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  • 1. Soldatov, Ruslan
    et al.
    Kaucka, Marketa
    Kastriti, Maria Eleni
    Petersen, Julian
    Chontorotzea, Tatiana
    Englmaier, Lukas
    Akkuratova, Natalia
    Yang, Yunshi
    Häring, Martin
    Dyachuk, Viacheslav
    Bock, Christoph
    Farlik, Matthias
    Piacentino, Michael L.
    Boismoreau, Franck
    Hilscher, Markus M.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Karolinska Institutet, Sweden.
    Yokota, Chika
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Qian, Xiaoyan
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Cartana AB, Sweden.
    Nilsson, Mats
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Bronner, Marianne E.
    Croci, Laura
    Hsiao, Wen-Yu
    Guertin, David A.
    Brunet, Jean-Francois
    Consalez, Gian Giacomo
    Ernfors, Patrik
    Fried, Kaj
    Kharchenko, Peter V.
    Adameyko, Igor
    Spatiotemporal structure of cell fate decisions in murine neural crest2019In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 364, no 6444, article id eaas9536Article in journal (Refereed)
    Abstract [en]

    Neural crest cells are embryonic progenitors that generate numerous cell types in vertebrates. With single-cell analysis, we show that mouse trunk neural crest cells become biased toward neuronal lineages when they delaminate from the neural tube, whereas cranial neural crest cells acquire ectomesenchyme potential dependent on activation of the transcription factor Twist1. The choices that neural crest cells make to become sensory, glial, autonomic, or mesenchymal cells can be formalized as a series of sequential binary decisions. Each branch of the decision tree involves initial coactivation of bipotential properties followed by gradual shifts toward commitment. Competing fate programs are coactivated before cells acquire fate-specific phenotypic traits. Determination of a specific fate is achieved by increased synchronization of relevant programs and concurrent repression of competing fate programs.

  • 2.
    Strell, Carina
    et al.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Hilscher, Markus M.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Laxman, Navya
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Svedlund, Jessica
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Wu, Chenglin
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Yokota, Chika
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Nilsson, Mats
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Placing RNA in context and space - methods for spatially resolved transcriptomics2019In: The FEBS Journal, ISSN 1742-464X, E-ISSN 1742-4658, Vol. 286, no 8, p. 1468-1481Article, review/survey (Refereed)
    Abstract [en]

    Single-cell transcriptomics provides us with completely new insights into the molecular diversity of different cell types and the different states they can adopt. The technique generates inventories of cells that constitute the building blocks of multicellular organisms. However, since the method requires isolation of discrete cells, information about the original location within tissue is lost. Therefore, it is not possible to draw detailed cellular maps of tissue architecture and their positioning in relation to other cells. In order to better understand the cellular and tissue function of multicellular organisms, we need to map the cells within their physiological, morphological, and anatomical context and space. In this review, we will summarize and compare the different methods of in situ RNA analysis and the most recent developments leading to more comprehensive and highly multiplexed spatially resolved transcriptomic approaches. We will discuss their highlights and advantages as well as their limitations and challenges and give an outlook on promising future applications and directions both within basic research as well as clinical integration.

  • 3. Tiklova, Katarina
    et al.
    Björklund, Åsa K.
    Lahti, Laura
    Fiorenzano, Alessandro
    Nolbrant, Sara
    Gillberg, Linda
    Volakakis, Nikolaos
    Yokota, Chika
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Hilscher, Markus M.
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Hauling, Thomas
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Holmstrom, Fredrik
    Joodmardi, Eliza
    Nilsson, Mats
    Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
    Parmar, Malin
    Perlmann, Thomas
    Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development2019In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 581Article in journal (Refereed)
    Abstract [en]

    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.

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