Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.693989
Title: The in silico identification and analysis of ancient and recent endogenous retroviruses in mammalian genomes
Author: Lee, Adam
ISNI:       0000 0004 5989 5654
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Abstract:
Recent advances in DNA sequencing technologies have led to a vast plethora of vertebrate genomes being made available for bioinformatic analysis and investigation. This has presented retrovirologists with many new opportunities to study endogenous retroviruses (ERVs) - selfish genetic element (SGEs) endogenised within the genomic DNA of their hosts. Many of these ERVs exist as molecular fossils of past germline infections by their exogenous counterparts, representing approximately 8-10% of mammalian genomes. While the majority are thought to be inactive today, one particular retroviral group - HERV-K(HML-2) - has been implicated in recent activity. In this thesis, efficient, synergistic in silico techniques have been implemented, with which intensive, genome-wide retroviral screens were performed. This has culminated in the identification of 11 novel, insertionally polymorphic human ERVs (HERVs), belonging to the HERV-K(HML-2) lineage, in two high- coverage archaic hominid genomes. This thesis also identifies the oldest ERV described to date - orthologous across all placental mammals - estimated to have endogenised in the germline of an ancestral mammal, 128-140 million years ago. Three SGEs, found to be endogenised within this ancient ERV, have also been described and assigned a minimum age of 104 million years, making these the oldest, definitively dated SGEs. This thesis also presents a computer program for renaming all identified ERVs in vertebrate genomes, according to a newly designed nomenclature standard to be implemented globally, that aims to unambiguously catalogue all the ERVs identified, to date.
Supervisor: Tristem, Michael Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.693989  DOI: Not available
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