In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus

By Sheel Shah, Eric Lubeck, Wen Zhou, Long Cai. Neuron, 2016

674 citations recorded by the source corpus.

Summary 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 homogenous 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.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4070df7919640892c8121d2bd496fdbfd23ef2a5

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Citations in the corpus

SpatialDE: identification of spatially variable genes (2018, positive): “Alternatively, researchers have applied analysis of variance (ANOVA) to test for differential expression between groups of cells, either using a priori defined cell annotations, or based on sample clustering2,3,6,7, with some methods incorporating spatial information10.”
The Human Cell Atlas (2017, methodology): “Some strategies for RNA detection, such as MERFISH (Chen et al., 2015c; Moffitt et al., 2016b) or Seq-FISH (Shah et al., 2016), combine multiplex hybridization with microscopy-based quantification to assess distributions at both the cellular and subcellular level; other early studies have performed ”
LNCcation: lncRNA localization and function (2021, background): “Generally, these phase condensates represent ribonucleoprotein (RNP) complexes where protein–protein, RNA–protein, and RNA–RNA interactions promote condensation (Banani et al., 2017; Fay et al., 2017; Protter and Parker, 2016; Shin and Brangwynne, 2017; Van Treeck et al., 2018; see text box).”
Identification of spatial expression trends in single-cell gene expression data (2018, positive): “spatial patterns in spatial transcriptomics data (mouse olfactory bulb and breast cancer sections4) and in sequential FISH (seqFISH) data (hippocampus)3.”
Exponential scaling of single-cell RNA-seq in the past decade (2017, methodology): “Other methods based on single molecule fluorescent in situ hybridisation (smFISH) have been scaled up to measure expression of up to 1,000 pre-defined target genes in tens of thousands of single cells using imaging (Moffitt et al., 2016a, 2016b; Shah et al., 2016) .”
Challenges in unsupervised clustering of single-cell RNA-seq data (2019, methodology): “Another very useful strategy is to use spatial methods, for example, seqFISH 84 , RNAscope 85 and merFISH 86 .”