Literature DB >> 31303374

A Single-Cell Transcriptomic Atlas of Human Neocortical Development during Mid-gestation.

Damon Polioudakis1, Luis de la Torre-Ubieta2, Justin Langerman3, Andrew G Elkins1, Xu Shi4, Jason L Stein5, Celine K Vuong6, Susanne Nichterwitz7, Melinda Gevorgian8, Carli K Opland1, Daning Lu1, William Connell1, Elizabeth K Ruzzo1, Jennifer K Lowe1, Tarik Hadzic2, Flora I Hinz1, Shan Sabri3, William E Lowry9, Mark B Gerstein10, Kathrin Plath3, Daniel H Geschwind11.   

Abstract

We performed RNA sequencing on 40,000 cells to create a high-resolution single-cell gene expression atlas of developing human cortex, providing the first single-cell characterization of previously uncharacterized cell types, including human subplate neurons, comparisons with bulk tissue, and systematic analyses of technical factors. These data permit deconvolution of regulatory networks connecting regulatory elements and transcriptional drivers to single-cell gene expression programs, significantly extending our understanding of human neurogenesis, cortical evolution, and the cellular basis of neuropsychiatric disease. We tie cell-cycle progression with early cell fate decisions during neurogenesis, demonstrating that differentiation occurs on a transcriptomic continuum; rather than only expressing a few transcription factors that drive cell fates, differentiating cells express broad, mixed cell-type transcriptomes before telophase. By mapping neuropsychiatric disease genes to cell types, we implicate dysregulation of specific cell types in ASD, ID, and epilepsy. We developed CoDEx, an online portal to facilitate data access and browsing.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  autism; cortical development; differentiation; epilepsy; evolution; human; intellectual disability; neurogenesis; schizophrenia; subplate

Mesh:

Year:  2019        PMID: 31303374      PMCID: PMC6831089          DOI: 10.1016/j.neuron.2019.06.011

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


  73 in total

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  114 in total

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