Skip to content
Open access

Whole-transcriptome-scale isoform-resolved spatial imaging of single cells in tissues.

Jul 2026 · Cell · Vol 189, pp. 6189-6207.e10 · 3 citations · 156 references
Medicine

TL;DR

An in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues is introduced.

Abstract

Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.

Read PDF

Similar papers

Open access Sep 2026

Imaging-based spatial isoform transcriptomics resolves transcript diversity at cellular and subcellular resolution

Spatial transcriptomics has transformed our understanding of tissue organization, yet current high-throughput approaches remain largely confined to a gene-centric paradigm, precluding systematic characterization of spatially resolved transcript isoform diversity. Here, we introduce imaging-based spatial isoform transcr...

McAndrew Eamon, Fierville Morgane, Gautier-Isola Marine et al. · 0 citations
Review Sep 2026

Single-cell and spatial transcriptomics inform mechanistic physiology in non-model animals

This review provides a physiology-centered blueprint for applying single-cell RNA sequencing, single-nucleus RNA sequencing, and spatial transcriptomics to non-model species and critically evaluates dissociation and preservation bias, genome annotation, seasonal and ecological variation, biological replication, pseudor...

Adnan Amin, W. Zaman · 0 citations
Open access Sep 2026

Single-cell splice isoform usage reveals distinct axes of cellular identity and senescence

Alternative splicing greatly expands the diversity of gene products encoded by the human genome. Single-cell transcriptomic atlases have characterized human cell types through gene-level expression, but short-read sequencing has limited the ability to resolve full-length isoforms and their functional consequences. Here...

Madhav Mantri, A. Detweiler, Jaeyoon Lee et al. · 0 citations
Review Aug 2026

EXPRESS: Harnessing Single-Cell Gene Regulatory Networks for Precision Health.

This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data.

J. López-Castiblanco, L. López-Kleine, Yesid Cuesta-Astroz · 0 citations
Open access Sep 2026

A systematic single-cell analysis of enhancer RNAs across human and mouse

Abstract Enhancer RNAs (eRNAs) contribute to gene expression specificity, yet their expression patterns at single-cell resolution remain poorly understood. Across 184 329 high-quality single cells from 187 full-length single-cell RNA-seq datasets, we identified 85 977 human and 82 727 mouse eRNAs, which were sparsely d...

Hao Rong, He-Ting Liu, Yan-Guo Li et al. · 0 citations
Open access Sep 2026

Precision-Based Filtering Facilitates Cross-Referencing of Conventional and Single-Nucleus Transcriptomes to Identify Time- and Temperature-Sensitive Cell Populations.

It is shown, using two independent Arabidopsis RNAseq datasets, that this filter allows for the inclusion of many more transcription factors than even a low-stringency expression level filter, and it is found that these lowly-expressed genes mark specific cell clusters in the single-nucleus (sn)RNAseq dataset and may f...

Adam Seluzicki, Travis A. Lee, N. Hartwick et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.