The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
Open accessPublished version of a preprint
Abstract
Gene expression at fine scale: Mapping gene expression at the single-cell level within tissues remains a technical challenge. Rodriques et al. developed a method called Slide-seq, whereby RNA was spatially resolved from tissue sections by transfer onto a surface covered with DNA-barcoded beads. Applying Slide-seq to regions of a mouse brain revealed spatial gene expression patterns in the Purkinje layer of the cerebellum and axes of variation across Purkinje cell compartments. The authors used this method to dissect the temporal evolution of cell type–specific responses in a mouse model of traumatic brain injury. Science , this issue p. 1463
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Spatial profiling provides further information on tissue organization and three-dimensional architecture, thereby being essential for model validation186,187”
From Human disease models in drug development (2023) · cites this paper as [187]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Slide-seq captures transcripts on a slide equipped with random 10-µm DNA-barcoded beads and gains the positions of barcodes via in situ indexing, enabling spatial transcriptomic analysis at a near-cellular resolution [79].”
From Single-cell sequencing to multi-omics: technologies and applications (2024) · cites this paper as [79]
In the citing paper
“While the technologies used here do not require harsh dissociation procedures like single-cell or single-nuclei approaches and maintain spatial information, the lack of single-cell resolution with ST and the low sensitivity of ISS requires further technological improvements (Eng et al. , 2019; Rodriques et al. , 2019; Vickovic et al. , 2019; Stickels et al. , 2020).”
From Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer’s Disease (2020) · cites this paper as Rodriques et al., 2019
In the citing paper
“PET imaging of collagen and molecular imaging of fibrosis185,186, which allows fast, non-invasive, and whole-organ-quantitative and longitudinal readouts of drug efficacy in antifibrotic clinical trials”
From Fibrosis: from mechanisms to medicines (2020) · cites this paper as [185]
In the citing paper
“combining molecular imaging of fibrosis185 with cutting edge omic approaches such as single cell genomics174–176 could markedly improve patient diagnostics, staging, prognostication, stratification and cohort enrichment, which would in turn optimize clinical trial design”
From Fibrosis: from mechanisms to medicines (2020) · cites this paper as [185]
In the citing paper
“Spatially resolved sequencing uses slides pre-patterned with beads carrying unique DNA barcodes to tag mRNA molecules based on their location in a brain slice, enabling whole-transcriptome sequencing with ~10 μm spatial resolution (Rodriques et al., 2019; Ståhl et al., 2016).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Rodriques et al., 2019
In the citing paper
“For Slide-seq (Rodriques et al., 2019), this is limited by spatial resolution (~10 μm)”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Rodriques et al., 2019
In the citing paper
“Slide-seq, and later Slide-seqV2, barcode mRNA in tissues using a method conceptually similar to spatial transcriptomics, but a different strategy: instead of using arrayed barcoded reagents printed on slides, the barcoded reagents are placed directly onto the glass slide in solution, thereby creating a monolayer-packed array on a glass coverslip118,119 (Fig. 4a).”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [118]
In the citing paper
“Nonetheless, we did observe the previously reported aging-related decline of OPC 49 , NRP 35,36 and ImmN 36,50 .”
From Single-cell transcriptomic profiling of the aging mouse brain (2019) · cites this paper as [50]
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
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
Salmon provides fast and bias-aware quantification of transcript expression
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods · doi:10.1038/nmeth.4197 · Cited by 12,700
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
Self-citationGenome-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
Self-citationVisualization and analysis of gene expression in tissue sections by spatial transcriptomics
Ståhl, P. L., Salmén, F., Vickovic, S., Lundmark, A., Navarro, J. F., Magnusson, J., Giacomello, S., Asp, M., Westholm, J. O., Huss, M., et al. (2016) · Science · doi:10.1126/science.aaf2403 · Cited by 3,834
A pyramid approach to subpixel registration based on intensity
Thévenaz, P., Ruttimann, U. E., & Unser, M. A. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.650848 · Cited by 3,097
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
Conditional gene targeting in macrophages and granulocytes using LysMcre mice
Clausen, B. E., Burkhardt, C., Reith, W., Renkawitz, R., & Förster, I. (1999) · Transgenic Research · doi:10.1023/a:1008942828960 · Cited by 2,098
Molecular diversity and specializations among the cells of the adult mouse brain
Saunders, A., Macosko, E. Z., Wysoker, A., Goldman, M., Krienen, F. M., de Rivera, H., Bien, E., Baum, M., Bortolin, L., Wang, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.028 · Cited by 1,531
Self-citationStoodley, C. J., & Schmahmann, J. D. (2010) · Cortex · doi:10.1016/j.cortex.2009.11.008 · Cited by 1,360
Cocker, L. J. L. D., van Veluw, S. J., Fowkes, M. E., Luijten, P. R., Mali, W. P. T. M., & Hendrikse, J. (2013) · Cerebrovascular Diseases · doi:10.1159/000353668 · Cited by 1,163
Single-cell spatial reconstruction reveals global division of labour in the mammalian liver
Halpern, K. B., Shenhav, R., Matcovitch-Natan, O., Tóth, B., Lemze, D., Golan, M., Massasa, E. E., Baydatch, S., Landen, S., Moor, A. E., et al. (2017) · Nature · doi:10.1038/nature21065 · Cited by 1,059
Highly Multiplexed Subcellular RNA Sequencing in Situ
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Yang, J. L., Ferrante, T. C., Terry, R., Jeanty, S. S. F., Li, C., Amamoto, R., et al. (2014) · Science · doi:10.1126/science.1250212 · Cited by 973
New stereological methods for counting neurons
West, M. J. (1993) · Neurobiology of Aging · doi:10.1016/0197-4580(93)90112-o · Cited by 940
Shah, S., Lubeck, E., Zhou, W., & Cai, L. (2016) · Neuron · doi:10.1016/j.neuron.2016.10.001 · Cited by 671
The Tumor Microenvironment in the Response to Immune Checkpoint Blockade Therapies
Petitprez, F., Meylan, M., de Reyniès, A., Sautès‐Fridman, C., & Fridman, W. H. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.00784 · Cited by 621
Brochu, G., Maler, L., & Hawkes, R. B. (1990) · The Journal of Comparative Neurology · doi:10.1002/cne.902910405 · Cited by 530
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Ferrante, T. C., Terry, R., Turczyk, B. M., Yang, J. L., Lee, H. S., Aach, J., et al. (2015) · Nature Protocols · doi:10.1038/nprot.2014.191 · Cited by 529
Climbing fiber responses evoked in vestibulocerebellum of rabbit from visual system.
Maekawa, K., & Simpson, J. L. (1973) · Journal of Neurophysiology · doi:10.1152/jn.1973.36.4.649 · Cited by 494
The diversity and disparity of the glial scar
Adams, K. L., & Gallo, V. (2017) · Nature Neuroscience · doi:10.1038/s41593-017-0033-9 · Cited by 448
Cerebellar modules operate at different frequencies
Zhou, H., Lin, Z., Voges, K., Ju, C., Gao, Z., Bosman, L. W. J., Ruigrok, T. J. H., Hoebeek, F. E., Zeeuw, C. I. D., & Schonewille, M. (2014) · eLife · doi:10.7554/elife.02536 · Cited by 352
Decoding Randomly Ordered DNA ArraysPreprint
Gunderson, K. L., Kruglyak, S., Graige, M. S., Garcia, F., Kermani, B. G., Zhao, C., Che, D., Dickinson, T. A., Wickham‐Garcia, E., Bierle, J., et al. (2004) · Genome Research · doi:10.1101/gr.2255804 · Cited by 328
Redefining the cerebellar cortex as an assembly of non-uniform Purkinje cell microcircuits
Cerminara, N. L., Lang, E. J., Sillitoe, R. V., & Apps, R. (2015) · Nature reviews. Neuroscience · doi:10.1038/nrn3886 · Cited by 315
Davis, M. Y., Trinh, K., Thomas, R. E., Yu, S., Germanos, A. A., Whitley, B. N., Sardi, S. P., Montine, T. J., & Pallanck, L. J. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005944 · Cited by 294
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
Kenney, A. M., & Kocsis, J. D. (1998) · Journal of Neuroscience · doi:10.1523/jneurosci.18-04-01318.1998 · Cited by 234
Distribution of the substance P receptor (NK-1 receptor) in the central nervous system
Maeno, H., Kiyama, H., & Tohyama, M. (1993) · Molecular Brain Research · doi:10.1016/0169-328x(93)90172-l · Cited by 202
A Single-Cell Transcriptional Atlas of the Developing Murine Cerebellum
Carter, R. A., Bihannic, L., Rosencrance, C. D., Hadley, J. L., Tong, Y., Phoenix, T. N., Natarajan, S., Easton, J. B., Northcott, P. A., & Gawad, C. (2018) · Current Biology · doi:10.1016/j.cub.2018.07.062 · Cited by 190
Gravel, C., & Hawkes, R. (1990) · The Journal of Comparative Neurology · doi:10.1002/cne.902910107 · Cited by 171
Sarna, J. R., Marzban, H., Watanabe, M., & Hawkes, R. B. (2006) · The Journal of Comparative Neurology · doi:10.1002/cne.20912 · Cited by 167
Miner, L. H., Schroeter, S., Blakely, R., & Sesack, S. R. (2000) · The Journal of Comparative Neurology · doi:10.1002/1096-9861(20001113)427:2 · Cited by 148
Shah, S., Lubeck, E., Zhou, W., & Cai, L. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.008 · Cited by 147
Dendritic Control of Spontaneous Bursting in Cerebellar Purkinje Cells
Womack, M. D., & Khodakhah, K. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.0290-04.2004 · Cited by 145
Systematic Regional Variations in Purkinje Cell Spiking Patterns
Xiao, J., Cerminara, N. L., Kotsurovskyy, Y., Aoki, H., Burroughs, A., Wise, A. K., Luo, Y., Marshall, S. P., Sugihara, I., Apps, R., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105633 · Cited by 103
Bravo González‐Blas, C., Quan, X., Duran‐Romaña, R., Taskiran, I. I., Koldere, D., Davie, K., Christiaens, V., Makhzami, S., Hulselmans, G., de Waegeneer, M., et al. (2020) · Molecular Systems Biology · doi:10.15252/msb.20209438 · Cited by 88
Lobule‐specific membrane excitability of cerebellar Purkinje cells
Kim, C., Oh, S. H., Lee, J. H., Chang, S. O., Kim, J., & Kim, S. J. (2011) · The Journal of Physiology · doi:10.1113/jphysiol.2011.221846 · Cited by 81
Dlk1 Promotes a Fast Motor Neuron Biophysical Signature Required for Peak Force Execution
Müller, D., Cherukuri, P., Henningfeld, K. A., Poh, C. H., Wittler, L., Grote, P., Schlüter, O. M., Schmidt, J. V., Laborda, J., Bauer, S. R., et al. (2014) · Science · doi:10.1126/science.1246448 · Cited by 78
Robinson, G. A. (1994) · Molecular Brain Research · doi:10.1016/0169-328x(94)90116-3 · Cited by 77
Focal brain injury induces multiple immediate early genes encoding zinc finger transcription factors
Honkaniemi, J., Sagar, S. M., Pyykönen, I., Hicks, K. J., & Sharp, F. R. (1995) · Molecular Brain Research · doi:10.1016/0169-328x(94)00200-x · Cited by 58
Roberts, M. T., & Trussell, L. O. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00312.2010 · Cited by 57
Gene Deregulation and Underlying Mechanisms in Spinocerebellar Ataxias With Polyglutamine Expansion
Niewiadomska-Cimicka, A., Hache, A., & Trottier, Y. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00571 · Cited by 42
Chung, C., Elrick, M. J., Dell’Orco, J., Qin, Z. S., Sundaram, S. K., Chinnaiyan, A. M., Shakkottai, V. G., & Lieberman, A. P. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1006042 · Cited by 31
WYLIE, D. R. W., Brown, M., Winship, I. R., Crowder, N. A., & Todd, K. G. (2003) · The Journal of Comparative Neurology · doi:10.1002/cne.10857 · Cited by 30
Demilly, A., Reeber, S. L., Gebre, S. A., & Sillitoe, R. V. (2010) · The Cerebellum · doi:10.1007/s12311-010-0156-y · Cited by 28
Microcircuits of the Dorsal Cochlear Nucleus
Trussell, L. O., & Oertel, D. (2018) · Springer handbook of auditory research · doi:10.1007/978-3-319-71798-2_4 · Cited by 26
González‐Blas, C. B., Quan, X., Duran‐Romaña, R., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.19.882381 · Cited by 17
The presence of rRNA sequences in polyadenylated RNA and its potential functions
Kong, Q., Stockinger, M., Chang, Y., Tashiro, H., & Lin, C. G. (2008) · Biotechnology Journal · doi:10.1002/biot.200800122 · Cited by 14
Decoding the body language of immunity: Tackling the immune system at the organism level
Chevrier, N. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.10.010 · Cited by 13
Storer, P. D., & Jones, K. J. (2003) · The Journal of Comparative Neurology · doi:10.1002/cne.10623 · Cited by 13
broadchenf/Slideseq: Slide-seq 2019 Archive
samrodriques, & linlinbroad (2019) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.2571615 · Cited by 1
broadchenf/Slideseq: Slide-seq 2019 Archive
Samrodriques, & Linlinbroad (2019) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.2571614 · Cited by 1
Cited by
Sorted by citations
Integrated analysis of multimodal single-cell data
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zagar, M., et al. (2020) · doi:10.1101/2020.10.12.335331 · Cited by 15,508
Efremova, M., Vento-Tormo, M., Teichmann, S. A., & Vento-Tormo, R. (2020) · Nature Protocols · doi:10.1038/s41596-020-0292-x · Cited by 3,449
NicheNet: Modeling intercellular communication by linking ligands to target genes
Browaeys, R., Saelens, W., & Saeys, Y. (2020) · Nature Methods · doi:10.1038/s41592-019-0667-5 · Cited by 2,192
RNA sequencing: the teenage years
Stark, R., Grzelak, M., & Hadfield, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0150-2 · Cited by 2,041
Fibrosis: from mechanisms to medicines
Henderson, N. C., Rieder, F., & Wynn, T. A. (2020) · Nature · doi:10.1038/s41586-020-2938-9 · Cited by 1,868
Metadata
- Authors
- Rodriques, S. G., Stickels, R. R., Goeva, A., Martin, C. A., Murray, E., Vanderburg, C. R., Welch, J., Chen, L. M., Chen, F., & Macosko, E. Z.
- Affiliations
- Broad Institute (US)
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
- Corresponding author
- Chen, Fei
- Macosko, Evan Z.
- ORCID
- Venue
- Science
- Published
- 2019-03-29
- Volume
- 363
- Issue
- 6434
- Pages
- 1463-1467
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6927209
- OpenAlex
- W2915848182
- Cited by
- 2,424
- References
- 49
- Citations by year
- 2026: 385 · 2025: 391 · 2024: 415 · 2023: 319 · 2022: 300 · 2021: 318 · 2020: 212 · 2019: 80
- FWCI
- 75.91
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH Office of the Director (DP2 AG058488-01, 1DP5OD024583)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Keywords
- Slide-seq, spatial transcriptomics, cerebellum, hippocampus, traumatic brain injury, single-cell RNA sequencing, mouse model
- MeSH terms
- Brain Injuries, Traumatic, Animals, Cerebellum, Disease Models, Animal, Frozen Sections, Gene Expression Regulation, Hippocampus, Purkinje Cells, RNA, Messenger, Transcription, Genetic, Sequence Analysis, RNA, Cell Size, Mice, Genome-Wide Association Study, Single-Cell Analysis, High-Throughput Nucleotide Sequencing
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
