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Transcriptomic analysis of the developing mouse habenula

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correlation gwas habenula mouse scrna-seq brain correlation-analysis scanpy seurat

dev_hb_mouse's Introduction

Analysis of Developmental mouse habenula dataset

This is a repository that holds all scripts for the manuscript:

Molecular signatures and cellular diversity during mouse habenula development. Lieke L. van de Haar, Danai Riga, Juliska E. Boer, Oxana Garritsen, Youri Adolfs, Thomas E. Sieburgh, Roland E. van Dijk, Kyoko Watanabe, Nicky C.H. van Kronenburg, Mark H. Broekhoven, Danielle Posthuma, Frank J. Meye, Onur Basak, R. Jeroen Pasterkamp. Cell Reports, Volume 40, Issue 1, 2022, 111029, ISSN 2211-1247, https://doi.org/10.1016/j.celrep.2022.111029.

The scripts are ordered by performed analysis. The order of execution can be read in Materials and Methods section in said manuscript. All data (count matrices and FastQ files) can be accessed through GEO: GSE188712.


External scRNAseq datasets used in this study:

  • Mouse diencephalon on E12.5 - Guo Q, Li JYH. Defining developmental diversification of diencephalon neurons through single cell gene expression profiling. Development 146(12): dev174284 (2019). doi: https://doi.org/10.1242/dev.174284
  • Adult mouse habenula dataset - Hashikawa Y, Hashikawa K, Rossi M, Basiri ML, Liu Y, Johnston NL, et al. Transcriptional and Spatial Resolution of Cell Types in the Mammalian Habenula. Neuron in press (2020). doi: https://doi.org/10.1016/j.neuron.2020.03.011
  • Adult mouse habenula dataset - Wallace M, Huang KW, Hochbaum D, Hyun M, Radeljic G, Sabatini BL. Anatomical and single-cell transcriptional profiling of the murine habenular complex. eLife 9: e51271 (2020). doi: https://doi.org/10.7554/eLife.51271
  • Larval zebrafish habenula dataset - Pandey S, Shekhar K, Regev A, Schier AF. Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq. Curr Biol. 28(7): 1052‐1065.e7 (2018). doi: https://doi.org/10.1016/j.cub.2018.02.040
  • Adult zebrafish habenula dataset - Pandey S, Shekhar K, Regev A, Schier AF. Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq. Curr Biol. 28(7): 1052‐1065.e7 (2018). doi: https://doi.org/10.1016/j.cub.2018.02.040
  • Adult mouse brain tissue dataset - The Tabula Muris Consortium. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562: 367-372 (2018). doi: https://doi.org/10.1038/s41586-018-0590-4
  • Developmental mouse hypothalamus dataset - Kim DW, Washington PW, Wang ZQ, Hao Lin S, Sun C, Ismail BT, et al. The cellular and molecular landscape of hypothalamic patterning and differentiation from embryonic to late postnatal development. Nat Commun 11: 4360 (2020). doi: https://doi.org/10.1038/s41467-020-18231-z
  • Developmental and adult mouse midbrain dataset - La Manno G, Gyllborg D, Codeluppi S, Nishimura K, Salto C, Zeisel A, et al. Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells. Cell 167(2): 566-580 (2016). doi: https://doi.org/10.1016/j.cell.2016.09.027

GWAS summary statistics used in this study:

  • Bipolar Disorder - Hou L, Bergen SE, Akula N, Song J, Hultman CM, Landén M, et al. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder. Hum Mol Genet 25(15): 3383-3394 (2016). doi: https://doi.org/10.1093/hmg/ddw181
  • Body-Mass Index - Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518(7538): 197-206 (2015). doi: https://doi.org/10.1038/nature14177
  • Height - Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet 46(11): 1173-1186 (2014). doi: https://doi.org/10.1038/ng.3097
  • Major Depressive Disorder - Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 50(5): 668-681 (2018). doi: https://doi.org/10.1038/s41588-018-0090-3
  • Schizophrenia - Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated loci. Nature 511(7510): 421-427 (2014). doi: https://doi.org/10.1038/nature13595

Correspondance, requests or questions can be addressed to: [email protected]

Lieke L van de Haar, Juliska E Boer (2022)

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