ReviewGenes2026
From Molecular Visualization to Spatial Landscapes: Engineering the Next Generation of In Situ Hybridization.
Review in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In situ hybridization (ISH) has undergone a rapid evolution from a low-throughput histological staining technique to a diverse family of modern methods for sensitive, specific and multiplexed molecular detection in intact cells and tissues, and to a cornerstone technology for image-based spatial transcriptomics. This transformation has been driven by advances in probe design, signal amplification, cyclic imaging, combinatorial barcoding, automated fluidics and computational decoding, which together allow RNA molecules to be measured within preserved cellular and tissue architecture. In this review, we examine the molecular and engineering principles that underlie modern ISH methods and their extension into ISH-based spatial profiling, with emphasis on hybridization chain reaction, branched-DNA amplification, SABER-FISH, rolling-circle-amplification-based approaches, seqFISH, MERFISH, RAEFISH and selected commercial implementations. We discuss how sensitivity, specificity, tissue compatibility, optical crowding, imaging burden, cost, reproducibility and computational uncertainty shape the practical use of each method. Sequencing-based spatial capture platforms are not reviewed comprehensively, but are considered where comparative benchmarks help clarify trade-offs in spatial resolution, transcriptome breadth, tissue area or analytical interpretation. We also consider how recent benchmarking and standardization efforts are beginning to define quantitative criteria for comparing platforms, and how advances in segmentation, barcode decoding, spatial integration and cell-cell communication analysis convert raw images into biological insight. Finally, we highlight applications in targeted transcript detection, tissue-based validation, neuroscience, cancer, developmental biology, non-model organisms and spatial functional genomics, where modern ISH methods and ISH-based spatial profiling provide information that bulk and dissociated single-cell approaches cannot capture. Together, these developments trace how ISH has expanded from targeted molecular visualization into a broad methodological framework for in situ detection and spatially resolved transcriptomic analysis.
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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.