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      Morphological diversity of single neurons in molecularly defined cell types

      research-article
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      Nature
      Nature Publishing Group UK
      Cellular neuroscience, Neural circuits

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          Abstract

          Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types 1, 2 , yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.

          Abstract

          Sparse labelling and whole-brain imaging are used to reconstruct and classify brain-wide complete morphologies of 1,741 individual neurons in the mouse brain, revealing a dependence on both brain region and transcriptomic profile.

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Normalized cuts and image segmentation

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              UMAP: Uniform Manifold Approximation and Projection

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                Author and article information

                Contributors
                h@braintell.org
                hongkuiz@alleninstitute.org
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                6 October 2021
                6 October 2021
                2021
                : 598
                : 7879
                : 174-181
                Affiliations
                [1 ]GRID grid.417881.3, Allen Institute for Brain Science, ; Seattle, WA USA
                [2 ]GRID grid.263826.b, ISNI 0000 0004 1761 0489, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, , Southeast University, ; Nanjing, China
                [3 ]GRID grid.263826.b, ISNI 0000 0004 1761 0489, Ministry of Education Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, , Southeast University, ; Nanjing, China
                [4 ]GRID grid.268099.c, ISNI 0000 0001 0348 3990, School of Optometry and Ophthalmology, , Wenzhou Medical University, ; Wenzhou, China
                [5 ]GRID grid.39436.3b, ISNI 0000 0001 2323 5732, School of Computer Engineering and Science, , Shanghai University, ; Shanghai, China
                [6 ]GRID grid.252245.6, ISNI 0000 0001 0085 4987, Key Laboratory of Intelligent Computation and Signal Processing, Ministry of Education, , Anhui University, ; Hefei, China
                [7 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, , Huazhong University of Science and Technology, ; Wuhan, China
                [8 ]GRID grid.263761.7, ISNI 0000 0001 0198 0694, HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, ; Suzhou, China
                [9 ]Tencent Jarvis Lab, Shenzhen, China
                [10 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, , University of California, Los Angeles, ; Los Angeles, CA USA
                [11 ]GRID grid.225279.9, ISNI 0000 0004 0387 3667, Cold Spring Harbor Laboratory, ; Cold Spring Harbor, NY USA
                [12 ]GRID grid.26009.3d, ISNI 0000 0004 1936 7961, Department of Neurobiology, , Duke University School of Medicine, ; Durham, NC USA
                [13 ]GRID grid.428986.9, ISNI 0000 0001 0373 6302, School of Biomedical Engineering, , Hainan University, ; Haikou, China
                [14 ]GRID grid.511032.4, Present Address: Cajal Neuroscience, ; Seattle, WA USA
                Author information
                http://orcid.org/0000-0002-3478-3942
                http://orcid.org/0000-0003-2515-6602
                http://orcid.org/0000-0002-2129-5253
                http://orcid.org/0000-0001-5519-6248
                http://orcid.org/0000-0002-2277-263X
                http://orcid.org/0000-0002-5877-4813
                http://orcid.org/0000-0002-9361-5607
                http://orcid.org/0000-0002-3775-1583
                http://orcid.org/0000-0003-0421-8050
                http://orcid.org/0000-0002-6861-4506
                http://orcid.org/0000-0001-9050-4496
                http://orcid.org/0000-0003-0592-028X
                http://orcid.org/0000-0002-5741-8024
                http://orcid.org/0000-0003-3705-7935
                http://orcid.org/0000-0001-8926-7710
                http://orcid.org/0000-0002-9179-4787
                http://orcid.org/0000-0001-6482-8067
                http://orcid.org/0000-0002-0326-5878
                Article
                3941
                10.1038/s41586-021-03941-1
                8494643
                34616072
                3448d094-c5b0-4a9f-934c-adc0288fc786
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 September 2020
                : 24 August 2021
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                © The Author(s), under exclusive licence to Springer Nature Limited 2021

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                cellular neuroscience,neural circuits
                Uncategorized
                cellular neuroscience, neural circuits

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