ArticleNucleic acids research2016
smiFISH and FISH-quant - a flexible single RNA detection approach with super-resolution capability.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 270 papers.
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Who cites it
270 citing papers in PubMed, 473 citations in OpenAlex.
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210 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single molecule FISH (smFISH) allows studying transcription and RNA localization by imaging individual mRNAs in single cells. We present smiFISH (single molecule inexpensive FISH), an easy to use and flexible RNA visualization and quantification approach that uses unlabelled primary probes and a fluorescently labelled secondary detector oligonucleotide. The gene-specific probes are unlabelled and can therefore be synthesized at low cost, thus allowing to use more probes per mRNA resulting in a substantial increase in detection efficiency. smiFISH is also flexible since differently labelled secondary detector probes can be used with the same primary probes. We demonstrate that this flexibility allows multicolor labelling without the need to synthesize new probe sets. We further demonstrate that the use of a specific acrydite detector oligonucleotide allows smiFISH to be combined with expansion microscopy, enabling the resolution of transcripts in 3D below the diffraction limit on a standard microscope. Lastly, we provide improved, fully automated software tools from probe-design to quantitative analysis of smFISH images. In short, we provide a complete workflow to obtain automatically counts of individual RNA molecules in single cells.
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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.