Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-3885
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dc.contributor.authorSell, Christian
dc.date.accessioned2017-05-03T09:24:25Z
dc.date.available2017-05-03T11:24:25Z
dc.date.issued2017
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/3887-
dc.description.abstractThis thesis addresses challenges in the bioinformatic analysis of palaeogenomes that were generated by Next Generation Sequencing of highly degrade ancient DNA from archaeological skeletal remains. It establishes a pipeline that incorporates a correction for postmortem damage as well as sequencing errors, to facilitate the comparison with sequence data from modern specimen. By applying the pipeline to published ancient genomes from the Aegean Neolithic and by comparing the results to data from the 1000 Genomes project, it could be shown that an excess of Cytosine to Thymine transitions linked to deaminations during the postmortem degradation of the DNA, can be reverted by bioinformatic processing. In another attempt to address the complexity and scarcity of DNA from prehistorical specimen, an in-solution hybridization enrichment was designed. This method can counteract the relatively low endogenous DNA content in samples from prehistoric human skeletal remains by selectively enriching specifically designed regions. The developed capture array was analyzed in 21 skeletal human remains from a Bronze Age battlefield, resulting in an average read depth of 1.71x over the whole genome. The statistical analysis of data produced by this approach enables genomic inferences similar to those based on full genomes. Third the thesis addresses the false assignments of individual bar-code-indices to sequence samples. In a data set comprising 38 capture enriched mitochondrial genomes from prehistoric human remains, it could be shown that this sequencing error can mimic a cross contamination event during lab work. By identifying and removing affected reads, false positive variants could be reduced from ~38% to 0%.en_GB
dc.language.isoeng
dc.rightsInCopyrightde_DE
dc.rights.urihttps://rightsstatements.org/vocab/InC/1.0/
dc.subject.ddc570 Biowissenschaftende_DE
dc.subject.ddc570 Life sciencesen_GB
dc.titleAddressing challenges of ancient DNA sequence data obtained with next generation methodsen_GB
dc.typeDissertationde_DE
dc.identifier.urnurn:nbn:de:hebis:77-diss-1000012793
dc.identifier.doihttp://doi.org/10.25358/openscience-3885-
jgu.type.dinitypedoctoralThesis
jgu.type.versionOriginal worken_GB
jgu.type.resourceText
jgu.description.extentiii, 109 Seiten
jgu.organisation.departmentFB 10 Biologie-
jgu.organisation.year2017
jgu.organisation.number7970-
jgu.organisation.nameJohannes Gutenberg-Universität Mainz-
jgu.rights.accessrightsopenAccess-
jgu.organisation.placeMainz-
jgu.subject.ddccode570
opus.date.accessioned2017-05-03T09:24:25Z
opus.date.modified2017-05-09T11:26:57Z
opus.date.available2017-05-03T11:24:25
opus.subject.dfgcode00-000
opus.organisation.stringFB 10: Biologie: Institut für Anthropologiede_DE
opus.identifier.opusid100001279
opus.institute.number1007
opus.metadataonlyfalse
opus.type.contenttypeDissertationde_DE
opus.type.contenttypeDissertationen_GB
jgu.organisation.rorhttps://ror.org/023b0x485
Appears in collections:JGU-Publikationen

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