CAP-RNAseq: an online platform for RNA-seq data clustering, annotation and prioritization based on gene essentiality and congruence between mRNA and protein levels
| buir.advisor | Karakayalı, Özlen Konu | |
| dc.contributor.author | Özdeniz, Merve Vural | |
| dc.date.accessioned | 2024-05-06T11:00:39Z | |
| dc.date.available | 2024-05-06T11:00:39Z | |
| dc.date.issued | 2024-04 | |
| dc.date.submitted | 2024-05-02 | |
| dc.department | Department of International Relations | |
| dc.description | Cataloged from PDF version of article. | |
| dc.description | Thesis (Ph.D.): Bilkent University, Graduate Program in Neuroscience, İhsan Doğramacı Bilkent University, 2024. | |
| dc.description | Includes bibliographical references (leaves 325-389). | |
| dc.description.abstract | In recent years, there has been a remarkable growth in the application of RNA-seq in both clinical and molecular biology research contexts. The analysis and interpretation of these RNA-seq data demands a good knowledge of bioinformatics. Many different applications are available to perform the analysis, but more comprehensive applications are needed, especially for researchers without coding experience. Therefore, I developed an all-in-one novel RNA-seq analysis tool, CAP-RNAseq (http://konulabapps.bilkent.edu.tr:3838/CAPRNAseq/), which provide valuable analysis for co-expression cluster prioritization and annotation. CAP-RNAseq in particular performs clustering of the genes based on their expression patterns, annotates mirror clusters that display inverse patterns with a network-based visualizations before prioritization of clusters and/or genes based on "gene essentiality", protein levels and the degree of congruence between mRNA and protein levels of genes. Furthermore, for illustration of the use of CAP-RNAseq in this thesis, I reanalyzed a number of published RNA-seq datasets and identified novel pathways modulated by NTRK2 overexpression (GSE136868) in neural stem cells and also showed significance of the essential genes/pathways in senescent cell clearance focusing on NTRK2 (fibroblast; GSE190998) and THBD (Huh7, GSE228941) siRNA models. In addition, I analyzed our lab’s novel RNA-seq data obtained from breast cancer cell lines in CAP-RNAseq; and the findings revealed a) the complex associations between steroid hormones; Drospirenone, Aldosterone, and Estrogen in hormone positive T47D and mineralocorticoid receptor-overexpressing MCF-7 cells; and b) significant differences in essential and non-essential gene expression of the isogenic MCF7 cells overexpressing wildtype or mutant TP53. I also studied a public breast cancer dataset (GSE201085) demonstrating CAP-RNAseq’s ability to identify novel breast cancer markers exhibiting high mRNA-protein level correlations. In conclusion, this thesis not only demonstrates the use and power of CAP-RNAseq as a tool to identify essential genes and pathways by analyzing RNA-seq data, but also provides new insights into the roles of essential genes in glioma, senescence and breast cancer. | |
| dc.description.degree | Ph.D. | |
| dc.description.statementofresponsibility | by Merve Vural Özdeniz | |
| dc.embargo.release | 2024-11-02 | |
| dc.format.extent | xxii, 393 leaves : illustrations (some color) ; 30 cm. | |
| dc.identifier.itemid | B120909 | |
| dc.identifier.uri | https://hdl.handle.net/11693/115162 | |
| dc.language.iso | English | |
| dc.publisher | Bilkent University | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Clustering | |
| dc.subject | Annotation | |
| dc.subject | Prioritization | |
| dc.subject | Transcriptome | |
| dc.subject | RNA-seq | |
| dc.subject | Cancer | |
| dc.title | CAP-RNAseq: an online platform for RNA-seq data clustering, annotation and prioritization based on gene essentiality and congruence between mRNA and protein levels | |
| dc.title.alternative | CAP-RNAseq: gen esansiyelliğine ve mRNA ve protein düzeyleri arasındaki uyuma dayalı RNA-Seq veri kümeleme, annotasyon ve önceliklendirme için çevrimiçi bir platform | |
| dc.type | Thesis |