CoChat
Sign Up
Cited by 317

Molecular atlas of the adult mouse brain

Ortiz, Cantin, Navarro, Jose Fernandez, Jurek, Aleksandra, Märtin, Antje, Lundeberg, Joakim, Meletis, Konstantinos·2020·Science Advances
DOI 10.1126/sciadv.abb3446PMC PMC7319762

Published version of a preprint

Open this paper in CoChat — free account

Abstract

Whole-brain spatial transcriptomics redefines the neuroanatomical classification of the adult mouse brain.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/sciadv.abb3446

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Entorhinal cortex-specific subtypes clustered separately from neocortical subtypes for the same layers and were often marked by RELN, TOX3 and GPC5, containing lateral (L2 RELN+GPC5+) and medial (L2 TOX3+POSTN+) EC subtypes.

    “EC-specific subtypes that clustered separately from neocortical subtypes for the same layers were often marked by expression of RELN, TOX3 and GPC5, and contained subtypes from both the lateral (L2 RELN+GPC5+) and medial (L2 TOX3+POSTN+) EC41–43”

    From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [42]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 40

  1. [1]Crick F., Jones E., Backwardness of human neuroanatomy. Nature 361, 109– 110 (1993). 8421513
  2. [2]Denk W., Briggman K. L., Helmstaedter M., Structural neurobiology: Missing link to a mechanistic understanding of neural computation. Nat. Rev. Neurosci. 13, 351– 358 (2012). 22353782
  3. [3]Swanson L. W., Lichtman J. W., From Cajal to Connectome and beyond. Annu. Rev. Neurosci. 39, 197– 216 (2016). 27442070
  4. [4]Zeng H., Mesoscale connectomics. Curr. Opin. Neurobiol. 50, 154– 162 (2018). 29579713 PMC6027632
  5. [5]L. W. Swanson, A history of neuroanatomical mapping, in Brain Mapping: The Systems, A. W. Toga, J. C. Mazziotta, Eds. (Academic Press, 2000), pp. 77–109.
  6. [6]Zilles K., Amunts K., Centenary of Brodmann’s map—Conception and fate. Nat. Rev. Neurosci. 11, 139– 145 (2010). 20046193
  7. [7]Oh S. W., Harris J. A., Ng L., Winslow B., Cain N., Mihalas S., Wang Q., Lau C., Kuan L., Henry A. M., Mortrud M. T., Ouellette B., Nguyen T. N., Sorensen S. A., Slaughterbeck C. R., Wakeman W., Li Y., Feng D., Ho A., Nicholas E., Hirokawa K. E., Bohn P., Joines K. M., Peng H., Hawrylycz M. J., Phillips J. W., Hohmann J. G., Wohnoutka P., Gerfen C. R., Koch C., Bernard A., Dang C., Jones A. R., Zeng H., A mesoscale connectome of the mouse brain. Nature 508, 207– 214 (2014). 24695228 PMC5102064
  8. [8]Schmidt H., Gour A., Straehle J., Boergens K. M., Brecht M., Helmstaedter M., Axonal synapse sorting in medial entorhinal cortex. Nature 549, 469– 475 (2017). 28959971
  9. [9]Hawrylycz M. J., Lein E. S., Guillozet-Bongaarts A. L., Shen E. H., Ng L., Miller J. A., van de Lagemaat L. N., Smith K. A., Ebbert A., Riley Z. L., Abajian C., Beckmann C. F., Bernard A., Bertagnolli D., Boe A. F., Cartagena P. M., Chakravarty M. M., Chapin M., Chong J., Dalley R. A., Daly B. D., Dang C., Datta S., Dee N., Dolbeare T. A., Faber V., Feng D., Fowler D. R., Goldy J., Gregor B. W., Haradon Z., Haynor D. R., Hohmann J. G., Horvath S., Howard R. E., Jeromin A., Jochim J. M., Kinnunen M., Lau C., Lazarz E. T., Lee C., Lemon T. A., Li L., Li Y., Morris J. A., Overly C. C., Parker P. D., Parry S. E., Reding M., Royall J. J., Schulkin J., Sequeira P. A., Slaughterbeck C. R., Smith S. C., Sodt A. J., Sunkin S. M., Swanson B. E., Vawter M. P., Williams D., Wohnoutka P., Zielke H. R., Geschwind D. H., Hof P. R., Smith S. M., Koch C., Grant S. G. N., Jones A. R., An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391– 399 (2012). 22996553 PMC4243026
  10. [13]Bota M., Dong H.-W., Swanson L. W., From gene networks to brain networks. Nat. Neurosci. 6, 795– 799 (2003). 12886225
  11. [14]Kim C. K., Adhikari A., Deisseroth K., Integration of optogenetics with complementary methodologies in systems neuroscience. Nat. Rev. Neurosci. 18, 222– 235 (2017). 28303019 PMC5708544
  12. [15]Luo L., Callaway E. M., Svoboda K., Genetic dissection of neural circuits: A decade of progress. Neuron 98, 256– 281 (2018). 29673479 PMC5912347
  13. [16]Belgard T. G., Marques A. C., Oliver P. L., Abaan H. O., Sirey T. M., Hoerder-Suabedissen A., García-Moreno F., Molnár Z., Margulies E. H., Ponting C. P., A transcriptomic atlas of mouse neocortical layers. Neuron 71, 605– 616 (2011). 21867878 PMC3163272
  14. [19]Fürth D., Vaissière T., Tzortzi O., Xuan Y., Märtin A., Lazaridis I., Spigolon G., Fisone G., Tomer R., Deisseroth K., Carlén M., Miller C. A., Rumbaugh G., Meletis K., An interactive framework for whole-brain maps at cellular resolution. Nat. Neurosci. 21, 139– 149 (2018). 29203898 PMC5994773
  15. [20]Cardoso J. F., Souloumiac A., Blind beamforming for non-Gaussian signals. IEE Proc. F 140, 362– 370 (1993).
  16. [23]Voorn P., Vanderschuren L. J. M. J., Groenewegen H. J., Robbins T. W., Pennartz C. M. A., Putting a spin on the dorsal–ventral divide of the striatum. Trends Neurosci. 27, 468– 474 (2004). 15271494
  17. [25]Ashburner M., Ball C. A., Blake J. A., Botstein D., Butler H., Cherry J. M., Davis A. P., Dolinski K., Dwight S. S., Eppig J. T., Harris M. A., Hill D. P., Issel-Tarver L., Kasarskis A., Lewis S., Matese J. C., Richardson J. E., Ringwald M., Rubin G. M., Sherlock G., Gene Ontology: Tool for the unification of biology. Nat. Genet. 25, 25– 29 (2000). 10802651 PMC3037419
  18. [26]Narayanan R. T., Udvary D., Oberlaender M., Narayanan R. T., Udvary D., Oberlaender M., Cell type-specific structural organization of the six layers in rat barrel cortex. Front. Neuroanat. 11, 91 (2017). 29081739 PMC5645532
  19. [27]Carlén M., What constitutes the prefrontal cortex? Science 358, 478– 482 (2017). 29074767
  20. [28]Harris J. A., Mihalas S., Hirokawa K. E., Whitesell J. D., Choi H., Bernard A., Bohn P., Caldejon S., Casal L., Cho A., Feiner A., Feng D., Gaudreault N., Gerfen C. R., Graddis N., Groblewski P. A., Henry A. M., Ho A., Howard R., Knox J. E., Kuan L., Kuang X., Lecoq J., Lesnar P., Li Y., Luviano J., Conoughey S. M., Mortrud M. T., Naeemi M., Ng L., Oh S. W., Ouellette B., Shen E., Sorensen S. A., Wakeman W., Wang Q., Wang Y., Williford A., Phillips J. W., Jones A. R., Koch C., Zeng H., Hierarchical organization of cortical and thalamic connectivity. Nature 575, 195– 202 (2019). 31666704 PMC8433044
  21. [29]Sylwestrak E. L., Rajasethupathy P., Wright M. A., Jaffe A., Deisseroth K., Multiplexed intact-tissue transcriptional analysis at cellular resolution. Cell 164, 792– 804 (2016). 26871636 PMC4775740
  22. [30]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., Nanoscale imaging of RNA with expansion microscopy. Nat. Methods 13, 679– 684 (2016). 27376770 PMC4965288
  23. [32]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., Peters D. T., Turczyk B. M., Marblestone A. H., Inverso S. A., Bernard A., Mali P., Rios X., Aach J., Church G. M., Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360– 1363 (2014). 24578530 PMC4140943
  24. [33]Lubeck E., Coskun A. F., Zhiyentayev T., Ahmad M., Cai L., Single-cell in situ RNA profiling by sequential hybridization. Nat. Methods 11, 360– 361 (2014). 24681720 PMC4085791
  25. [34]Chen K. H., Boettiger A. N., Moffitt J. R., Wang S., Zhuang X., Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015). 25858977 PMC4662681
  26. [35]Eng C.-H. L., Lawson M., Zhu Q., Dries R., Koulena N., Takei Y., Yun J., Cronin C., Karp C., Yuan G.-C., Cai L., Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 568, 235– 239 (2019). 30911168 PMC6544023
  27. [36]Shah S., Lubeck E., Zhou W., Cai L., In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus. Neuron 92, 342– 357 (2016). 27764670 PMC5087994
  28. [37]Phillips J. W., Schulmann A., Hara E., Winnubst J., Liu C., Valakh V., Wang L., Shields B. C., Korff W., Chandrashekar J., Lemire A. L., Mensh B., Dudman J. T., Nelson S. B., Hantman A. W., A repeated molecular architecture across thalamic pathways. Nat. Neurosci. 22, 1925– 1935 (2019). 31527803 PMC6819258
  29. [38]Vickovic S., Eraslan G., Salmén F., Klughammer J., Stenbeck L., Schapiro D., Äijö T., Bonneau R., Bergenstråhle L., Navarro J. F., Gould J., Griffin G. K., Borg Å., Ronaghi M., Frisén J., Lundeberg J., Regev A., Ståhl P. L., High-definition spatial transcriptomics for in situ tissue profiling. Nat. Methods 16, 987– 990 (2019). 31501547 PMC6765407
  30. [39]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., Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463– 1467 (2019). 30923225 PMC6927209
  31. [40]Zapala M. A., Hovatta I., Ellison J. A., Wodicka L., Del Rio J. A., Tennant R., Tynan W., Broide R. S., Helton R., Stoveken B. S., Winrow C., Lockhart D. J., Reilly J. F., Young W. G., Bloom F. E., Lockhart D. J., Barlow C., Adult mouse brain gene expression patterns bear an embryologic imprint. Proc. Natl. Acad. Sci. U.S.A. 102, 10357– 10362 (2005). 16002470 PMC1173363
  32. [41]Nowakowski T. J., Bhaduri A., Pollen A. A., Alvarado B., Mostajo-Radji M. A., Lullo E. D., Haeussler M., Sandoval-Espinosa C., Liu S. J., Velmeshev D., Ounadjela J. R., Shuga J., Wang X., Lim D. A., West J. A., Leyrat A. A., Kent W. J., Kriegstein A. R., Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex. Science 358, 1318– 1323 (2017). 29217575 PMC5991609
  33. [43]Jemt A., Salmén F., Lundmark A., Mollbrink A., Navarro J. F., Ståhl P. L., Yucel-Lindberg T., Lundeberg J., An automated approach to prepare tissue-derived spatially barcoded RNA-sequencing libraries. Sci. Rep. 6, 37137 (2016). 27849009 PMC5111054
  34. [44]Lundin S., Stranneheim H., Pettersson E., Klevebring D., Lundeberg J., Increased throughput by parallelization of library preparation for massive sequencing. PLOS ONE 5, e10029 (2010). 20386591 PMC2850305
  35. [45]Schindelin J., Rueden C. T., Hiner M. C., Eliceiri K. W., The ImageJ ecosystem: An open platform for biomedical image analysis. Mol. Reprod. Dev. 82, 518– 529 (2015). 26153368 PMC5428984
  36. [46]Navarro J. F., Sjöstrand J., Salmén F., Lundeberg J., Ståhl P. L., ST Pipeline: An automated pipeline for spatial mapping of unique transcripts. Bioinformatics 33, 2591– 2593 (2017). 28398467
  37. [47]Lun A. T. L., McCarthy D. J., Marioni J. C., A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. F1000Res. 5, 2122 (2016). 27909575 PMC5112579
  38. [51]Waltman L., van Eck N. J., A smart local moving algorithm for large-scale modularity-based community detection. Eur. Phys. J. B 86, 471 (2013).
  39. [52]Bohland J. W., Bokil H., Pathak S. D., Lee C.-K., Ng L., Lau C., Kuan C., Hawrylycz M., Mitra P. P., Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy. Methods 50, 105– 112 (2010). 19733241
  40. [53]Becht E., Innes L. M., Healy J., Dutertre C.-A., Kwok I. W. H., Ng L. G., Ginhoux F., Newell E. W., Dimensionality reduction for visualizing single-cell data using UMAP. Nat. Biotechnol. 37, 38– 44 (2019). 30531897

Cited by

Sorted by citations

Authors
Ortiz, C., Navarro, J. F., Jurek, A., Märtin, A., Lundeberg, J., & Meletis, K.
Affiliations
  • Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
  • Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
ORCID
Venue
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Published
2020-06-26
Volume
6
Issue
26
ISSN
2375-2548
DOI
10.1126/sciadv.abb3446
PMC
PMC7319762
Cited by
317
References
10
Language
en
Funders
  • Swedish Foundation for Strategic Research (FFL12-0006, SB16-0014)
  • Hjärnfonden (FO2018-0213)
  • Knut och Alice Wallenbergs Stiftelse (Spatial Brain KAW 2015.0296)
  • Swedish Research Council for Health, Working Life and Welfare (VR 2017-01457)

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