Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

Nano, Patricia R.; Nguyen, Claudia V.; Mil, Jessenya; Bhaduri, Aparna

doi:10.3389/fncir.2021.788560

Cited by 6 publications

(2 citation statements)

References 112 publications

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“…By identifying genes that describe subclasses, we found that GABAergic neurons conserve the most subclass features across regions. These results align with recent studies showing that cell-types vary along a continuum across cortical regions and that glutamatergic neurons exhibit greater differences than interneurons (Bhaduri et al, 2021;Nano et al, 2021;Yao et al, 2021a). The distinct clustering of pyramidal cells between ALM and VISp is thought to be accounted for by a frontal to occipital pole gradient in cell-types (Yao et al, 2021a).…”

Section: Discussionsupporting

confidence: 91%

Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism

Moussa

Wester

2022

Preprint

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A prevailing challenge in neuroscience is understanding how diverse neuronal cell types select their synaptic partners to form circuits. In the neocortex, major subclasses of excitatory projection neurons and inhibitory interneurons are conserved across functionally distinct regions. There is evidence these subclasses form circuits that depend primarily on their identity; however, regional cues likely also influence their choice of synaptic partners. We mined the Allen Brain Institute's single-cell RNA-sequencing database of mouse cortical neurons to study the expression of cellular adhesion molecules (CAMs) necessary for synapse formation in two regions: the anterior lateral motor cortex (ALM) and the primary visual cortex (VISp). We used the Allen's metadata to parse cells by clusters representing major excitatory and inhibitory subclasses that are common to both ALM and VISp. We then performed two types of pairwise differential gene expression analysis: 1) between different neuronal subclasses within the same brain region (ALM or VISp), and 2) between the same neuronal subclass in ALM and VISp. We filtered our results for differentially expressed genes encoding CAMs and developed a novel bioinformatic approach to determine the sets uniquely enriched in each neuronal subclass in ALM, VISp, or both. This analysis provides an organized set of genes that may regulate circuit formation in a cell-type specific manner. Furthermore, it identifies candidate mechanisms for the formation of circuits that are conserved across functionally distinct cortical regions or that are region dependent. Finally, we used the SFARI Human Gene Module to identify CAMs from our analysis that are related to risk for autism spectrum disorder (ASD). From over 3,000 differentially expressed genes, we found 40 ASD-associated CAMs that are enriched in specific neuronal subclasses in both ALM and VISp. Our analysis provides clear molecular targets for future studies to understand neocortical circuit organization and abnormalities that underly autistic phenotypes.

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Section: Discussionsupporting

confidence: 91%

Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism

Moussa

Wester

2022

Preprint

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“…3b ). For example, glutamatergic cells showed arealization 32 among cortical areas within each slice and dorsal–ventral separation was observed among medium spiny neurons dissected from the caudoputamen (CP) and nucleus accumbens (ACB) regions. Moreover, many subcortical dissection borders were faithfully preserved in the imputed spatial embedding.…”

Section: Spatial Epigenomic Diversitymentioning

confidence: 99%

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Liu,

Zeng,

Zhou

et al. 2023

Nature

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Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 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 taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent 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 spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular–spatial and regulatory genome diversity of the mouse brain.

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Genetics of cortical development

Bella

Habibi

2023

Encyclopedia of Child and Adolescent Health

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Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

Cited by 6 publications

References 112 publications

Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism

Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Genetics of cortical development

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