Development of a multi-species scRNA-seq atlas of metabolic dysfunction–sssociated steatotic liver disease (MASLD)

buir.advisorKarakayalı, Özlen Konu
dc.contributor.authorDemirdizen, Mert
dc.date.accessioned2024-07-30T13:34:32Z
dc.date.available2024-07-30T13:34:32Z
dc.date.copyright2024-07
dc.date.issued2024-07
dc.date.submitted2024-07-29
dc.descriptionCataloged from PDF version of article.
dc.descriptionThesis (Master's): Bilkent University, Department of Molecular Biology and Genetics, İhsan Doğramacı Bilkent University, 2024.
dc.descriptionIncludes bibliographical references (leaves 67-91).
dc.description.abstractMetabolic dysfunction-associated steatotic liver disease (MASLD) affects a significant portion of the human population, potentially leading to severe secondary conditions. Despite extensive research on patients and animal models to understand the disease's initiation and progression, and the development of various therapeutic strategies, current non-invasive techniques remain inefficient, and only one drug has been approved. This underscores the critical need to elucidate the cellular mechanisms driving MASLD to develop new diagnostic and therapeutic approaches. Single-cell RNA sequencing (scRNA-seq) enables the investigation of transcriptomic profiles at the cellular level. Various studies have utilized scRNA-seq to explore MASLD in patient samples and animal models. Although there are numerous publicly available scRNA-seq datasets from these studies, no comprehensive tool exists to explore and analyse them collectively. In this study, publicly available scRNA-seq datasets related to MASLD were collected and reanalysed, adhering to best practices suggested in the literature, and a web tool was developed for their visualisation and custom downstream analyses. Thirteen datasets obtained from the livers of human MASLD spectrum patients, and three datasets different animal models, two mouse and one zebrafish, were uniformly preprocessed. The two human datasets containing cirrhotic samples and two fibrotic datasets, one from mouse and another from zebrafish models, were integrated to reveal the conserved mechanisms of liver fibrosis among human patients and animal models. A web tool was developed in R Shiny to enable visualizations, cell cluster selection, differential expression analysis and gene set enrichment of genes and gene sets. The utility of the app was demonstrated by conducting a case study with the integrated dataset. The results included an endothelial cluster that had cells from each of the four datasets, and differential gene expression analysis on the integrated dataset provided significantly modulated known, e.g., SYNPO and TIMD4 liver fibrosis-associated genes across the three species. As a result, the custom analysis workflow provided in this thesis can allow the detection of conserved markers in different MASDL stages by further analysing this and other integrated datasets in the future.
dc.description.provenanceSubmitted by İlknur Sarıkaya (ilknur.sarikaya@bilkent.edu.tr) on 2024-07-30T13:34:32Z No. of bitstreams: 1 B021394.pdf: 5988725 bytes, checksum: 919c5265a5599ab81d1a72c1c2334223 (MD5)en
dc.description.provenanceMade available in DSpace on 2024-07-30T13:34:32Z (GMT). No. of bitstreams: 1 B021394.pdf: 5988725 bytes, checksum: 919c5265a5599ab81d1a72c1c2334223 (MD5) Previous issue date: 2024-07en
dc.description.statementofresponsibilityby Mert Demirdizen
dc.embargo.release2025-01-29
dc.format.extentxii, 97 leaves : color illustrations, charts ; 30 cm.
dc.identifier.itemidB021394
dc.identifier.urihttps://hdl.handle.net/11693/115466
dc.language.isoEnglish
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMetabolic dysfunction–associated steatotic liver disease
dc.subjectMASLD
dc.subjectSingle-cell RNA sequencing
dc.subjectScRNA-seq
dc.subjectShiny app
dc.titleDevelopment of a multi-species scRNA-seq atlas of metabolic dysfunction–sssociated steatotic liver disease (MASLD)
dc.title.alternativeMetabolik disfonksiyon ilişkili yağlı karaciğer hastalığı (MASLD) için çok türlü scRNA-seq atlasının geliştirilmesi
dc.typeThesis
thesis.degree.disciplineMolecular Biology and Genetics
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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