Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq

Current Biology

Volumn 28, Issue 7, 2018, Pages 1052-1065.e7

  Pandey, Shristi ^a   Shekhar, Karthik ^b   Regev, Aviv ^b,c   Schier, Alexander F ^a,b,d,e  

^a HARVARD UNIVERSITY   (United States)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d UNIVERSITY OF BASEL   (Switzerland)

^e UNIVERSITY OF WASHINGTON   (United States)

Author keywords

adult; habenula; in situ atlas; larva; neuronal types; single cell RNA seq; transcriptomes; zebrafish

Indexed keywords

ZEBRAFISH PROTEIN;

ANATOMY AND HISTOLOGY; ANIMAL; CYTOLOGY; GENE EXPRESSION REGULATION; GENETICS; GROWTH, DEVELOPMENT AND AGING; HABENULA; HIGH THROUGHPUT SEQUENCING; LARVA; METABOLISM; NERVE CELL; NERVOUS SYSTEM DEVELOPMENT; PHYSIOLOGY; PROCEDURES; SINGLE CELL ANALYSIS; ZEBRA FISH;

ANIMALS; GENE EXPRESSION REGULATION, DEVELOPMENTAL; HABENULA; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; LARVA; NEUROGENESIS; NEURONS; SINGLE-CELL ANALYSIS; ZEBRAFISH; ZEBRAFISH PROTEINS;

EID: 85044604944     PISSN: 09609822     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cub.2018.02.040     Document Type: Article

References (68)

1. Poulin, J.F., Tasic, B., Hjerling-Leffler, J., Trimarchi, J.M., Awatramani, R., Disentangling neural cell diversity using single-cell transcriptomics. Nat. Neurosci. 19 (2016), 1131–1141.
2. Zeng, H., Sanes, J.R., Neuronal cell-type classification: Challenges, opportunities and the path forward. Nat. Rev. Neurosci. 18 (2017), 530–546.
3. Pollen, A.A., Nowakowski, T.J., Shuga, J., Wang, X., Leyrat, A.A., Lui, J.H., Li, N., Szpankowski, L., Fowler, B., Chen, P., et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32 (2014), 1053–1058.
4. Chen, R., Wu, X., Jiang, L., Zhang, Y., Single-cell RNA-seq reveals hypothalamic cell diversity. Cell Rep. 18 (2017), 3227–3241.
5. Tasic, B., Menon, V., Nguyen, T.N., Kim, T.K., Jarsky, T., Yao, Z., Levi, B., Gray, L.T., Sorensen, S.A., Dolbeare, T., et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat. Neurosci. 19 (2016), 335–346.
6. Zeisel, A., Muñoz-Manchado, A.B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347 (2015), 1138–1142.
7. Pollen, A.A., Nowakowski, T.J., Chen, J., Retallack, H., Sandoval-Espinosa, C., Nicholas, C.R., Shuga, J., Liu, S.J., Oldham, M.C., Diaz, A., et al. Molecular identity of human outer radial glia during cortical development. Cell 163 (2015), 55–67.
8. Macosko, E.Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A.R., Kamitaki, N., Martersteck, E.M., et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161 (2015), 1202–1214.
9. Klein, A.M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D.A., Kirschner, M.W., Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161 (2015), 1187–1201.
10. Shekhar, K., Lapan, S.W., Whitney, I.E., Tran, N.M., Macosko, E.Z., Kowalczyk, M., Adiconis, X., Levin, J.Z., Nemesh, J., Goldman, M., et al. Comprehensive classification of retinal bipolar neurons by single-cell transcriptomics. Cell 166 (2016), 1308–1323.
11. Bianco, I.H., Wilson, S.W., The habenular nuclei: A conserved asymmetric relay station in the vertebrate brain. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364 (2009), 1005–1020.
12. Hikosaka, O., The habenula: From stress evasion to value-based decision-making. Nat. Rev. Neurosci. 11 (2010), 503–513.
13. Namboodiri, V.M., Rodriguez-Romaguera, J., Stuber, G.D., The habenula. Curr. Biol. 26 (2016), R873–R877.
14. Proulx, C.D., Hikosaka, O., Malinow, R., Reward processing by the lateral habenula in normal and depressive behaviors. Nat. Neurosci. 17 (2014), 1146–1152.
15. Beretta, C.A., Dross, N., Guiterrez-Triana, J.A., Ryu, S., Carl, M., Habenula circuit development: Past, present, and future. Front. Neurosci., 2012, 10.3389/fnins.2012.00051 Published online April 23, 2012.
16. Okamoto, H., Aizawa, H., Fear and anxiety regulation by conserved affective circuits. Neuron 78 (2013), 411–413.
17. Amo, R., Aizawa, H., Takahoko, M., Kobayashi, M., Takahashi, R., Aoki, T., Okamoto, H., Identification of the zebrafish ventral habenula as a homolog of the mammalian lateral habenula. J. Neurosci. 30 (2010), 1566–1574.
18. Agetsuma, M., Aizawa, H., Aoki, T., Nakayama, R., Takahoko, M., Goto, M., Sassa, T., Amo, R., Shiraki, T., Kawakami, K., et al. The habenula is crucial for experience-dependent modification of fear responses in zebrafish. Nat. Neurosci. 13 (2010), 1354–1356.
19. Chou, M.Y., Amo, R., Kinoshita, M., Cherng, B.W., Shimazaki, H., Agetsuma, M., Shiraki, T., Aoki, T., Takahoko, M., Yamazaki, M., et al. Social conflict resolution regulated by two dorsal habenular subregions in zebrafish. Science 352 (2016), 87–90.
20. Amo, R., Fredes, F., Kinoshita, M., Aoki, R., Aizawa, H., Agetsuma, M., Aoki, T., Shiraki, T., Kakinuma, H., Matsuda, M., et al. The habenulo-raphe serotonergic circuit encodes an aversive expectation value essential for adaptive active avoidance of danger. Neuron 84 (2014), 1034–1048.
21. Okamoto, H., Neurobiology: Sensory lateralization in the fish brain. Curr. Biol. 24 (2014), R285–R287.
22. Hong, E., Santhakumar, K., Akitake, C.A., Ahn, S.J., Thisse, C., Thisse, B., Wyart, C., Mangin, J.M., Halpern, M.E., Cholinergic left-right asymmetry in the habenulo-interpeduncular pathway. Proc. Natl. Acad. Sci. USA 110 (2013), 21171–21176.
23. deCarvalho, T.N., Subedi, A., Rock, J., Harfe, B.D., Thisse, C., Thisse, B., Halpern, M.E., Hong, E., Neurotransmitter map of the asymmetric dorsal habenular nuclei of zebrafish. Genesis 52 (2014), 636–655.
24. Kuan, Y.S., Yu, H.H., Moens, C.B., Halpern, M.E., Neuropilin asymmetry mediates a left-right difference in habenular connectivity. Development 134 (2007), 857–865.
25. Biran, J., Palevitch, O., Ben-Dor, S., Levavi-Sivan, B., Neurokinin Bs and neurokinin B receptors in zebrafish-potential role in controlling fish reproduction. Proc. Natl. Acad. Sci. USA 109 (2012), 10269–10274.
26. Dreosti, E., Vendrell Llopis, N., Carl, M., Yaksi, E., Wilson, S.W., Left-right asymmetry is required for the habenulae to respond to both visual and olfactory stimuli. Curr. Biol. 24 (2014), 440–445.
27. Jetti, S.K., Vendrell-Llopis, N., Yaksi, E., Spontaneous activity governs olfactory representations in spatially organized habenular microcircuits. Curr. Biol. 24 (2014), 434–439.
28. Kishimoto, N., Asakawa, K., Madelaine, R., Blader, P., Kawakami, K., Sawamoto, K., Interhemispheric asymmetry of olfactory input-dependent neuronal specification in the adult brain. Nat. Neurosci. 16 (2013), 884–888.
29. Zheng, G.X., Terry, J.M., Belgrader, P., Ryvkin, P., Bent, Z.W., Wilson, R., Ziraldo, S.B., Wheeler, T.D., McDermott, G.P., Zhu, J., et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun., 8, 2017, 14049.
30. Picelli, S., Björklund, A.K., Faridani, O.R., Sagasser, S., Winberg, G., Sandberg, R., Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat. Methods 10 (2013), 1096–1098.
31. Satija, R., Farrell, J.A., Gennert, D., Schier, A.F., Regev, A., Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33 (2015), 495–502.
32. Waltman, L., Eck, N.J.V., A smart local moving algorithm for large-scale modularity-based community detection. Eur. Phys. J. B, 86, 2013, 471.
33. McDavid, A., Finak, G., Chattopadyay, P.K., Dominguez, M., Lamoreaux, L., Ma, S.S., Roederer, M., Gottardo, R., Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments. Bioinformatics 29 (2013), 461–467.
34. Bayramli, X., Kocagöz, Y., Sakizli, U., Fuss, S.H., Patterned arrangements of olfactory receptor gene expression in zebrafish are established by radial movement of specified olfactory sensory neurons. Sci. Rep., 7, 2017, 5572.
35. Kitahashi, T., Ogawa, S., Parhar, I.S., Cloning and expression of kiss2 in the zebrafish and medaka. Endocrinology 150 (2009), 821–831.
36. Broms, J., Antolin-Fontes, B., Tingström, A., Ibañez-Tallon, I., Conserved expression of the GPR151 receptor in habenular axonal projections of vertebrates. J. Comp. Neurol. 523 (2015), 359–380.
37. Hirai, H., Pang, Z., Bao, D., Miyazaki, T., Li, L., Miura, E., Parris, J., Rong, Y., Watanabe, M., Yuzaki, M., Morgan, J.I., Cbln1 is essential for synaptic integrity and plasticity in the cerebellum. Nat. Neurosci. 8 (2005), 1534–1541.
38. Ngo, L., Haas, M., Qu, Z., Li, S.S., Zenker, J., Teng, K.S., Gunnersen, J.M., Breuss, M., Habgood, M., Keays, D.A., Heng, J.I., TUBB5 and its disease-associated mutations influence the terminal differentiation and dendritic spine densities of cerebral cortical neurons. Hum. Mol. Genet. 23 (2014), 5147–5158.
39. Jefferis, G.S., Potter, C.J., Chan, A.M., Marin, E.C., Rohlfing, T., Maurer, C.R. Jr., Luo, L., Comprehensive maps of Drosophila higher olfactory centers: Spatially segregated fruit and pheromone representation. Cell 128 (2007), 1187–1203.
40. Rohlfing, T., Maurer, C.R. Jr., Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees. IEEE Trans. Inf. Technol. Biomed. 7 (2003), 16–25.
41. Randlett, O., Wee, C.L., Naumann, E.A., Nnaemeka, O., Schoppik, D., Fitzgerald, J.E., Portugues, R., Lacoste, A.M., Riegler, C., Engert, F., Schier, A.F., Whole-brain activity mapping onto a zebrafish brain atlas. Nat. Methods 12 (2015), 1039–1046.
42. Shalek, A.K., Satija, R., Adiconis, X., Gertner, R.S., Gaublomme, J.T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498 (2013), 236–240.
43. Breiman, L., Random forests. Mach. Learn. 45 (2001), 5–32.
44. Wong, M.K., Sze, K.H., Chen, T., Cho, C.K., Law, H.C., Chu, I.K., Wong, A.O., Goldfish spexin: Solution structure and novel function as a satiety factor in feeding control. Am. J. Physiol. Endocrinol. Metab. 305 (2013), E348–E366.
45. Appelbaum, L., Wang, G.X., Maro, G.S., Mori, R., Tovin, A., Marin, W., Yokogawa, T., Kawakami, K., Smith, S.J., Gothilf, Y., et al. Sleep-wake regulation and hypocretin-melatonin interaction in zebrafish. Proc. Natl. Acad. Sci. USA 106 (2009), 21942–21947.
46. Habib, N., Li, Y., Heidenreich, M., Swiech, L., Avraham-Davidi, I., Trombetta, J.J., Hession, C., Zhang, F., Regev, A., Div-Seq: Single-nucleus RNA-seq reveals dynamics of rare adult newborn neurons. Science 353 (2016), 925–928.
47. Masland, R.H., The fundamental plan of the retina. Nat. Neurosci. 4 (2001), 877–886.
48. Shimada, Y., Hirano, M., Nishimura, Y., Tanaka, T., A high-throughput fluorescence-based assay system for appetite-regulating gene and drug screening. PLoS ONE, 7, 2012, e52549.
49. Dreosti, E., Lopes, G., Kampff, A.R., Wilson, S.W., Development of social behavior in young zebrafish. Front. Neural Circuits, 9, 2015, 39.
50. Duboue, E.R., Hong, E., Eldred, K.C., Halpern, M.E., Left habenular activity attenuates fear responses in larval zebrafish. Curr. Biol. 27 (2017), 2154–2162.
51. Lénárd, L., László, K., Kertes, E., Ollmann, T., Péczely, L., Kovács, A., Kállai, V., Zagorácz, O., Gálosi, R., Karádi, Z., Substance P and neurotensin in the limbic system: Their roles in reinforcement and memory consolidation. Neurosci. Biobehav. Rev. 85 (2018), 1–20.
52. Normandeau, C.P., Ventura-Silva, A.P., Hawken, E.R., Angelis, S., Sjaarda, C., Liu, X., Pêgo, J.M., Dumont, É.C., A key role for neurotensin in chronic-stress-induced anxiety-like behavior in rats. Neuropsychopharmacology 43 (2018), 285–293.
53. Fore, S., Palumbo, F., Pelgrims, R., Yaksi, E., Information processing in the vertebrate habenula. Semin. Cell Dev. Biol., 2017, 10.1016/j.semcdb.2017.08 Published online August 7, 2017.
54. Lovett-Barron, M., Andalman, A.S., Allen, W.E., Vesuna, S., Kauvar, I., Burns, V.M., Deisseroth, K., Ancestral circuits for the coordinated modulation of brain state. Cell 171 (2017), 1411–1423.
55. Campbell, J.N., Macosko, E.Z., Fenselau, H., Pers, T.H., Lyubetskaya, A., Tenen, D., Goldman, M., Verstegen, A.M., Resch, J.M., McCarroll, S.A., et al. A molecular census of arcuate hypothalamus and median eminence cell types. Nat. Neurosci. 20 (2017), 484–496.
56. Gokce, O., Stanley, G.M., Treutlein, B., Neff, N.F., Camp, J.G., Malenka, R.C., Rothwell, P.E., Fuccillo, M.V., Südhof, T.C., Quake, S.R., Cellular taxonomy of the mouse striatum as revealed by single-cell RNA-seq. Cell Rep. 16 (2016), 1126–1137.
57. Zheng, G.X., Lau, B.T., Schnall-Levin, M., Jarosz, M., Bell, J.M., Hindson, C.M., Kyriazopoulou-Panagiotopoulou, S., Masquelier, D.A., Merrill, L., Terry, J.M., et al. Haplotyping germline and cancer genomes with high-throughput linked-read sequencing. Nat. Biotechnol. 34 (2016), 303–311.
58. Ronneberger, O., Liu, K., Rath, M., Rueβ, D., Mueller, T., Skibbe, H., Drayer, B., Schmidt, T., Filippi, A., Nitschke, R., et al. ViBE-Z: A framework for 3D virtual colocalization analysis in zebrafish larval brains. Nat. Methods 9 (2012), 735–742.
59. Marquart, G.D., Tabor, K.M., Horstick, E.J., Brown, M., Burgess, H.A., High precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization. Gigascience 6 (2016), 1–15.
60. Langmead, B., Salzberg, S.L., Fast gapped-read alignment with Bowtie 2. Nat. Methods 9 (2012), 357–359.
61. Li, B., Dewey, C.N., RSEM: Accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics, 12, 2011, 323.
62. Brennecke, P., Anders, S., Kim, J.K., Kołodziejczyk, A.A., Zhang, X., Proserpio, V., Baying, B., Benes, V., Teichmann, S.A., Marioni, J.C., Heisler, M.G., Accounting for technical noise in single-cell RNA-seq experiments. Nat. Methods 10 (2013), 1093–1095.
63. Chung, N.C., Storey, J.D., Statistical significance of variables driving systematic variation in high-dimensional data. Bioinformatics 31 (2015), 545–554.
64. Hinton, G., Maaten, L.d., Visualizing data using t-SNE. J. Mach. Learn. Res. 9 (2008), 2579–2605.
65. Milligan, G.W., Cooper, M.C., A study of the comparability of external criteria for hierarchical cluster analysis. Multivariate Behav. Res. 21 (1986), 441–458.
66. Valente, A., Huang, K.H., Portugues, R., Engert, F., Ontogeny of classical and operant learning behaviors in zebrafish. Learn. Mem. 19 (2012), 170–177.
67. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., Gingeras, T.R., STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29 (2013), 15–21.
68. Marquart, G.D., High-precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization. GigaScience 6 (2017), 1–15.