Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex.
IF: 68.164
Cited by: 740


Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.


Gene Expression

MeSH terms

Cerebral Cortex
Computational Biology
Equipment Design
Gene Expression Profiling
Microfluidic Analytical Techniques
RNA, Messenger
Sequence Analysis, RNA
Signal Transduction


Pollen, Alex A
Nowakowski, Tomasz J
Shuga, Joe
Wang, Xiaohui
Leyrat, Anne A
Lui, Jan H
Li, Nianzhen
Szpankowski, Lukasz
Fowler, Brian
Chen, Peilin
Ramalingam, Naveen
Sun, Gang
Thu, Myo
Norris, Michael
Lebofsky, Ronald
Toppani, Dominique
Kemp, Darnell W 2nd
Wong, Michael
Clerkson, Barry
Jones, Brittnee N
Wu, Shiquan
Knutsson, Lawrence
Alvarado, Beatriz
Wang, Jing
Weaver, Lesley S
May, Andrew P
Jones, Robert C
Unger, Marc A
Kriegstein, Arnold R
West, Jay A A

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