Cited by 920Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesGene expression and cancer classification

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex

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Abstract

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.

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Metadata

Authors
Pollen, A. A., Nowakowski, T. J., Shuga, J., Wang, X., Leyrat, A. A., Lui, J. H., Li, N., Szpankowski, L., Fowler, B., Chen, P., Ramalingam, N., Sun, G., Thu, M., Norris, M., Lebofsky, R., Toppani, D., Kemp, D. W., Wong, M., Clerkson, B., Jones, B. N., Wu, S., Knutsson, L., Alvarado, B., Wang, J., Weaver, L. S., May, A. P., Jones, R. C., Unger, M. A., Kriegstein, A. R., & West, J. A. A.
Affiliations
  • University of California, San Francisco (US)
  • Standard BioTools (United States) (US)
Corresponding author
  • Pollen, Alex A
  • Kriegstein, Arnold R
Venue
Nature Biotechnology
Published
2014-08-03
Volume
32
Issue
10
Pages
1053-1058
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2051658465
Cited by
920
References
38
Citations by year
2026: 33 · 2025: 51 · 2024: 54 · 2023: 62 · 2022: 78 · 2021: 110 · 2020: 110 · 2019: 105 · 2018: 93 · 2017: 91 · 2016: 74 · 2015: 52 · 2014: 5
FWCI
30.36
Type
journal article
Language
en
Open access
Locations
  • Nature Biotechnology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
National Institute of Neurological Disorders and Stroke (R01NS072630, R01NS075998)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
single-cell transcriptomics, low-pass sequencing, cellular heterogeneity, cortical development, microfluidic cell capture, cell type classification, biomarker discovery, Notch signaling, radial glia, EGR1, FOS, human brain
MeSH terms
Animals, Cerebral Cortex, Equipment Design, Humans, RNA, Messenger, Signal Transduction, Sequence Analysis, RNA, Computational Biology, Gene Expression Profiling, Microfluidic Analytical Techniques, Mice

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