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Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches

Please always quote using this URN: urn:nbn:de:bvb:20-opus-229169
  • Background Processing and analysis of DNA sequences obtained from next-generation sequencing (NGS) face some difficulties in terms of the correct prediction of DNA sequencing outcomes without the implementation of bioinformatics approaches. However, algorithms based on NGS perform inefficiently due to the generation of long DNA fragments, the difficulty of assembling them and the complexity of the used genomes. On the other hand, the Sanger DNA sequencing method is still considered to be the most reliable; it is a reliable choice for virtualBackground Processing and analysis of DNA sequences obtained from next-generation sequencing (NGS) face some difficulties in terms of the correct prediction of DNA sequencing outcomes without the implementation of bioinformatics approaches. However, algorithms based on NGS perform inefficiently due to the generation of long DNA fragments, the difficulty of assembling them and the complexity of the used genomes. On the other hand, the Sanger DNA sequencing method is still considered to be the most reliable; it is a reliable choice for virtual modeling to build all possible consensus sequences from smaller DNA fragments. Results In silico and in vitro experiments were conducted: (1) to implement and test our novel sequencing algorithm, using the standard cloning vectors of different length and (2) to validate experimentally virtual shotgun sequencing using the PCR technique with the number of cycles from 1 to 9 for each reaction. Conclusions We applied a novel algorithm based on Sanger methodology to correctly predict and emphasize the performance of DNA sequencing techniques as well as in de novo DNA sequencing and its further application in synthetic biology. We demonstrate the statistical significance of our results.show moreshow less

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Metadaten
Author: Sergey ShityakovORCiD, Elena Bencurova, Carola Förster, Thomas Dandekar
URN:urn:nbn:de:bvb:20-opus-229169
Document Type:Journal article
Faculties:Medizinische Fakultät / Klinik und Poliklinik für Anästhesiologie (ab 2004)
Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):BMC Bioinformatics
Year of Completion:2020
Volume:2020
Article Number:132
Source:BMC Bioinformatics (2020) 21:132 https://doi.org/10.1186/s12859-020-3461-6
DOI:https://doi.org/10.1186/s12859-020-3461-6
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:Gene expression vectors; Polymerase chain reaction; Sanger sequencing; Shotgun method; Synthetic biology; Virtual sequencing
Release Date:2021/04/14
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2020
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International