Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease

被引:96
作者
Piwecka, Monika [1 ]
Rajewsky, Nikolaus [2 ]
Rybak-Wolf, Agnieszka [2 ]
机构
[1] Polish Acad Sci, Inst Bioorgan Chem, Poznan, Poland
[2] Max Delbrueck Ctr Mol Med, Berlin Inst Med Syst Biol BIMSB, Berlin, Germany
关键词
NUCLEUS RNA-SEQ; GENOME-WIDE EXPRESSION; ALZHEIMERS-DISEASE; GENE-EXPRESSION; MOLECULAR DIVERSITY; SEQUENCING DATA; MOUSE; MICROGLIA; TAXONOMY; DYNAMICS;
D O I
10.1038/s41582-023-00809-y
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject - the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies.
引用
收藏
页码:346 / 362
页数:17
相关论文
共 213 条
[1]   Single-nucleus RNA-seq identifies Huntington disease astrocyte states [J].
Al-Dalahmah, Osama ;
Sosunov, Alexander A. ;
Shaik, A. ;
Ofori, Kenneth ;
Liu, Yang ;
Vonsattel, Jean Paul ;
Adorjan, Istvan ;
Menon, Vilas ;
Goldman, James E. .
ACTA NEUROPATHOLOGICA COMMUNICATIONS, 2020, 8 (01)
[2]   FIN-Seq: transcriptional profiling of specific cell types from frozen archived tissue of the human central nervous system [J].
Amamoto, Ryoji ;
Zuccaro, Emanuela ;
Curry, Nathan C. ;
Khurana, Sonia ;
Chen, Hsu-Hsin ;
Cepko, Constance L. ;
Arlotta, Paola .
NUCLEIC ACIDS RESEARCH, 2020, 48 (01)
[3]   Transcriptome and epigenome landscape of human cortical development modeled in organoids [J].
Amiri, Anahita ;
Coppola, Gianfilippo ;
Scuderi, Soraya ;
Wu, Feinan ;
Roychowdhury, Tanmoy ;
Liu, Fuchen ;
Pochareddy, Sirisha ;
Shin, Yurae ;
Safi, Alexias ;
Song, Lingyun ;
Zhu, Ying ;
Sousa, Andre M. M. ;
Gerstein, Mark ;
Crawford, Gregory E. ;
Sestan, Nenad ;
Abyzov, Alexej ;
Vaccarino, Flora M. .
SCIENCE, 2018, 362 (6420) :1268-+
[4]   A Single-Cell RNA Sequencing Study Reveals Cellular and Molecular Dynamics of the Hippocampal Neurogenic Niche [J].
Artegiani, Benedetta ;
Lyubimova, Anna ;
Muraro, Mauro ;
van Es, Johan H. ;
van Oudenaarden, Alexander ;
Clevers, Hans .
CELL REPORTS, 2017, 21 (11) :3271-3284
[5]   SCnorm: robust normalization of single-cell RNA-seq data [J].
Bacher, Rhonda ;
Chu, Li-Fang ;
Leng, Ning ;
Gasch, Audrey P. ;
Thomson, James A. ;
Stewart, Ron M. ;
Newton, Michael ;
Kendziorski, Christina .
NATURE METHODS, 2017, 14 (06) :584-+
[6]   Neuroimmune crosstalk and evolving pharmacotherapies in neurodegenerative diseases [J].
Baidya, Falguni ;
Bohra, Mariya ;
Datta, Aishika ;
Sarmah, Deepaneeta ;
Shah, Birva ;
Jagtap, Priya ;
Raut, Swapnil ;
Sarkar, Ankan ;
Singh, Upasna ;
Kalia, Kiran ;
Borah, Anupom ;
Wang, Xin ;
Dave, Kunjan R. ;
Yavagal, Dileep R. ;
Bhattacharya, Pallab .
IMMUNOLOGY, 2021, 162 (02) :160-178
[7]   Comparative cellular analysis of motor cortex in human, marmoset and mouse [J].
Bakken, Trygve E. ;
Jorstad, Nikolas L. ;
Hu, Qiwen ;
Lake, Blue B. ;
Tian, Wei ;
Kalmbach, Brian E. ;
Crow, Megan ;
Hodge, Rebecca D. ;
Krienen, Fenna M. ;
Sorensen, Staci A. ;
Eggermont, Jeroen ;
Yao, Zizhen ;
Aevermann, Brian D. ;
Aldridge, Andrew I. ;
Bartlett, Anna ;
Bertagnolli, Darren ;
Casper, Tamara ;
Castanon, Rosa G. ;
Crichton, Kirsten ;
Daigle, Tanya L. ;
Dalley, Rachel ;
Dee, Nick ;
Dembrow, Nikolai ;
Diep, Dinh ;
Ding, Song-Lin ;
Dong, Weixiu ;
Fang, Rongxin ;
Fischer, Stephan ;
Goldman, Melissa ;
Goldy, Jeff ;
Graybuck, Lucas T. ;
Herb, Brian R. ;
Hou, Xiaomeng ;
Kancherla, Jayaram ;
Kroll, Matthew ;
Lathia, Kanan ;
van Lew, Baldur ;
Li, Yang Eric ;
Liu, Christine S. ;
Liu, Hanqing ;
Lucero, Jacinta D. ;
Mahurkar, Anup ;
McMillen, Delissa ;
Miller, Jeremy A. ;
Moussa, Marmar ;
Nery, Joseph R. ;
Nicovich, Philip R. ;
Niu, Sheng-Yong ;
Orvis, Joshua ;
Osteen, Julia K. .
NATURE, 2021, 598 (7879) :111-+
[8]   Single-nucleus and single-cell transcriptomes compared in matched cortical cell types [J].
Bakken, Trygve E. ;
Hodge, Rebecca D. ;
Miller, Jeremy A. ;
Yao, Zizhen ;
Thuc Nghi Nguyen ;
Aevermann, Brian ;
Barkan, Eliza ;
Bertagnolli, Darren ;
Casper, Tamara ;
Dee, Nick ;
Garren, Emma ;
Goldy, Jeff ;
Graybuck, Lucas T. ;
Kroll, Matthew ;
Lasken, Roger S. ;
Lathia, Kanan ;
Parry, Sheana ;
Rimorin, Christine ;
Scheuermann, Richard H. ;
Schork, Nicholas J. ;
Shehata, Soraya I. ;
Tieu, Michael ;
Phillips, John W. ;
Bernard, Amy ;
Smith, Kimberly A. ;
Zeng, Hongkui ;
Lein, Ed S. ;
Tasic, Bosiljka .
PLOS ONE, 2018, 13 (12)
[9]   Identification of region-specific astrocyte subtypes at single cell resolution [J].
Batiuk, Mykhailo Y. ;
Martirosyan, Araks ;
Wahis, Jerome ;
de Vin, Filip ;
Marneffe, Catherine ;
Kusserow, Carola ;
Koeppen, Jordan ;
Viana, Joao Filipe ;
Oliveira, Joao Filipe ;
Voet, Thierry ;
Ponting, Chris P. ;
Belgard, T. Grant ;
Holt, Matthew G. .
NATURE COMMUNICATIONS, 2020, 11 (01)
[10]   Dimensionality reduction for visualizing single-cell data using UMAP [J].
Becht, Etienne ;
McInnes, Leland ;
Healy, John ;
Dutertre, Charles-Antoine ;
Kwok, Immanuel W. H. ;
Ng, Lai Guan ;
Ginhoux, Florent ;
Newell, Evan W. .
NATURE BIOTECHNOLOGY, 2019, 37 (01) :38-+