Unit:
Κατεύθυνση Βιοπληροφορική-Υπολογιστική ΒιολογίαLibrary of the School of Science
Supervisors info:
Ιωάννης Μιχαλόπουλος, Ειδικός Λειτουργικός Επιστήμων Β’, Κέντρο Βιολογίας Συστημάτων, Ίδρυμα Ιατροβιολογικών Ερευνών της Ακαδημίας Αθηνών
Αλέξανδρος Γεωργακίλας, Καθηγητής, Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών, Εθνικό Μετσόβιο Πολυτεχνείο
Βασιλική Οικονομίδου, Αναπληρώτρια Καθηγήτρια, Τμήμα Βιολογίας, ΕΚΠΑ
Original Title:
Μετα-ανάλυση μεταγραφωμικών δεδομένων έκθεσης σε ακτινοβολίες UV
Translated title:
Meta-analysis of transcriptomic data of UV radiation exposure
Summary:
The electromagnetic spectrum spans from radio waves to gamma rays, with UVR located between visible light and X-rays (100-400 nm). UVR, originating from both natural and artificial sources, can induce significant biological effects on cells. This thesis focuses on analyzing differential gene expression to identify genes that are differentially expressed under UV radiation, aiming to understand the biological effects resulting from exposure to this type of radiation.
The primary data for this project was obtained from the European Nucleotide Archive (ENA) database. Following quality control and RNA-Seq processing, differential gene expression analysis was conducted to create a list of differentially expressed genes per study. These lists were then integrated through the prism of a meta-analysis, ranking the genes by statistical significance. The final ranked list was utilized for biological term enrichment analysis and protein-protein (PPI) interaction networks, identifying common biological functions linked to the response to UV radiation.
From the results, a variety of DEGs and biological processes were observed with the most important ones falling into the categories of immune-inflammatory response, DNA damage and DDR pathways, oxidative stress and ribosomal response. A notable finding is the effect of UVB on ribosome structure and function, which constitutes an under-explored area. Based on the results of this study, further analyses could utilize data with more detailed categorization, experimental validation, different techniques (ATAC-Seq, single-cell methods) as well as comparative analyses against the effects of different UVR spectra.
Main subject category:
Science
Keywords:
Bioinformatics, gene expression, nf-core, radiation, ribosomes, programming
Number of references:
161
File:
File access is restricted until 2027-04-15.
Thesis_ON.pdf
6 MB
File access is restricted until 2027-04-15.
