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Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126183/ https://www.ncbi.nlm.nih.gov/pubmed/32245400 http://dx.doi.org/10.1186/s12859-020-3461-6 |
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author | Shityakov, Sergey Bencurova, Elena Förster, Carola Dandekar, Thomas |
author_facet | Shityakov, Sergey Bencurova, Elena Förster, Carola Dandekar, Thomas |
author_sort | Shityakov, Sergey |
collection | PubMed |
description | 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 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. GRAPHICAL ABSTRACT: [Image: see text] |
format | Online Article Text |
id | pubmed-7126183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71261832020-04-10 Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches Shityakov, Sergey Bencurova, Elena Förster, Carola Dandekar, Thomas BMC Bioinformatics Software 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 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. GRAPHICAL ABSTRACT: [Image: see text] BioMed Central 2020-04-03 /pmc/articles/PMC7126183/ /pubmed/32245400 http://dx.doi.org/10.1186/s12859-020-3461-6 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Shityakov, Sergey Bencurova, Elena Förster, Carola Dandekar, Thomas Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title | Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title_full | Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title_fullStr | Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title_full_unstemmed | Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title_short | Modeling of shotgun sequencing of DNA plasmids using experimental and theoretical approaches |
title_sort | modeling of shotgun sequencing of dna plasmids using experimental and theoretical approaches |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126183/ https://www.ncbi.nlm.nih.gov/pubmed/32245400 http://dx.doi.org/10.1186/s12859-020-3461-6 |
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