Cited by 671Single-cell and spatial transcriptomicsGenomics and Chromatin DynamicsGene Regulatory Network Analysis

In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus

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Shah, Sheel, Lubeck, Eric, Zhou, Wen, Cai, Long·2016·Neuron

Abstract

Identifying the spatial organization of tissues at cellular resolution from single-cell gene expression profiles is essential to understanding biological systems. Using an in situ 3D multiplexed imaging method, seqFISH, we identify unique transcriptional states by quantifying and clustering up to 249 genes in 16,958 cells to examine whether the hippocampus is organized into transcriptionally distinct subregions. We identified distinct layers in the dentate gyrus corresponding to the granule cell layer and the subgranular zone and, contrary to previous reports, discovered that distinct subregions within the CA1 and CA3 are composed of unique combinations of cells in different transcriptional states. In addition, we found that the dorsal CA1 is relatively homogeneous at the single cell level, while ventral CA1 is highly heterogeneous. These structures and patterns are observed using different mice and different sets of genes. Together, these results demonstrate the power of seqFISH in transcriptional profiling of complex tissues.

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  • ANOVA-based methods for differential expression between groups of cells can only detect variations captured by differences between discrete groups.

    “Critically, such methods can only detect variations that are captured by differences between discrete groups.”

    From SpatialDE: identification of spatially variable genes (2018) · cites this paper as [7]

    The Experimental Procedure (Clustering; page unavailable) describes correlation-based clustering and random-forest classification, while the Results (Combinatorial expression patterns define fine clusters; page unavailable) discusses variation within the expression data. Neither passage addresses whether ANOVA-based differential-expression methods can detect only variation between discrete groups. Searches for “ANOVA” and that specific limitation found no relevant passage in our copy. (LLM, conf=0.76)

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Authors
Shah, S., Lubeck, E., Zhou, W., & Cai, L.
Affiliations
California Institute of Technology (US)
Corresponding author
Cai, Long
Venue
Neuron
Publisher
Elsevier BV
Published
2016-10
Volume
92
Issue
2
Pages
342-357
ISSN
0896-6273 (ISSN-L)
OpenAlex
W2533012945
Cited by
671
References
10
Citations by year
2026: 45 · 2025: 85 · 2024: 101 · 2023: 56 · 2022: 71 · 2021: 86 · 2020: 54 · 2019: 60 · 2018: 74 · 2017: 36 · 2016: 3
FWCI
24.77
Type
journal article
Language
en
Update notices
addendum (2017-05-17)
Open access
Locations
  • Neuron (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Funders
  • Allen Foundation
  • National Institutes of Health (1dp2od008530-01)
  • National Institute on Drug Abuse (R21DA038468)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD075605)
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 Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
hippocampus, seqFISH, dentate gyrus, CA1, CA3, granular layer, subgranular zone, transcriptional heterogeneity
MeSH terms
Animals, Base Sequence, Female, Mice, Inbred C57BL, Neurons, RNA, Messenger, In Situ Hybridization, Fluorescence, Dentate Gyrus, Gene Expression Profiling, Mice, CA1 Region, Hippocampal, CA3 Region, Hippocampal, Transcriptome

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