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Erschienen in: International Journal of Legal Medicine 1/2017

22.07.2016 | Original Article

Indel analysis by droplet digital PCR: a sensitive method for DNA mixture detection and chimerism analysis

verfasst von: Ana Santurtún, José A. Riancho, Jana Arozamena, Mónica López-Duarte, María T. Zarrabeitia

Erschienen in: International Journal of Legal Medicine | Ausgabe 1/2017

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Abstract

Several methods have been developed to determinate genetic profiles from a mixed samples and chimerism analysis in transplanted patients. The aim of this study was to explore the effectiveness of using the droplet digital PCR (ddPCR) for mixed chimerism detection (a mixture of genetic profiles resulting after allogeneic hematopoietic stem cell transplantation (HSCT)). We analyzed 25 DNA samples from patients who had undergone HSCT and compared the performance of ddPCR and two established methods for chimerism detection, based upon the Indel and STRs analysis, respectively. Additionally, eight artificial mixture DNA samples were created to evaluate the sensibility of ddPCR. Our results show that the chimerism percentages estimated by the analysis of a single Indel using ddPCR were very similar to those calculated by the amplification of 15 STRs (r 2 = 0.970) and with the results obtained by the amplification of 38 Indels (r 2 = 0.975). Moreover, the amplification of a single Indel by ddPCR was sensitive enough to detect a minor DNA contributor comprising down to 0.5 % of the sample. We conclude that ddPCR can be a powerful tool for the determination of a genetic profile of forensic mixtures and clinical chimerism analysis when traditional techniques are not sensitive enough.
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Metadaten
Titel
Indel analysis by droplet digital PCR: a sensitive method for DNA mixture detection and chimerism analysis
verfasst von
Ana Santurtún
José A. Riancho
Jana Arozamena
Mónica López-Duarte
María T. Zarrabeitia
Publikationsdatum
22.07.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Legal Medicine / Ausgabe 1/2017
Print ISSN: 0937-9827
Elektronische ISSN: 1437-1596
DOI
https://doi.org/10.1007/s00414-016-1422-4

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