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Author: Sell, Christian (Author) 
Title: Addressing challenges of ancient DNA sequence data obtained with next generation methods
100001279.pdf (4.303 KB) PDF
Source: Mainz : Univ. iii, 109 Seiten
Year of publication: 2017
URN: urn:nbn:de:hebis:77-diss-1000012793
Document type:
Book Book
Further document specification: Dissertation
Language: English
Open Access: OpenAccess
Institution: Institut für Anthropologie
DDC subject area: Life sciences
ID: 100001279  Universitätsbibliothek Mainz
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Abstract: This 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%.
Check availability: URN (urn:nbn:de:hebis:77-diss-1000012793)

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