Integrative analysis of in vivo recording with single-cell RNA-seq data reveals molecular properties of light-sensitive neurons in mouse V1
Jianwei Liu1,3, Mengdi Wang1, Le Sun1,3, Na Clara Pan1, Changjiang Zhang1,3, Junjing Zhang2, Zhentao Zuo1, Sheng He1, Qian Wu2,5(), Xiaoqun Wang1,3,4,6()
1. State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Brain-Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 2. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China 3. University of Chinese Academy of Sciences, Beijing 100049, China 4. Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China 5. IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China 6. Advanced Innovation Center for Human Brain Protection, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100069, China
Vision formation is classically based on projections from retinal ganglion cells (RGC) to the lateral geniculate nucleus (LGN) and the primary visual cortex (V1). Neurons in the mouse V1 are tuned to light stimuli. Although the cellular information of the retina and the LGN has been widely studied, the transcriptome profiles of single light-stimulated neuron in V1 remain unknown. In our study, in vivo calcium imaging and whole-cell electrophysiological patch-clamp recording were utilized to identify 53 individual cells from layer 2/3 of V1 as lightsensitive (LS) or non-light-sensitive (NS) by single-cell light-evoked calcium evaluation and action potential spiking. The contents of each cell after functional tests were aspirated in vivo through a patch-clamp pipette for mRNA sequencing. Moreover, the three-dimensional (3-D) morphological characterizations of the neurons were reconstructed in a live mouse after the whole-cell recordings. Our sequencing results indicated that V1 neurons with a high expression of genes related to transmission regulation, such as Rtn4r and Rgs7, and genes involved in membrane transport, such as Na+/K+ ATPase and NMDA-type glutamatergic receptors, preferentially responded to light stimulation. Furthermore, an antagonist that blocks Rtn4r signals could inactivate the neuronal responses to light stimulation in live mice. In conclusion, our findings of the vivo-seq analysis indicate the key role of the strength of synaptic transmission possesses neurons in V1 of light sensory.
. [J]. Protein & Cell, 2020, 11(6): 417-432.
Jianwei Liu, Mengdi Wang, Le Sun, Na Clara Pan, Changjiang Zhang, Junjing Zhang, Zhentao Zuo, Sheng He, Qian Wu, Xiaoqun Wang. Integrative analysis of in vivo recording with single-cell RNA-seq data reveals molecular properties of light-sensitive neurons in mouse V1. Protein Cell, 2020, 11(6): 417-432.
A Aperia, EE Akkuratov, JM Fontana, H Brismar (2016) Na+-K+- ATPase, a new class of plasma membrane receptors. Am J Physiol Cell Physiol 310:C491–495 https://doi.org/10.1152/ajpcell.00359.2015
2
S Arganda, R Guantes, GG de Polavieja (2007) Sodium pumps adapt spike bursting to stimulus statistics. Nat Neurosci 10:1467–1473 https://doi.org/10.1038/nn1982
3
C Bardy, M van den Hurk, B Kakaradov, JA Erwin, BN Jaeger, RV Hernandez, T Eames, AA Paucar, M Gorris, C Marchandet al. (2016) Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology. Mol Psychiatry 21:1573–1588 https://doi.org/10.1038/mp.2016.158
4
L Bjartmar, AD Huberman, EM Ullian, RC Renteria, X Liu, W Xu, J Prezioso, MW Susman, D Stellwagen, CC Stokeset al. (2006) Neuronal pentraxins mediate synaptic refinement in the devel- oping visual system. J Neurosci 26:6269–6281 https://doi.org/10.1523/JNEUROSCI.4212-05.2006
5
DD Bock, WC Lee, AM Kerlin, ML Andermann, G Hood, AW Wetzel, S Yurgenson, ER Soucy, HS Kim, RC Reid (2011) Network anatomy and in vivo physiology of visual cortical neurons. Nature 471:177–182 https://doi.org/10.1038/nature09802
6
A Butler, P Hoffman, P Smibert, E Papalexi, R Satija (2018) Integrating single-cell transcriptomic data across different condi- tions, technologies, and species. Nat Biotechnol 36:411 https://doi.org/10.1038/nbt.4096
7
CR Cadwell, A Palasantza, X Jiang, P Berens, Q Deng, M Yilmaz, J Reimer, S Shen, M Bethge, KF Toliaset al. (2016) Electro- physiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nat Biotechnol 34:199–203 https://doi.org/10.1038/nbt.3445
8
CR Cadwell, F Scala, S Li, G Livrizzi, S Shen, R Sandberg, X Jiang, AS Tolias (2017) Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq. Nat Protoc 12:2531–2553 https://doi.org/10.1038/nprot.2017.120
9
J Cang, RC Renteria, M Kaneko, X Liu, DR Copenhagen, MP Stryker (2005) Development of precise maps in visual cortex requires patterned spontaneous activity in the retina. Neuron 48:797–809 https://doi.org/10.1016/j.neuron.2005.09.015
10
LMW Chalupa, JS Werner (2003) The visual neurosciences. MIT Press, Cambridge
11
S Chen, T Huang, Y Zhou, Y Han, M Xu, J Gu (2017) AfterQC: automatic filtering, trimming, error removing and quality control for fastq data. BMC Bioinform 18:80 https://doi.org/10.1186/s12859-017-1469-3
12
X Chen, K Zhang, L Zhou, X Gao, J Wang, Y Yao, F He, Y Luo, Y Yu, S Liet al. (2016) Coupled electrophysiological recording and single cell transcriptome analyses revealed molecular mecha- nisms underlying neuronal maturation. Protein Cell 7:175–186 https://doi.org/10.1007/s13238-016-0247-8
13
A Cruz-Martin, RN El-Danaf, F Osakada, B Sriram, OS Dhande, PL Nguyen, EM Callaway, A Ghosh, AD Huberman (2014) A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex. Nature 507:358–361 https://doi.org/10.1038/nature12989
14
B Cubelos, CG Briz, GM Esteban-Ortega, M Nieto (2015) Cux1 and Cux2 selectively target basal and apical dendritic compartments of layer II-III cortical neurons. Dev Neurobiol 75:163–172 https://doi.org/10.1002/dneu.22215
15
W da Huang, BT Sherman, RA Lempicki (2009a) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37:1–13 https://doi.org/10.1093/nar/gkn923
16
W da Huang, BT Sherman, RA Lempicki (2009b) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57 https://doi.org/10.1038/nprot.2008.211
17
Y Ding, Y Zheng, T Liu, T Chen, C Wang, Q Sun, M Hua, T Hua (2017) Changes in GABAergic markers accompany degradation of neuronal function in the primary visual cortex of senescent rats. Sci Rep 7:14897 https://doi.org/10.1038/s41598-017-15006-3
18
A Dobin, CA Davis, F Schlesinger, J Drenkow, C Zaleski, S Jha, P Batut, M Chaisson, TR Gingeras (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21 https://doi.org/10.1093/bioinformatics/bts635
19
X Fan, J Dong, S Zhong, Y Wei, Q Wu, L Yan, J Yong, L Sun, X Wang, Y Zhaoet al. (2018) Spatial transcriptomic survey of human embryonic cerebral cortex by single-cell RNA-seq analysis. Cell Res 28:730–745 https://doi.org/10.1038/s41422-018-0053-3
20
SW Flavell, ME Greenberg (2008) Signaling mechanisms linking neuronal activity to gene expression and plasticity of the nervous system. Annu Rev Neurosci 31:563–590 https://doi.org/10.1146/annurev.neuro.31.060407.125631
21
J Fuzik, A Zeisel, Z Mate, D Calvigioni, Y Yanagawa, G Szabo, S Linnarsson, T Harkany (2016) Integration of electrophysiolog- ical recordings with single-cell RNA-seq data identifies neuronal subtypes. Nat Biotechnol 34:175–183 https://doi.org/10.1038/nbt.3443
22
G Gao, CS Fernandez, D Stapleton, AS Auster, J Widmer, JR Dyck, BE Kemp, LA Witters (1996) Non-catalytic beta- and gamma- subunit isoforms of the 5’-AMP-activated protein kinase. J Biol Chem 271:8675–8681 https://doi.org/10.1074/jbc.271.15.8675
23
KJ Gerber, KE Squires, JR Hepler (2016) Roles for Regulator of G Protein Signaling Proteins in Synaptic Signaling and Plasticity. Mol Pharmacol 89:273–286 https://doi.org/10.1124/mol.115.102210
24
LT Gray, Z Yao (2017) Layer-specific chromatin accessibility landscapes reveal regulatory networks in adult mouse visual cortex. Elife 6:e21883 https://doi.org/10.7554/eLife.21883
25
KM Hagihara, K Ohki (2013) Long-term down-regulation of GABA decreases orientation selectivity without affecting direction selec- tivity in mouse primary visual cortex. Front Neural Circuits 7:28 https://doi.org/10.3389/fncir.2013.00028
26
JL Herrero, MA Gieselmann, A Thiele (2017) Muscarinic and Nicotinic Contribution to Contrast Sensitivity of Macaque Area V1 Neurons. Front Neural Circuits 11:106 https://doi.org/10.3389/fncir.2017.00106
27
B Hille (2001) Ion channels of excitable membranes, 3rd edn. Sinauer, Sunderland
28
S Hrvatin, DR Hochbaum, MA Nagy, M Cicconet, K Robertson, L Cheadle, R Zilionis, A Ratner, R Borges-Monroy, AM Kleinet al. (2018) Single-cell analysis of experience-dependent transcrip- tomic states in the mouse visual cortex. Nat Neurosci 21:120–129 https://doi.org/10.1038/s41593-017-0029-5
29
F Hucho (1993) Neurotransmitter receptors. Elsevier, Amsterdam
30
B Juliandi, M Abematsu, T Sanosaka, K Tsujimura, A Smith, K Nakashima (2012) Induction of superficial cortical layer neurons from mouse embryonic stem cells by valproic acid. Neurosci Res 72:23–31 https://doi.org/10.1016/j.neures.2011.09.012
31
L Kaczmarek, A Chaudhuri (1997) Sensory regulation of immediate– early gene expression in mammalian visual cortex: implications for functional mapping and neural plasticity. Brain Res Brain Res Rev 23:237–256 https://doi.org/10.1016/S0165-0173(97)00005-2
32
PJ Kersey, JE Allen, A Allot, M Barba, S Boddu, BJ Bolt, D Carvalho- Silva, M Christensen, P Davis, C Grabmuelleret al. (2018) Ensembl Genomes 2018: an integrated omics infrastructure for non-vertebrate species. Nucleic Acids Res 46:D802–D808 https://doi.org/10.1093/nar/gkx1011
33
A Kirkwood, MC Rioult, MF Bear (1996) Experience-dependent modification of synaptic plasticity in visual cortex. Nature 381:526–528 https://doi.org/10.1038/381526a0
34
SK Lam, N Yoda, R Schekman (2010) A vesicle carrier that mediates peroxisome protein traffic from the endoplasmic reticulum. Proc Natl Acad Sci USA 107:21523–21528 https://doi.org/10.1073/pnas.1013397107
P Langfelder, S Horvath (2012) Fast R functions for robust correlations and hierarchical clustering. J Stat Softw 46 https://doi.org/10.18637/jss.v046.i11
37
SH Lee, AC Kwan, S Zhang, V Phoumthipphavong, JG Flannery, SC Masmanidis, H Taniguchi, ZJ Huang, F Zhang, ES Boydenet al. (2012) Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488:379–383 https://doi.org/10.1038/nature11312
38
SJ Lee, M Wei, C Zhang, S Maxeiner, C Pak, S Calado Botelho, J Trotter, FH Sterky, TC Sudhof (2017) Presynaptic neuronal pentraxin receptor organizes excitatory and inhibitory synapses. J Neurosci 37:1062–1080 https://doi.org/10.1523/JNEUROSCI.2768-16.2016
39
WC Lee, V Bonin, M Reed, BJ Graham, G Hood, K Glattfelder, RC Reid (2016) Anatomy and function of an excitatory network in the visual cortex. Nature 532:370–374 https://doi.org/10.1038/nature17192
40
D Leifer, D Krainc, YT Yu, J McDermott, RE Breitbart, J Heng, RL Neve, B Kosofsky, B Nadal-Ginard, SA Lipton (1993) MEF2C, a MADS/MEF2-family transcription factor expressed in a laminar distribution in cerebral cortex. Proc Natl Acad Sci USA 90:1546–1550 https://doi.org/10.1073/pnas.90.4.1546
41
CL Li, KC Li, D Wu, Y Chen, H Luo, JR Zhao, SS Wang, MM Sun, YJ Lu, YQ Zhonget al. (2016) Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity. Cell Res 26:967 https://doi.org/10.1038/cr.2016.90
42
J Li, J Zhang, M Wang, J Pan, X Chen, X Liao (2017a) Functional imaging of neuronal activity of auditory cortex by using Cal-520 in anesthetized and awake mice. Biomed Opt Express 8:2599–2610 https://doi.org/10.1364/BOE.8.002599
43
S Li, L Wang, X Tie, K Sohya, X Lin, A Kirkwood, B Jiang (2017b) Brief novel visual experience fundamentally changes synaptic plasticity in the mouse visual cortex. J Neurosci 37:9353–9360 https://doi.org/10.1523/JNEUROSCI.0334-17.2017
44
Y Liao, GK Smyth, W Shi (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930 https://doi.org/10.1093/bioinformatics/btt656
45
J Liu, W Liu, L Yang, Q Wu, H Zhang, A Fang, L Li, X Xu, L Sun, J Zhanget al. (2017) The primate-specific gene TMEM14B marks outer radial glia cells and promotes cortical expansion and folding. Cell Stem Cell 21(635–649):e638 https://doi.org/10.1016/j.stem.2017.08.013
46
MI Love, W Huber, S Anders (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550 https://doi.org/10.1186/s13059-014-0550-8
47
R Madabhushi, F Gao, AR Pfenning, L Pan, S Yamakawa, J Seo, R Rueda, T Phan, H Yamakawa, PC Paoet al. (2015) Activity- induced DNA breaks govern the expression of neuronal early- response genes. Cell 161:1592–1605 https://doi.org/10.1016/j.cell.2015.05.032
48
G Malagon, T Miki, I Llano, E Neher, A Marty (2016) Counting vesicular release events reveals binomial release statistics at single glutamatergic synapses. J Neurosci 36:4010–4025 https://doi.org/10.1523/JNEUROSCI.4352-15.2016
49
NJ Mangini, AL Pearlman (1980) Laminar distribution of receptive field properties in the primary visual cortex of the mouse. J Comp Neurol 193:203–222 https://doi.org/10.1002/cne.901930114
50
DJ McCarthy, KR Campbell, AT Lun, QF Wills (2017) Scater: pre- processing, quality control, normalization and visualization of single-cell RNA-seq data in R. Bioinformatics 33:1179–1186 https://doi.org/10.1093/bioinformatics/btw777
RF Moroni, F Inverardi, MC Regondi, A Watakabe, T Yamamori, R Spreafico, C Frassoni (2009) Expression of layer-specific markers in the adult neocortex of BCNU-Treated rat, a model of cortical dysplasia. Neuroscience 159:682–691 https://doi.org/10.1016/j.neuroscience.2008.12.064
H Okuno (2011) Regulation and function of immediate-early genes in the brain: beyond neuronal activity markers. Neurosci Res 69:175–186 https://doi.org/10.1016/j.neures.2010.12.007
56
P Paoletti, C Bellone, Q Zhou (2013) NMDA receptor subunit diversity: impact on receptor properties, synaptic plasticity and disease. Nat Rev Neurosci 14:383–400 https://doi.org/10.1038/nrn3504
57
X Pei, TR Vidyasagar, M Volgushev, OD Creutzfeldt (1994) Receptive field analysis and orientation selectivity of postsynaptic potentials of simple cells in cat visual cortex. J Neurosci 14:7130–7140 https://doi.org/10.1523/JNEUROSCI.14-11-07130.1994
58
KA Pelkey, E Barksdale, MT Craig, X Yuan, M Sukumaran, GA Vargish, RM Mitchell, MS Wyeth, RS Petralia, R Chittajalluet al. (2015) Pentraxins coordinate excitatory synapse maturation and circuit integration of parvalbumin interneurons. Neuron 85:1257–1272 https://doi.org/10.1016/j.neuron.2015.02.020
59
S Picelli, OR Faridani, AK Bjorklund, G Winberg, S Sagasser, R Sandberg (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9:171–181 https://doi.org/10.1038/nprot.2014.006
60
K Plossl, M Royer, S Bernklau, NN Tavraz, T Friedrich, J Wild, BHF Weber, U Friedrich (2017) Retinoschisin is linked to retinal Na/K-ATPase signaling and localization. Mol Biol Cell 28:2178–2189 https://doi.org/10.1091/mbc.e17-01-0064
61
I Sarria, C Orlandi, MA McCall, RG Gregg, KA Martemyanov (2016) Intermolecular interaction 2between anchoring subunits specify subcellular targeting and function of RGS proteins in retina ON- bipolar neurons. J Neurosci 36:2915–2925 https://doi.org/10.1523/JNEUROSCI.3833-15.2016
62
H Sato, Y Hata, H Masui, T Tsumoto (1987) A functional role of cholinergic innervation to neurons in the cat visual cortex. J Neurophysiol 58:765–780 https://doi.org/10.1152/jn.1987.58.4.765
63
GM Sia, JC Beique, G Rumbaugh, R Cho, PF Worley, RL Huganir (2007) Interaction of the N-terminal domain of the AMPA receptor GluR4 subunit with the neuronal pentraxin NP1 mediates GluR4 synaptic recruitment. Neuron 55:87–102 https://doi.org/10.1016/j.neuron.2007.06.020
CE Stephany, LL Chan, SN Parivash, HM Dorton, M Piechowicz, S Qiu, AW McGee (2014) Plasticity of binocularity and visual acuity are differentially limited by nogo receptor. J Neurosci 34:11631–11640 https://doi.org/10.1523/JNEUROSCI.0545-14.2014
66
CE Stephany, MG Frantz, AW McGee (2016a) Multiple roles for nogo receptor 1 in visual system plasticity. Neuroscientist 22:653–666 https://doi.org/10.1177/1073858415614564
67
CE Stephany, T Ikrar, C Nguyen, X Xu, AW McGee (2016b) Nogo receptor 1 confines a disinhibitory microcircuit to the critical period in visual cortex. J Neurosci 36:11006–11012 https://doi.org/10.1523/JNEUROSCI.0935-16.2016
68
C Stosiek, O Garaschuk, K Holthoff, A Konnerth (2003) In vivo two- photon calcium imaging of neuronal networks. Proc Natl Acad Sci USA 100:7319–7324 https://doi.org/10.1073/pnas.1232232100
69
RA Thomas, J Gibon, CXQ Chen, S Chierzi, VG Soubannier, S Baulac, P Seguela, K Murai, PA Barker (2018) The nogo receptor ligand LGI1 regulates synapse number and synaptic activity in hippocampal and cortical neurons. eNeuro. https://doi.org/10.1523/ENEURO.0185-18.2018
70
SF Traynelis, LP Wollmuth, CJ McBain, FS Menniti, KM Vance, KK Ogden, KB Hansen, H Yuan, SJ Myers, R Dingledine (2010) Glutamate receptor ion channels: structure, regulation, and function. Pharmacol Rev 62:405–496 https://doi.org/10.1124/pr.109.002451
71
QF Wu, L Yang, S Li, Q Wang, XB Yuan, X Gao, L Bao, X Zhang (2012)Fibroblast growth factor 13 is a microtubule-stabilizing protein regulating neuronal polarization and migration. Cell 149:1549–1564 https://doi.org/10.1016/j.cell.2012.04.046
72
HA Zariwala, L Madisen, KF Ahrens, A Bernard, ES Lein, AR Jones, H Zeng (2011) Visual tuning properties of genetically identified layer 2/3 neuronal types in the primary visual cortex of cre- transgenic mice. Front Syst Neurosci 4:162 https://doi.org/10.3389/fnsys.2010.00162
73
S Zhong, S Zhang, X Fan, Q Wu, L Yan, J Dong, H Zhang, L Li, L Sun, N Panet al. (2018) A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature 555:524 https://doi.org/10.1038/nature25980
