Literature DB >> 24129073

Comparison of phi29-based whole genome amplification and whole transcriptome amplification in dengue virus.

Patcharawan Sujayanont1, Kwanrutai Chininmanu, Boonrat Tassaneetrithep, Nattaya Tangthawornchaikul, Prida Malasit, Prapat Suriyaphol.   

Abstract

Dengue virus is responsible for 50-100 million new infections annually worldwide. The virus uses error-prone RNA polymerase during genome replication in a host, resulting in the formation of closely related viruses known as quasispecies. The availability of next-generation sequencing technology provides opportunities to analyze viral quasispecies. Before analysis, it is crucial to increase the amount of DNA because of the limited amounts of viral genomic material that can be isolated from a patient. However, using specific primers may overlook the occurrence of possible variations at primer binding sites. To address this problem, the performance of two sequence-independent amplification methods was compared for whole genome amplification (WGA): phi29 DNA polymerase-based WGA and whole transcriptome amplification (WTA). Both methods have the ability to provide complete coverage of the dengue genome from template amounts as low as 1 ng. However, WTA showed greater efficiency in terms of yield (WTA: ~10 μg; phi29-based WGA: ~500 ng) and lower amplification bias. In conclusion, the WTA amplification kit was shown to perform substantially better than phi29 DNA polymerase-based WGA in terms of both final concentration and amplification bias in amplifying small genomes, such as that of the dengue virus.
Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Amplification bias; Dengue; WGA; WTA; Whole genome amplification; Whole transcriptome amplification; phi29; whole genome amplification; whole transcriptome amplification

Mesh:

Substances:

Year:  2013        PMID: 24129073     DOI: 10.1016/j.jviromet.2013.10.005

Source DB:  PubMed          Journal:  J Virol Methods        ISSN: 0166-0934            Impact factor:   2.014


  4 in total

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Authors:  Hong-Ying Wei; Sheng Huang; Jiang-Yong Wang; Fang Gao; Jing-Zhe Jiang
Journal:  Genes Genomics       Date:  2017-12-02       Impact factor: 1.839

2.  Workflow and web application for annotating NCBI BioProject transcriptome data.

Authors:  Roberto Vera Alvarez; Newton Medeiros Vidal; Gina A Garzón-Martínez; Luz S Barrero; David Landsman; Leonardo Mariño-Ramírez
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

3.  Complete Genome Sequence of West Nile Virus (WNV) from the First Human Case of Neuroinvasive WNV Infection in Cyprus.

Authors:  Jan Richter; Christina Tryfonos; Aristomenis Tourvas; Dora Floridou; Niki I Paphitou; Christina Christodoulou
Journal:  Genome Announc       Date:  2017-10-26

Review 4.  Adenoviromics: Mining the Human Adenovirus Species D Genome.

Authors:  Ashrafali M Ismail; Ji Sun Lee; Jeong Yoon Lee; Gurdeep Singh; David W Dyer; Donald Seto; James Chodosh; Jaya Rajaiya
Journal:  Front Microbiol       Date:  2018-09-11       Impact factor: 5.640

  4 in total

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