ArticleDevelopment (Cambridge, England)2024
Open-source, high-throughput targeted in situ transcriptomics for developmental and tissue biology.
Article in Development (Cambridge, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Spatial transcriptomics differences of histopathological growth patterns in colorectal cancer liver metastases.British journal of cancer · 2026Article
- Two distinct chromatin modules regulate proinflammatory gene expression.Nature cell biology · 2026Article
- Spatiotemporal gene expression and cellular dynamics of the developing human heart.Nature genetics · 2025Article
- Charting the single-cell and spatial landscape of IDH-wild-type glioblastoma with GBmap.Neuro-oncology · 2025Article
- Spatial TCR clonality and clonal expansion in the in situ microenvironment of non-small cell lung cancer.Journal for immunotherapy of cancer · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Multiplexed spatial profiling of mRNAs has recently gained traction as a tool to explore the cellular diversity and the architecture of tissues. We propose a sensitive, open-source, simple and flexible method for the generation of in situ expression maps of hundreds of genes. We use direct ligation of padlock probes on mRNAs, coupled with rolling circle amplification and hybridization-based in situ combinatorial barcoding, to achieve high detection efficiency, high-throughput and large multiplexing. We validate the method across a number of species and show its use in combination with orthogonal methods such as antibody staining, highlighting its potential value for developmental and tissue biology studies. Finally, we provide an end-to-end computational workflow that covers the steps of probe design, image processing, data extraction, cell segmentation, clustering and annotation of cell types. By enabling easier access to high-throughput spatially resolved transcriptomics, we hope to encourage a diversity of applications and the exploration of a wide range of biological questions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.