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Transcriptional states of human oligodendroglia during development
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre. Department of Medical Biochemistry and Biophysics, Karolinska Institutet. (Castelo-Branco group)
2021 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

Differentiation of oligodendroglia lineage cells in humans still remains largely unclear. Oligodendrocyte progenitor cells (OPCs) are known to participate in remyelination processes by proliferating, migrating to the area of the lesion and then differentiating into oligodendrocytes (OLs), which can myelinate the affected axons again. This has sparked an interest in OPCs, since cell transplant could be a potential form of therapy for demyelinating diseases such as multiple sclerosis. However, that is not the only relevant aspect about them. OPCs have been shown to present heterogeneous populations with different functions, such as participating in immunological processes or responses to injury.

Single cell technologies have become a powerful tool for the identification of unknown functions in OPCs and the characterization of the evolution of the oligodendroglia lineage. In this project, we analysed single-nuclei data of human foetal brain samples. For most of the steps of this pipeline, we used the Scanpy toolbox. In order to mitigate batch effects in our data, the Harmony algorithm was used for the correction. The Harmony-corrected principal components still retained part of the bias by batch. Leiden graph-based clustering resulted in a total of 19 clusters, 14 of which we were able to successfully annotate. Annotation was performed in combination of differential expression analysis and literature markers from public datasets. We obtained a single OPC cluster in our data, but marker genes expression suggests not all cells within this cluster are equally mature. Instead, some of them seem to be closer to commitment to an OL fate. This hypothesis would have to be confirmed by lineage inference analysis, which we could not include in this study. Finally, validation of our annotation with label transfer gave mixed results depending on the dataset used. This step was performed in Seurat. A possible explanation of these results could be sensitivity to differences between plate-based and droplet-based technologies for library preparation before sequencing. OPCs were successfully transferred regardless of the dataset used, so we can be certain of their identity.

Place, publisher, year, edition, pages
2021. , p. 57
Keywords [en]
single cell transcriptomics, development, oligodendroglia, oligodendrocyte progenitor cells
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-450814OAI: oai:DiVA.org:uu-450814DiVA, id: diva2:1586015
Educational program
Master Programme in Bioinformatics
Supervisors
Examiners
Available from: 2021-08-18 Created: 2021-08-18 Last updated: 2021-08-18Bibliographically approved

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CiteExportLink to record
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