Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/436055
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dc.date.accessioned2023-01-04T08:17:36Z-
dc.date.available2023-01-04T08:17:36Z-
dc.identifier.urihttp://hdl.handle.net/10603/436055-
dc.description.abstractBacteria thrive in dynamic environments with their DNA facing a constant onslaught of damage. To combat these damages, genomes code for a toolkit of cellular responses, including DNA repair. Making a choice of DNA repair pathway is critical to ensure genome stability versus accuracy. Comparative genomics based studies have highlighted a variability in the repertoires of repair pathways coded across bacterial genomes. Even though we have started to gain mechanistic insights of how these repair pathways work at a molecular level, we still lack an understanding of the factors that dictate the employment of a given repair pathway over the other. newlineIn this light, some of the outstanding questions that we do not have answers to, include, how, when and why repair pathways came to be distributed across bacteria. Towards addressing these questions, we included two different repair pathways as case studies: 1. Non-homologous end joining (NHEJ), a template-independent double strand break repair pathway and 2. AlkB, an oxidative demethylase employed in nucleotide alkylation damage repair. We developed a workflow to understand the evolution of these two repair pathways using computational approaches like comparative genomics, phylogenetic comparative methods and machine learning. We found that shared ancestry is not sufficient to explain the incidence of proteins involved in both the repair mechanisms. Our work supports the hypothesis that sources of genome instability play an important role in dictating the evolutionary history of these DNA repair pathways across bacteria. newline newline
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dc.languageEnglish
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dc.rightsself
dc.titleComputational study of the evolution of bacterial DNA repair systems
dc.title.alternative
dc.creator.researcherSharda, Mohak
dc.subject.keywordBioinformatics
dc.subject.keywordBiostatistics
dc.subject.keywordComparative Genomics
dc.subject.keywordComputational Biology
dc.subject.keywordDNA repair systems
dc.subject.keywordEvolutionary Biology
dc.subject.keywordMachine Learning
dc.subject.keywordMicrobial Genomics
dc.subject.keywordPhylogenomics
dc.description.note
dc.contributor.guideSeshasayee, Aswin Sai Narain
dc.publisher.placeBangalore
dc.publisher.universityInstitute of Trans-disciplinary Health Science and Technology
dc.publisher.institutionCentre for Functional Genomics and Bio-informatics
dc.date.registered2017
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Centre for Functional Genomics & Bio-informatics

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01_title.pdfAttached File383.35 kBAdobe PDFView/Open
02_prelim_pages.pdf969.96 kBAdobe PDFView/Open
03_contents.pdf217.11 kBAdobe PDFView/Open
04_abstract.pdf306.15 kBAdobe PDFView/Open
05_chapter1.pdf300.3 kBAdobe PDFView/Open
06_chapter2.pdf931.7 kBAdobe PDFView/Open
07_chapter3.pdf1.87 MBAdobe PDFView/Open
08_chapter4.pdf976.79 kBAdobe PDFView/Open
09_chapter5.pdf259.54 kBAdobe PDFView/Open
10_annexures.pdf6.92 MBAdobe PDFView/Open
80_recommendation.pdf507.9 kBAdobe PDFView/Open


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