ArticleFrontiers in genetics2022
Full-Length Spatial Transcriptomics Reveals the Unexplored Isoform Diversity of the Myocardium Post-MI.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 33 citations in OpenAlex.
- Amplification bias in sequencing-based spatial transcriptomics: sources, mechanisms, impacts, and mitigation strategies.Briefings in bioinformatics · 2026Review
- Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain.Nature methods · 2026Article
- Spatiotemporal transcriptomics of human cardiovascular progenitors in pig hearts identifies Midkine as a positive regulator of neovascularization.Nature cardiovascular research · 2026Article
- Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity.Function (Oxford, England) · 2026Review
- Cellular and molecular signals of cardiac wound healing after myocardial infarction.American journal of physiology. Heart and circulatory physiology · 2026Review
- Decoding the human PBMC isonome: isoform-level resolution with single-cell long-read transcriptomics.Frontiers in genetics · 2026Article
- Decoding the human PBMC isonome: Isoform-level resolution with single-cell long-read transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking spatial transcriptomics technologies with the multi-sample SpatialBenchVisium dataset.Genome biology · 2025Article
- Application of Spatial Omics in the Cardiovascular System.Research (Washington, D.C.) · 2025Review
- Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics.Genome research · 2024Review
- Transient Inhibition of Translation Improves Cardiac Function After Ischemia/Reperfusion by Attenuating the Inflammatory Response.Circulation · 2024Article
- Review
- Integration mapping of cardiac fibroblast single-cell transcriptomes elucidates cellular principles of fibrosis in diverse pathologies.Science advances · 2024Article
- Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage.Molecular brain · 2024Article
- Advances in single-cell long-read sequencing technologies.NAR genomics and bioinformatics · 2024Article
- A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration.Cardiovascular drugs and therapy · 2024Review
- Mapping cancer biology in space: applications and perspectives on spatial omics for oncology.Molecular cancer · 2024Review
- Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases.Genome medicine · 2024Review
- Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage.bioRxiv : the preprint server for biology · 2024Article
- Spatial Transcriptomics: Technical Aspects of Recent Developments and Their Applications in Neuroscience and Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce Single-cell Nanopore Spatial Transcriptomics (scNaST), a software suite to facilitate the analysis of spatial gene expression from second- and third-generation sequencing, allowing to generate a full-length near-single-cell transcriptional landscape of the tissue microenvironment. Taking advantage of the Visium Spatial platform, we adapted a strategy recently developed to assign barcodes to long-read single-cell sequencing data for spatial capture technology. Here, we demonstrate our workflow using four short axis sections of the mouse heart following myocardial infarction. We constructed a
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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 Socratic graph.