scholarly journals Single-cell transcriptomics of the early developing mouse cerebral cortex disentangles the spatial and temporal components of neuronal fate acquisition

Development ◽  
2021 ◽  
Author(s):  
Matthieu X. MOREAU ◽  
Yoann SAILLOUR ◽  
Andrzej W. CWETSCH ◽  
Alessandra PIERANI ◽  
Frédéric CAUSERET
Keyword(s):  
Cerebral Cortex ◽  
Single Cell ◽  
Spatial Information ◽  
Developmental Trajectories ◽  
Specific Gene ◽  
Neuronal Fate ◽  
Mouse Cerebral Cortex ◽  
Neuronal Types ◽  
Gene Modules ◽  
Neuronal Output

In the developing cerebral cortex, how progenitors that seemingly display limited diversity end up producing a vast array of neurons remains a puzzling question. The prevailing model suggests that temporal maturation of progenitors is a key driver in the diversification of the neuronal output. However, temporal constraints are unlikely to account for all diversity, especially in the ventral and lateral pallium where neuronal types significantly differ from their dorsal neocortical counterparts born at the same time. In this study, we implemented single-cell RNAseq to sample the diversity of progenitors and neurons along the dorso-ventral axis of the early developing pallium. We first identified neuronal types, mapped them on the tissue and determined their origin through genetic tracing. We characterised progenitor diversity and disentangled the gene modules underlying temporal vs spatial regulations of neuronal specification. Finally, we reconstructed the developmental trajectories followed by ventral and dorsal pallial neurons to identify lineage-specific gene waves. Our data suggest a model by which discrete neuronal fate acquisition from a continuous gradient of progenitors results from the superimposition of spatial information and temporal maturation.

scholarly journals Single-cell transcriptomics of the early developing mouse cerebral cortex disentangles the spatial and temporal components of neuronal fate acquisition

2020 ◽  
Author(s):  
Matthieu X. Moreau ◽  
Yoann Saillour ◽  
Andrzej W. Cwetsch ◽  
Alessandra Pierani ◽  
Frédéric Causeret
Keyword(s):  
Cerebral Cortex ◽  
Single Cell ◽  
Spatial Information ◽  
Developmental Trajectories ◽  
Neuronal Fate ◽  
Mouse Cerebral Cortex ◽  
Neuronal Types ◽  
Key Driver ◽  
Cortical Regions ◽  
Neuronal Output

AbstractIn the developing cerebral cortex, how progenitors that seemingly display limited diversity end up in producing a vast array of neurons remains a puzzling question. The prevailing model that recently emerged suggests that temporal maturation of these progenitors is a key driver in the diversification of the neuronal output. However, temporal constrains are unlikely to account for all diversity across cortical regions, especially in the ventral and lateral domains where neuronal types significantly differ from their dorsal neocortical counterparts born at the same time. In this study, we implemented single-cell RNAseq to sample the diversity of progenitors and neurons along the dorso-ventral axis of the early developing pallium. We first identified neuronal types, mapped them on the tissue and performed genetic tracing to determine their origin. By characterising progenitor diversity, we disentangled the gene expression modules underlying temporal vs spatial regulations of neuronal specification. Finally, we reconstructed the developmental trajectories followed by ventral and dorsal pallial neurons to identify gene waves specific of each lineage. Our data suggest a model by which discrete neuronal fate acquisition from a continuous gradient of progenitors results from the superimposition of spatial information and temporal maturation.

scholarly journals Single-cell transcriptomic analysis identifies neocortical developmental differences between human and mouse

2020 ◽  
Author(s):  
Ziheng Zhou ◽  
Shuguang Wang ◽  
Dengwei Zhang ◽  
Xiaosen Jiang ◽  
Jie Li ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Single Cell ◽  
Developmental Trajectories ◽  
Expression Patterns ◽  
Development Stage ◽  
Inhibitory Neurons ◽  
Projection Neurons ◽  
Cerebral Cortex Development ◽  
Excitatory Neurons ◽  
Human And Mouse

AbstractBackgroundThe specification and differentiation of neocortical projection neurons is a complex process under precise molecular regulation; however, little is known about the similarities and differences in cerebral cortex development between human and mouse at single-cell resolution.ResultsHere, using single-cell RNA-seq (scRNA-seq) data we explore the divergence and conservation of human and mouse cerebral cortex development using 18,446 and 7,610 neocortical cells. Systematic cross-species comparison reveals that the overall transcriptome profile in human cerebral cortex is similar to that in mouse such as cell types and their markers genes. By single-cell trajectories analysis we find human and mouse excitatory neurons have different developmental trajectories of neocortical projection neurons, ligand-receptor interactions and gene expression patterns. Further analysis reveals a refinement of neuron differentiation that occurred in human but not in mouse, suggesting that excitatory neurons in human undergo refined transcriptional states in later development stage. By contrast, for glial cells and inhibitory neurons we detected conserved developmental trajectories in human and mouse.ConclusionsTaken together, our study integrates scRNA-seq data of cerebral cortex development in human and mouse, and uncovers distinct developing models in neocortical projection neurons. The earlier activation of cognition -related genes in human may explain the differences in behavior, learning or memory abilities between the two species.

scholarly journals Single-cell transcriptomic catalog of mouse cortical development

2017 ◽  
Author(s):  
Lipin Loo ◽  
Jeremy M. Simon ◽  
Eric S. McCoy ◽  
Jesse K. Niehaus ◽  
Mark J. Zylka
Keyword(s):  
Cerebral Cortex ◽  
Single Cell ◽  
Neurological Disease ◽  
Expression Profiles ◽  
Cortical Development ◽  
Brain Diseases ◽  
Mouse Cerebral Cortex ◽  
Transcriptomics Data ◽  
Disease Associated Genes ◽  
Cell Expression

We generated a single-cell transcriptomic catalog of the developing mouse cerebral cortex that includes numerous classes of neurons, progenitors, and glia, their proliferation, migration, and activation states, and their relatedness within and across timepoints. Cell expression profiles stratified neurological disease-associated genes into distinct subtypes. Complex neurodevelopmental processes can be reconstructed with single-cell transcriptomics data, permitting a deeper understanding of cortical development and the cellular origins of brain diseases.

scholarly journals Single-cell analysis resolves the genetic program of primary vascular system formation in hybrid poplar

2021 ◽  
Author(s):  
Daniel Conde ◽  
Paolo M. Triozzi ◽  
Wendell J. Pereira ◽  
Henry W. Schmidt ◽  
Kelly M. Balmant ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Shoot Apex ◽  
Vascular Tissue ◽  
Vascular System ◽  
Developmental Trajectories ◽  
Specific Gene ◽  
Cell Type ◽  
Woody Perennials ◽  
Cell Type Specific

Despite the enormous potential of novel approaches to explore gene expression at a single-cell level, we lack a high-resolution and cell type-specific gene expression map of the shoot apex in woody perennials. We use single-nuclei RNA sequencing to determine the cell type-specific transcriptome of the Populus vegetative shoot apex. We identified highly heterogeneous cell populations clustered into seven broad groups represented by 18 transcriptionally distinct cell clusters. Next, we established the developmental trajectories of epidermal cells, leaf mesophyll, and vascular tissue. Motivated by the high similarities between Populus and Arabidopsis cell population in the vegetative apex, we created and applied a pipeline for interspecific single-cell expression data integration. We contrasted the developmental trajectories of primary phloem and xylem formation in both species, establishing the first comparison of primary vascular development between a model annual herbaceous and a woody perennial plant species. Our results offer a valuable resource for investigating the basic principles underlying cell division and differentiation conserved between herbaceous and perennial species, which also allows the evaluation of the divergencies at single-cell resolution.

scholarly journals Multifactorial chromatin regulatory landscapes at single cell resolution

2021 ◽  
Author(s):  
Michael P. Meers ◽  
Derek H. Janssens ◽  
Steven Henikoff
Keyword(s):  
Single Cell ◽  
Target Identification ◽  
Developmental Trajectories ◽  
Single Cells ◽  
High Sensitivity ◽  
Cell Types ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Chromatin Profiling ◽  
Regulatory Landscapes

Chromatin profiling at locus resolution uncovers gene regulatory features that define cell types and developmental trajectories, but it remains challenging to map and compare distinct chromatin-associated proteins within the same sample. Here we describe a scalable antibody barcoding approach for profiling multiple chromatin features simultaneously in the same individual cells, Multiple Target Identification by Tagmentation (MulTI-Tag). MulTI-Tag is optimized to retain high sensitivity and specificity of enrichment for multiple chromatin targets in the same assay. We use MulTI-Tag to resolve distinct cell types using multiple chromatin features on a commercial single-cell platform, and to distinguish unique, coordinated patterns of active and repressive element regulatory usage in the same individual cells. Multifactorial profiling allows us to detect novel associations between histone marks in single cells and holds promise for comprehensively characterizing cell-specific gene regulatory landscapes in development and disease.

scholarly journals Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development

2021 ◽  
Author(s):  
Junil Kim ◽  
Michaela Mrugala Rothová ◽  
Linbu Liao ◽  
Siyeon Rhee ◽  
Guangzheng Weng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spatial Information ◽  
Dimensional Space ◽  
Cell Types ◽  
Cell Contact ◽  
Specific Gene ◽  
Neighboring Cell ◽  
Cell Fate Decisions ◽  
Specific Gene Expression

ABSTRACTCells continuously communicate with the neighboring cells during development. Direct interaction of different cell types can induce molecular signals dictating lineage specification and cell fate decisions. The current single cell RNAseq (scRNAseq) technology cannot study cell contact dependent gene expression due to the loss of spatial information. To overcome this issue and determine cell contact specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PICseq) and assessed alongside our single cell transcriptomes (scRNAseq) derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of PICseq data identifies an interesting suite of gene expression signatures depending on neighboring cell types. For instance, neural progenitor (NP) cells expressed Nkx2-1 when interacting with definitive endoderm (DE) and DE cells expressed Gsc when interacting with NP. Based on the identified cell contact specific genes, we devised a means to predict the neighboring cell types from individual cell transcriptome. We further developed spatial-tSNE to show the pseudo-spatial distribution of cells in a 2-dimensional space. In sum, we suggest an approach to study contact specific gene regulation during embryogenesis.

scholarly journals Recovering Spatially-Varying Cell-Specific Gene Co-expression Networks for Single-Cell Spatial Expression Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Jinge Yu ◽  
Xiangyu Luo
Keyword(s):  
Single Cell ◽  
Spatial Information ◽  
Estimation Accuracy ◽  
Dependence Structure ◽  
Specific Gene ◽  
Expression Data ◽  
Cell Type ◽  
Spatial Expression ◽  
Real World Datasets ◽  
Spatially Varying

Recent advances in single-cell technologies enable spatial expression profiling at the cell level, making it possible to elucidate spatial changes of cell-specific genomic features. The gene co-expression network is an important feature that encodes the gene-gene marginal dependence structure and allows for the functional annotation of highly connected genes. In this paper, we design a simple and computationally efficient two-step algorithm to recover spatially-varying cell-specific gene co-expression networks for single-cell spatial expression data. The algorithm first estimates the gene expression covariance matrix for each cell type and then leverages the spatial locations of cells to construct cell-specific networks. The second step uses expression covariance matrices estimated in step one and label information from neighboring cells as an empirical prior to obtain thresholded Bayesian posterior estimates. After completing estimates for each cell, this algorithm can further predict or interpolate gene co-expression networks on tissue positions where cells are not captured. In the simulation study, the comparison against the traditional cell-type-specific network algorithms and the cell-specific network method but without incorporating spatial information highlights the advantages of the proposed algorithm in estimation accuracy. We also applied our algorithm to real-world datasets and found some meaningful biological results. The accompanied software is available on https://github.com/jingeyu/CSSN.

scholarly journals Single-cell transcriptome atlas and chromatin accessibility landscape reveal differentiation trajectories in the rice root

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tian-Qi Zhang ◽  
Yu Chen ◽  
Ye Liu ◽  
Wen-Hui Lin ◽  
Jia-Wei Wang
Keyword(s):  
Single Cell ◽  
Developmental Trajectories ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Rice Root ◽  
Root Apical Meristem ◽  
Root Tip ◽  
Transcriptional Networks ◽  
Marker Genes ◽  
Specific Gene

AbstractRoot development relies on the establishment of meristematic tissues that give rise to distinct cell types that differentiate across defined temporal and spatial gradients. Dissection of the developmental trajectories and the transcriptional networks that underlie them could aid understanding of the function of the root apical meristem in both dicots and monocots. Here, we present a single-cell RNA (scRNA) sequencing and chromatin accessibility survey of rice radicles. By temporal profiling of individual root tip cells we reconstruct continuous developmental trajectories of epidermal cells and ground tissues, and elucidate regulatory networks underlying cell fate determination in these cell lineages. We further identify characteristic processes, transcriptome profiles, and marker genes for these cell types and reveal conserved and divergent root developmental pathways between dicots and monocots. Finally, we demonstrate the potential of the platform for functional genetic studies by using spatiotemporal modeling to identify a rice root meristematic mutant from a cell-specific gene cohort.

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