Transcriptomic mapping uncovers Purkinje neuron plasticity driving learning

被引:24
作者
Chen, Xiaoying [1 ,8 ]
Du, Yanhua [2 ]
Broussard, Gerard Joey [3 ]
Kislin, Mikhail [3 ]
Yuede, Carla M. [4 ]
Zhang, Shuwei [2 ]
Dietmann, Sabine [5 ,6 ]
Gabel, Harrison
Zhao, Guoyan [1 ]
Wang, Samuel S. -H. [3 ]
Zhang, Xiaoqing [2 ]
Bonni, Azad [1 ,7 ]
机构
[1] Washington Univ, Sch Med, Dept Neurosci, St Louis, MO 63108 USA
[2] Tongji Univ, Shanghai East Hosp, Sch Med, Shanghai, Peoples R China
[3] Princeton Univ, Neurosci Inst, Washington Rd, Princeton, NJ 08544 USA
[4] Washington Univ, Sch Med, Dept Neurol, St Louis, MO 63110 USA
[5] Washington Univ, Sch Med, Dev Biol, St Louis, MO USA
[6] Washington Univ, Sch Med, Inst Informat, St Louis, MO USA
[7] Roche Innovat Ctr Basel, Neurosci & Rare Dis, Roche Pharma Res & Early Dev pRED, Basel, Switzerland
[8] Washington Univ, Dept Neurol, Hope Ctr Neurol Disorders, Knight Alzheimers Dis Res Ctr,Sch Med, St Louis, MO USA
基金
中国国家自然科学基金;
关键词
CELL DEGENERATION; EXPRESSION;
D O I
10.1038/s41586-022-04711-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cellular diversification is critical for specialized functions of the brain including learning and memory(1). Single-cell RNA sequencing facilitates transcriptomic profiling of distinct major types of neuron(2-4), but the divergence of transcriptomic profiles within a neuronal population and their link to function remain poorly understood. Here we isolate nuclei tagged(5) in specific cell types followed by single-nucleus RNA sequencing to profile Purkinje neurons and map their responsesto motor activity and learning. We find that two major subpopulations of Purkinje neurons, identified by expression of the genes Aldoc and Plcb4, bear distinct transcriptomic features. Plcb4(+), but not Aldoe , Purkinje neurons exhibit robust plasticity of gene expression in mice subjected to sensorimotor and learning experience. In vivo calcium imaging and optogenetic perturbation reveal that Plcb4(+) Purkinje neurons have a crucial role in associative learning. Integrating single-nucleus RNA sequencing datasets with weighted gene co-expression network analysis uncovers a learning gene module that includes components of FGFR2 signalling in Plcb4(+) Purkinje neurons. Knockout of Fgfr2 in Plcb4(+) Purkinje neurons in mice using CRISPR disrupts motor learning. Our findings define how diversification of Purkinje neurons is linked to their responses in motor learning and provide a foundation for understanding their differential vulnerability to neurological disorders.
引用
收藏
页码:722 / +
页数:25
相关论文
共 32 条
  • [1] Functional Specialization of Mouse Higher Visual Cortical Areas
    Andermann, Mark L.
    Kerlin, Aaron M.
    Roumis, Demetris K.
    Glickfeld, Lindsey L.
    Reid, R. Clay
    [J]. NEURON, 2011, 72 (06) : 1025 - 1039
  • [2] Integrating single-cell transcriptomic data across different conditions, technologies, and species
    Butler, Andrew
    Hoffman, Paul
    Smibert, Peter
    Papalexi, Efthymia
    Satija, Rahul
    [J]. NATURE BIOTECHNOLOGY, 2018, 36 (05) : 411 - +
  • [3] High-performance calcium sensors for imaging activity in neuronal populations and microcompartments
    Dana, Hod
    Sun, Yi
    Mohar, Boaz
    Hulse, Brad K.
    Kerlin, Aaron M.
    Hasseman, Jeremy P.
    Tsegaye, Getahun
    Tsang, Arthur
    Wong, Allan
    Patel, Ronak
    Macklin, John J.
    Chen, Yang
    Konnerth, Arthur
    Jayaraman, Vivek
    Looger, Loren L.
    Schreiter, Eric R.
    Svoboda, Karel
    Kim, Douglas S.
    [J]. NATURE METHODS, 2019, 16 (07) : 649 - +
  • [4] Bidirectional learning in upbound and downbound microzones of the cerebellum
    De Zeeuw, Chris I.
    [J]. NATURE REVIEWS NEUROSCIENCE, 2021, 22 (02) : 92 - 110
  • [5] Cerebellar disruption impairs working memory during evidence accumulation
    Deverett, Ben
    Kislin, Mikhail
    Tank, David W.
    Wang, Samuel S-H
    [J]. NATURE COMMUNICATIONS, 2019, 10 (1)
  • [6] Selective Optogenetic Control of Purkinje Cells in Monkey Cerebellum
    El-Shamayleh, Yasmine
    Kojima, Yoshiko
    Soetedjo, Robijanto
    Horwitz, Gregory D.
    [J]. NEURON, 2017, 95 (01) : 51 - +
  • [7] CaImAn an open source tool for scalable calcium imaging data analysis
    Giovannucci, Andrea
    Friedrich, Johannes
    Gunn, Pat
    Kalfon, Jeremie
    Brown, Brandon L.
    Koay, Sue Ann
    Taxidis, Jiannis
    Najafi, Farzaneh
    Gauthier, Jeffrey L.
    Zhou, Pengcheng
    Khakh, Baljit S.
    Tank, David W.
    Chklovskii, Dmitri B.
    Pnevmatikakis, Eftychios A.
    [J]. ELIFE, 2019, 8
  • [8] Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
    Hafemeister, Christoph
    Satija, Rahul
    [J]. GENOME BIOLOGY, 2019, 20 (01)
  • [9] CEREBELLAR CELL DEGENERATION IN THE LEANER MUTANT MOUSE
    HERRUP, K
    WILCZYNSKI, SL
    [J]. NEUROSCIENCE, 1982, 7 (09) : 2185 - 2196
  • [10] Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex
    Hrvatin, Sinisa
    Hochbaum, Daniel R.
    Nagy, M. Aurel
    Cicconet, Marcelo
    Robertson, Keiramarie
    Cheadle, Lucas
    Zilionis, Rapolas
    Ratner, Alex
    Borges-Monroy, Rebeca
    Klein, Allon M.
    Sabatini, Bernardo L.
    Greenberg, Michael E.
    [J]. NATURE NEUROSCIENCE, 2018, 21 (01) : 120 - +