make network tracing amenable to readout by RNA-sequencing. First, we optimized and characterized library complexity and uniformity, such that detection of specific barcodes can reliably distinguish the individual monosynaptic input networks of multiple infected neurons in parallel. To deploy the method at scale; to hundreds of cells and full-brain volume per experiment, we developed regions-of-interest network sequencing (ROInet-seq); an accessible, scalable and low-cost spatial assay. ROInet-seq combines routine fluorescent imaging and processing of fixed tissue sections with a simple molecular biology workflow to capture barcode sequences in relevant regions-of-interest, and ultimately describes single-neuron networks brain-wide. In cortical brain areas the assay revealed preserved regional network motives, including co-inputs to single cortical neurons from distant and local sites. Towards improved spatial resolution and simultaneous detection of transcriptomes and networks we finally sampled barcoded {Delta}G rabies virus-infected hippocampus on commercial spatial transcriptomics assays and reveal details of the regions neurons local network architecture.

neuroscience↗

bioRxiv2023

A telencephalon cell type atlas for goldfish reveals diversity in the evolution of spatial structure and cell types

Teleost fish form the largest group of vertebrates, making them critically important for the study on the mechanisms of brain evolution. In fact, teleosts show a tremendous variety of adaptive behaviors similar to birds and mammals, however, the neural basis mediating these behaviors remains elusive. We performed a systematic comparative survey of the goldfish telencephalon; the seat of plastic behavior, learning and memory in vertebrates. We delineated and mapped goldfish telencephalon cell types using single-cell RNA-seq and spatial transcriptomics, resulting in de novo molecular neuroanatomy parcellation. Glial cells were highly conserved across 450 million years of evolution separating mouse and goldfish, while neurons showed diversity and modularity in gene expression. Specifically, somatostatin (SST) interneurons, famously interspersed in the mammalian isocortex for local inhibitory input, were curiously aggregated in a single goldfish telencephalon nucleus, but molecularly conserved. Cerebral nuclei including the striatum, a hub for motivated behavior in amniotes, had molecularly and spatially conserved goldfish homologues. We further suggest different elements of a hippocampal formation across the goldfish pallium. Together, our atlas provides new insights to organization and evolution of vertebrate forebrains and may serve as a resource for the functional study underlying cognition in teleost fish. TeaserDetailed mapping of goldfish forebrain cells unwraps how 450 million years of evolution may have impacted brain function

neuroscience↗

bioRxiv2022

Cell types in the mouse amygdala and their transcriptional response to fear conditioning

The amygdala is one of the most widely studied regions in behavioral neuroscience. A plethora of classical, and new paradigms have dissected its precise involvement in emotional and social sensing, learning, and memory. Several important insights resulted from the use of genetic markers - yet, in the age of single cell transcriptomics, the amygdala remains molecularly underdescribed. Here, we present a molecular cell type taxonomy of the full mouse amygdala in fear learning and consolidation. We performed single-cell RNA-seq on naive and fear conditioned mice, inferred the 130 neuronal cell types distributions in silico using orthogonal spatial transcriptomic datasets, and describe the cell types transcriptional responses to learning and memory consolidation. Only a fraction of cells, within a subset of all neuronal types, were transcriptionally responsive to fear learning, memory and retrieval. These activated engram cells upregulated activity-response genes, and processes of synaptic signaling, plasticity, development and neurite outgrowth. Our transcriptome-wide data confirm known actors, and describe several new candidate genes. The atlas may help pinpoint the amygdalas circuits in performing emotional sensing and integration, and provide new insights to the global cellular processes involved.

neuroscience↗

bioRxiv2022

Sex-, strain and lateral differences in brain cytoarchitecture across a large mouse population

The mouse brain is by far the most intensively studied among mammalian brains, yet basic measures of its cytoarchitecture remain obscure. For example, quantifying cell numbers, and the interplay of sex-, strain-, and individual variability in cell density and volume is out of reach for many regions. The Allen Mouse Brain Connectivity project produces high-resolution full brain images of hundreds of brains. Although these were created for a different purpose, they reveal details of neuroanatomy and cytoarchitecture. Here, we used this population to systematically characterize cell density and volume for each anatomical unit in the mouse brain. We developed a deep neural network-based segmentation pipeline that uses the auto-fluorescence intensities of images to segment cell nuclei even within the densest regions, such as the dentate gyrus. We applied our pipeline to 537 brains of males and females from C57BL/6J and FVB.CD1 strains. Globally, we found that increased overall brain volume does not result in uniform expansion across all regions. Moreover, region-specific density changes are often negatively correlated with the volume of the region, therefore cell count does not scale linearly with volume. Many regions, including layer 2/3 across several cortical areas, showed distinct lateral bias. We identified the greatest strain-specific or sex-specific differences in the medial amygdala (MEA), bed nuclei (BST), lateral septum and olfactory system (e.g., MOB, AOB, TR) and prefrontal areas (e.g., ORB) - yet, inter-individual variability was always greater than the effect size of a single qualifier. We provide the results of this analysis as an accessible resource for the community.

neuroscience↗

bioRxiv2018

Molecular architecture of the mouse nervous system

The mammalian nervous system executes complex behaviors controlled by specialised, precisely positioned and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse, and were grouped by developmental anatomical units, and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission and membrane conductance. We discovered several distinct, regionally restricted, astrocytes types, which obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity, followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system, and enables genetic manipulation of specific cell types.

neuroscience↗

bioRxiv2018

Spatial organization of the somatosensory cortex revealed by cyclic smFISH

The global efforts towards the creation of a molecular census of the brain using single-cell transcriptomics is generating a large catalog of molecularly defined cell types lacking spatial information. Thus, new methods are needed to map a large number of cell-specific markers simultaneously on large tissue areas. Here, we developed a cyclic single molecule fluorescence in situ hybridization methodology and defined the cellular organization of the somatosensory cortex using markers identified by single-cell transcriptomics.

neuroscience↗

bioRxiv2017

RNA velocity in single cells

RNA abundance is a powerful indicator of the state of individual cells, but does not directly reveal dynamic processes such as cellular differentiation. Here we show that RNA velocity--the time derivative of RNA abundance--can be estimated by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. We show that RNA velocity is a vector that predicts the future state of individual cells on a timescale of hours. We validate the accuracy of RNA velocity in the neural crest lineage, demonstrate its use on multiple technical platforms, reconstruct the branching lineage tree of the mouse hippocampus, and measure RNA kinetics in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

genomics↗

bioRxiv2017

Conservation of differentiation but transformation of initiation in hippocampal neurogenesis

The dentate gyrus in the hippocampal formation is one of few regions in the brain where neurogenesis persists in the adult, and is therefore studied in the context of neurodevelopment and regenerative medicine. However, the relationship between developmental and adult neurogenesis has not been studied in detail. Here, we used extensive and unbiased single-cell RNA-seq to reveal the molecular dynamics and diversity of cell types in perinatal, juvenile and adult mice. We found clearly distinct quiescent and proliferating progenitor cell types, linked by transient intermediate states to neuroblast stages and fully mature granule cells. The molecular identity of quiescent and proliferating radial glia shifted after postnatal day 5, and was then maintained through postnatal and adult stages. A similar shift was observed for granule cells at P20. In contrast, intermediate progenitor cells, neuroblasts and immature granule cells were nearly indistinguishable at all ages. These findings demonstrate the fundamental continunity of postnatal and adult neurogenesis in the hippocampus, and pinpoint the early postnatal transformation of radial glia from embryonic progenitors to adult quiescent stem cells.

neuroscience↗

bioRxiv2017

Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling

BackgroundMost of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region and the resolution of profiling is inherently limited. Platforms that offer ultra long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others, all allow different ways to circumvent this problem yet suffer various shortcomings. There is need for a simple and low cost 16S rRNA gene based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.\n\nResultsThis manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about two-fold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200bp (80%) of the 16S rRNA gene we were able to achieve ~100 fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~100 fold increase in resolution, and thus enabling efficient downstream analysis.\n\nConclusionsSMURF enables identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of Formalin-fixed and Paraffin-embedded samples, fossil-derived DNA or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in Multilocus Sequence Typing (MLST).

bioinformatics↗

bioRxiv2017

STRT-seq-2i: dual-index 5′ single cell and nucleus RNA-seq on an addressable microwell array

Single-cell RNA-seq has become routine for discovering cell types and revealing cellular diversity, but currently no high-throughput platform has been used successfully on archived human brain samples. We present STRT-seq-2i, an addressable 9600-microwell array platform, combining sampling by limiting dilution or FACS, with imaging and high throughput at competitive cost. We applied the platform to fresh single mouse cortical cells and to frozen post-mortem human cortical nuclei, matching the performance of a previous lower-throughput platform.

molecular biology↗