Autoren:	Schoonenberg, Vivien Antoinette Catharina
Hauptberichter:	Butter, Falk
Titel:	Computational analysis of quantitative “omics” data
Online-Publikationsdatum:	1-Feb-2024
Erscheinungsdatum:	2024
Sprache des Dokuments:	Englisch
Zusammenfassung/Abstract:	Over the past decades, the rise of "omics" approaches has allowed for systematic, in-depth investigation of each aspect of molecular biology. It has contributed to our changed view on the on the linearity and the regulation of the informational flow of the central dogma. Different regulatory mechanisms have been identified, describing interaction and variety not only on the genetic level but also on the transcript and protein level. The development and integration of multi-omics have allowed for the uncovering of intricate molecular mechanisms underlying different phenotypic manifestations of traits at a high accuracy, in a systematic manner. With this, multi-omics is essentially the basis of network or systems biology. In this thesis, I have utilized "omics" technologies, specifically proteomics, and the subsequent computational data analysis and integration to investigate the systematic DNA damage response in Tetrahymena thermophila and identify DNA damage proteins across the Tree of Life. Additionally, I co-developed a user-friendly computational pipeline for evolutionary positive selection analysis, which relies on comparative genomics and either large-scale genome sequencing or proteotranscriptomics data. In Chapter 2, we mapped the system's response to DNA damage over time in Tetrahymena thermophila (Nischwitz, Schoonenberg et al., in preparation). To date, limited studies have combined the strength of proteomics and transcriptomics to investigate DNA damage kinetics in response to various DNA-damage treatments. Our study investigated DNA damage response (DDR) dynamics over eight hours after or during exposure to six different mutagens. We observed upregulation of previously identified DNA damage repair pathways and found novel crosstalk between DDR pathways. All treatments induced a dynamic response at both the transcript and protein levels. Using unsupervised self-organizing maps, we examined the clustering of expression profile trends to better understand the DDR. Many of the quantified proteins and transcripts exhibited damage-specific responses. We are currently employing a novel knockdown system to target a subset of PARP-related proteins to characterize their specific roles in Tetrahymena further. In Chapter 3, we studied the interactome of specific DNA damage lesions across the Tree of Life, exploring the conservation of pathways responsible for repair and recognition of DNA damage lesions (Nischwitz, Schoonenberg et al., iScience, 2023). Due to the need for precise genome maintenance, DNA repair has been highly conserved across all domains of life. To study the shared and unique elements of the DNA damage response, we performed a phylointeractomic study to identify enriched DNA damage binders in 11 different species at the 8-oxoG and abasic lesions and at a uracil base incorporated into DNA. Our approach identified several known DNA damage factors as binders to the afore-mentioned lesions. Additionally, through orthology, network, and domain analysis, we linked 44 previously unassociated proteins to DNA repair. Finally, in Chapter 4, we developed a computational pipeline to make positive selection analysis user-friendly (Ceron-Noriega et al., Genome Biology and Evolution, 2023). AlexandrusPS generates orthology relationships, sequence alignments, and phylogenetic trees with its automated process. It then performs site-specific (SSM), branch (BM), and branch-site (BSM) positive selection analyses and produces four main output files, including orthology relationships, positive selection results, and all intermediate files (sequence alignments, phylogenetic trees).
DDC-Sachgruppe:	570 Biowissenschaften 570 Life sciences
Veröffentlichende Institution:	Johannes Gutenberg-Universität Mainz
Organisationseinheit:	FB 10 Biologie
Veröffentlichungsort:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-9902
URN:	urn:nbn:de:hebis:77-openscience-fdfa1b6c-9f8b-44c6-87b9-b9a5680a71946
Version:	Original work
Publikationstyp:	Dissertation
Nutzungsrechte:	CC BY-ND
Informationen zu den Nutzungsrechten:	https://creativecommons.org/licenses/by-nd/4.0/
Umfang:	xiv, 137 Seiten ; Illustrationen, Diagramme
Enthalten in den Sammlungen:	JGU-Publikationen