Single-cell transcriptomic reveals molecular diversity and developmental heterogeneity of human stem cell-derived oligodendrocyte lineage cells

Injury and loss of oligodendrocytes can cause demyelinating diseases such as multiple sclerosis. To improve our understanding of human oligodendrocyte development, which could facilitate development of remyelination-based treatment strategies, here we describe time-course single-cell-transcriptomic analysis of developing human stem cell-derived oligodendrocyte-lineage-cells (hOLLCs). The study includes hOLLCs derived from both genome engineered embryonic stem cell (ESC) reporter cells containing an Identification-and-Purification tag driven by the endogenous PDGFRα promoter and from unmodified induced pluripotent (iPS) cells. Our analysis uncovers substantial transcriptional heterogeneity of PDGFRα-lineage hOLLCs. We discover sub-populations of human oligodendrocyte progenitor cells (hOPCs) including a potential cytokine-responsive hOPC subset, and identify candidate regulatory genes/networks that define the identity of these sub-populations. Pseudotime trajectory analysis defines developmental pathways of oligodendrocytes vs astrocytes from PDGFRα-expressing hOPCs and predicts differentially expressed genes between the two lineages. In addition, pathway enrichment analysis followed by pharmacological intervention of these pathways confirm that mTOR and cholesterol biosynthesis signaling pathways are involved in maturation of oligodendrocytes from hOPCs.

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Don Zack
Dec 22, 2020 No software was used To extract expression matrices from fastq files dropseq cookbook (version 1.0.1) was used. The principal component analysis (PCA), tdistributed stochastic neighbor embedding (tSNE) and UMAP analyses were performed using a previously published, open source, R package, Seurat (version 2 and 3). Time-series analysis to generate a pseudotemporal trajectory was performed using an unsupervised differential gene expression test based on sample age in Monocle (version 2). The networks and pathway analyses were generated through the use of Gene Set Enrichment Analysis, Ingenuity Pathway Analysis (IPA QIAGEN Inc) and KEGG via Visualization and Integrated Discovery (DAVID, v6.7) tools. qPCR analysis was performed using CFX Maestro version: 4.1.2434.0124 (Biorad). Graphs were generated using prism version 9. Co-staining analysis of the tdTomato and PDGFRA was performed using a built-in algorithm of the ArrayScan image analysis software (ThermoFisher Scientific ArrayScan XTI). For flow analysis SH-800 Cell Sorter and its built-in software, SH800S was used.
NO custom codes were developed in this study. The previously published codes used in this study are deposited to: https://github.com/ wefang/TdTom nature research | reporting summary

October 2018
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.