Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries.
DNA assembly
nanopore sequencing
next-generation sequencing
strand bias
synthetic biology
Journal
Synthetic biology (Oxford, England)
ISSN: 2397-7000
Titre abrégé: Synth Biol (Oxf)
Pays: England
ID NLM: 101728857
Informations de publication
Date de publication:
2019
2019
Historique:
received:
08
07
2019
revised:
01
10
2019
accepted:
03
10
2019
entrez:
30
9
2020
pubmed:
1
10
2020
medline:
1
10
2020
Statut:
epublish
Résumé
Synthetic biology utilizes the Design-Build-Test-Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from
Identifiants
pubmed: 32995546
doi: 10.1093/synbio/ysz025
pii: ysz025
pmc: PMC7445882
doi:
Types de publication
Journal Article
Langues
eng
Pagination
ysz025Subventions
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/M017702/1
Pays : United Kingdom
Informations de copyright
© The Author(s) 2019. Published by Oxford University Press.
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