Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
04 02 2019
Historique:
received: 28 06 2018
accepted: 10 01 2019
entrez: 6 2 2019
pubmed: 6 2 2019
medline: 11 4 2019
Statut: epublish

Résumé

Midbrain dopamine (mDA) neurons constitute a heterogenous group of cells that have been intensely studied, not least because their degeneration causes major symptoms in Parkinson's disease. Understanding the diversity of mDA neurons - previously well characterized anatomically - requires a systematic molecular classification at the genome-wide gene expression level. Here, we use single cell RNA sequencing of isolated mouse neurons expressing the transcription factor Pitx3, a marker for mDA neurons. Analyses include cells isolated during development up until adulthood and the results are validated by histological characterization of newly identified markers. This identifies seven neuron subgroups divided in two major branches of developing Pitx3-expressing neurons. Five of them express dopaminergic markers, while two express glutamatergic and GABAergic markers, respectively. Analysis also indicate evolutionary conservation of diversity in humans. This comprehensive molecular characterization will provide a valuable resource for elucidating mDA neuron subgroup development and function in the mammalian brain.

Identifiants

pubmed: 30718509
doi: 10.1038/s41467-019-08453-1
pii: 10.1038/s41467-019-08453-1
pmc: PMC6362095
doi:

Substances chimiques

Homeodomain Proteins 0
Transcription Factors 0
homeobox protein PITX3 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

581

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Auteurs

Katarína Tiklová (K)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden. katarina.tiklova@ki.se.

Åsa K Björklund (ÅK)

Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, SE-752 37, Uppsala, Sweden.

Laura Lahti (L)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden.

Alessandro Fiorenzano (A)

Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, and Lund Stem Cell Centre, Department of Experimental Medical Science, Lund University, SE-221 84, Lund, Sweden.

Sara Nolbrant (S)

Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, and Lund Stem Cell Centre, Department of Experimental Medical Science, Lund University, SE-221 84, Lund, Sweden.

Linda Gillberg (L)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden.

Nikolaos Volakakis (N)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden.

Chika Yokota (C)

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, SE-171 65, Solna, Sweden.

Markus M Hilscher (MM)

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, SE-171 65, Solna, Sweden.

Thomas Hauling (T)

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, SE-171 65, Solna, Sweden.

Fredrik Holmström (F)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden.

Eliza Joodmardi (E)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden.

Mats Nilsson (M)

Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, SE-171 65, Solna, Sweden.

Malin Parmar (M)

Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, and Lund Stem Cell Centre, Department of Experimental Medical Science, Lund University, SE-221 84, Lund, Sweden.

Thomas Perlmann (T)

Ludwig Institute for Cancer Research, Box 240, SE-171 77, Stockholm, Sweden. thomas.perlmann@ki.se.
Department of Cell and Molecular Biology, Karolinska Institutet, SE-171 77, Stockholm, Sweden. thomas.perlmann@ki.se.

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Classifications MeSH