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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorRidder, Jeroen
dc.contributor.authorArts, Julian
dc.date.accessioned2022-10-21T00:00:39Z
dc.date.available2022-10-21T00:00:39Z
dc.date.issued2022
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/43011
dc.description.abstractThe outmost layer of the cornea, the corneal epithelium, is maintained by stem cells in the limbus called limbal stem cells. Cells in the cornea shift their cell type in a process called stratification. For cells involved in corneal stratication, it is vital to maintain the proper cell fate. Transcription factors (TFs) driving gene regulatory networks (GRNs) determine proper cell fate determination. Thus, determining which TFs drive cell fate determination in corneal cell types is necessary to get insights into corneal stratification. Here we combine data from the publicly available human corneal atlas. We show that a combination of single-cell RNA-seq and single-cell ATAC-seq can be used for determining gene regulatory networks. Motif analysis on single-cell ATAC-seq data after integration reveals a division of cell populations into stromal or epithelial cell fates. Moreover, we reveal TFs involved in driving corneal cell identity when we analyze gene regulatory networks of cell type clusters. Most importantly, KLF5, EHF, GRHL1 and ELF3 drive epithelial cell identity. We also show that limbal neural crest derived progenitor cells are separate from corneal, limbal and conjunctival cell clusters. Cell-cell interaction analysis demonstrates that this cell population could modulate the immune cells. Thus, we provide insights in corneal stratification by predicting which TFs are important for driving cell fate determination of cells in the human cornea.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectData integration of the single-cell human corneal atlas data to determine gene regulatory networks in single-cell populations.
dc.titleA Single-Cell Approach To Gene Regulatory Network Analysis of The Human Cornea
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsBioinformatics; single-cell epigenomics; cornea; data integration; gene regulatory networks
dc.subject.courseuuMolecular and Cellular Life Sciences
dc.thesis.id788


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