The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Nanoscale imaging of RNA with expansion microscopy
Open accessAbstract
The ability to image RNA identity and location with nanoscale precision in intact tissues is of great interest for defining cell types and states in normal and pathological biological settings. Here, we present a strategy for expansion microscopy of RNA. We developed a small-molecule linker that enables RNA to be covalently attached to a swellable polyelectrolyte gel synthesized throughout a biological specimen. Then, postexpansion, fluorescent in situ hybridization (FISH) imaging of RNA can be performed with high yield and specificity as well as single-molecule precision in both cultured cells and intact brain tissue. Expansion FISH (ExFISH) separates RNAs and supports amplification of single-molecule signals (i.e., via hybridization chain reaction) as well as multiplexed RNA FISH readout. ExFISH thus enables super-resolution imaging of RNA structure and location with diffraction-limited microscopes in thick specimens, such as intact brain tissue and other tissues of importance to biology and medicine.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Spatially resolved, highly multiplexed RNA profiling in single cells
Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969
Imaging individual mRNA molecules using multiple singly labeled probes
Raj, A., van den Bogaard, P., Rifkin, S. A., van Oudenaarden, A., & Tyagi, S. (2008) · Nature Methods · doi:10.1038/nmeth.1253 · Cited by 2,028
Self-citationVisualization of Single RNA Transcripts in Situ
Femino, A. M., Fay, F. S., Fogarty, K., & Singer, R. H. (1998) · Science · doi:10.1126/science.280.5363.585 · Cited by 1,504
Clemson, C. M., Hutchinson, J. N., Sara, S. A., Ensminger, A. W., Fox, A. H., Chess, A., & Lawrence, J. B. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.01.026 · Cited by 1,445
Single-cell in situ RNA profiling by sequential hybridization
Lubeck, E., Coskun, A. F., Zhiyentayev, T., Ahmad, M., & Cai, L. (2014) · Nature Methods · doi:10.1038/nmeth.2892 · Cited by 985
In situ sequencing for RNA analysis in preserved tissue and cells
Ke, R., Mignardi, M., Pacureanu, A., Svedlund, J., Botling, J., Wählby, C., & Nilsson, M. (2013) · Nature Methods · doi:10.1038/nmeth.2563 · Cited by 934
Cited by
Cellpose: a generalist algorithm for cellular segmentation
Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021) · Nature Methods · doi:10.1038/s41592-020-01018-x · Cited by 4,369
Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife · doi:10.7554/elife.27041 · Cited by 2,232
Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH
Eng, C.-H. L., Lawson, M., Zhu, Q., Dries, R., Koulena, N., Takei, Y., Yun, J., Cronin, C., Karp, C., Yuan, G.-C., et al. (2019) · Nature · doi:10.1038/s41586-019-1049-y · Cited by 1,754
Three-dimensional intact-tissue sequencing of single-cell transcriptional states
Wang, X., Allen, W. E., Wright, M. A., Sylwestrak, E. L., Samusik, N., Vesuna, S., Evans, K., Liu, C., Ramakrishnan, C., Liu, J., et al. (2018) · Science · doi:10.1126/science.aat5691 · Cited by 1,620
The technological landscape and applications of single-cell multi-omics
Baysoy, A., Bai, Z., Satija, R., & Fan, R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00615-w · Cited by 1,037
Neuronal cell-type classification: challenges, opportunities and the path forward
Zeng, H., & Sanes, J. R. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.85 · Cited by 841
Shah, S., Lubeck, E., Zhou, W., & Cai, L. (2016) · Neuron · doi:10.1016/j.neuron.2016.10.001 · Cited by 671
Spatially resolved transcriptomes—next generation tools for tissue exploration
Asp, M., Bergenstråhle, J., & Lundeberg, J. (2020) · BioEssays · doi:10.1002/bies.201900221 · Cited by 666
The expanding vistas of spatial transcriptomics
Tian, L., Chen, F., & Macosko, E. Z. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01448-2 · Cited by 539
Self-citationHighly multiplexed in situ protein imaging with signal amplification by Immuno-SABER
Saka, S. K., Wang, Y., Kishi, J. Y., Zhu, A., Zeng, Y., Xie, W., Kirli, K., Yapp, C., Cicconet, M., Beliveau, B. J., et al. (2018) · doi:10.1101/507566 · Cited by 485
Self-citationImmuno-SABER enables highly multiplexed and amplified protein imaging in tissues
Saka, S. K., Wang, Y., Kishi, J. Y., Zhu, A., Zeng, Y., Xie, W., Kirli, K., Yapp, C., Cicconet, M., Beliveau, B. J., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0207-y · Cited by 481
Self-citationThe promise of spatial transcriptomics for neuroscience in the era of molecular cell typing
Lein, E., Borm, L. E., & Linnarsson, S. (2017) · Science · doi:10.1126/science.aan6827 · Cited by 383
Protection of tissue physicochemical properties using polyfunctional crosslinkers
Park, Y.-G., Sohn, C. H., Chen, R., McCue, M., Yun, D. H., Drummond, G. T., Ku, T., Evans, N. B., Oak, H. C., Trieu, W., et al. (2019) · Nature Biotechnology · doi:10.1038/nbt.4281 · Cited by 421
The emerging landscape of spatial profiling technologies
Moffitt, J. R., Lundberg, E., & Heyn, H. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00515-3 · Cited by 419
Iterative expansion microscopy
Chang, J.-B., Chen, F., Yoon, Y.-G., Jung, E. E., Babcock, H., Kang, J. S., Asano, S., Suk, H.-J., Pak, N., Tillberg, P. W., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4261 · Cited by 386
Self-citationIntracellular mRNA transport and localized translation
Das, S., Vera, M., Gandin, V., Singer, R. H., & Tutucci, E. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00356-8 · Cited by 382
Moffitt, J. R., Hao, J., Bambah-Mukku, D., Lu, T., Dulac, C., & Zhuang, X. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1617699113 · Cited by 308
Molecular atlas of the adult mouse brain
Ortiz, C., Navarro, J. F., Jurek, A., Märtin, A., Lundeberg, J., & Meletis, K. (2020) · Science Advances · doi:10.1126/sciadv.abb3446 · Cited by 286
Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH
Fang, R., Xia, C., Close, J. L., Zhang, M., He, J., Huang, Z., Halpern, A. R., Long, B., Miller, J. A., Lein, E. S., et al. (2022) · Science · doi:10.1126/science.abm1741 · Cited by 277
Hu, P., Fabyanic, E., Kwon, D. Y., Tang, S., Zhou, Z., & Wu, H. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.11.017 · Cited by 162
Spatially resolved transcriptomics in neuroscience
Close, J. L., Long, B. R., & Zeng, H. (2021) · Nature Methods · doi:10.1038/s41592-020-01040-z · Cited by 94
Exploring single cells in space and time during tissue development, homeostasis and regeneration
Mayr, U., Serra, D., & Liberali, P. (2019) · Development · doi:10.1242/dev.176727 · Cited by 63
Kohman, R. E., Kunjapur, A. M., Hysolli, E., Wang, Y., & Church, G. M. (2018) · Angewandte Chemie International Edition · doi:10.1002/anie.201707976 · Cited by 33
Self-citation
Metadata
- Authors
- Chen, F., Wassie, A. T., Cote, A. J., Sinha, A., Alon, S., Asano, S., Daugharthy, E. R., Chang, J.-B., Marblestone, A., Church, G. M., Raj, A., & Boyden, E. S.
- Venue
- Nature Methods
- Published
- 2016-07-04
- Volume
- 13
- Issue
- 8
- Pages
- 679-684
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2472582738
- Cited by
- 404
- References
- 8
- FWCI
- 20.93
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.