SEQU-INTO: Early detection of impurities, contamination and off-targets (ICOs) in long read/MinION sequencing

  • Markus Joppich
  • , Margaryta Olenchuk
  • , Julia M. Mayer
  • , Quirin Emslander
  • , Luisa F. Jimenez-Soto
  • , Ralf Zimmer*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The MinION sequencer by Oxford Nanopore Technologies turns DNA and RNA sequencing into a routine task in biology laboratories or in field research. For downstream analysis it is required to have a sufficient amount of target reads. Especially prokaryotic or bacteriophagic sequencing samples can contain a significant amount of off-target sequences in the processed sample, stemming from human DNA/RNA contamination, insufficient rRNA depletion, or remaining DNA/RNA from other organisms (e.g. host organism from bacteriophage cultivation). Such impurity, contamination and off-targets (ICOs) block read capacity, requiring to sequence deeper. In comparison to second-generation sequencing, MinION sequencing allows to reuse its chip after a (partial) run. This allows further usage of the same chip with more sample, even after adjusting the library preparation to reduce ICOs. The earlier a sample's ICOs are detected, the better the sequencing chip can be conserved for future use. Here we present sequ-into, a low-resource and user-friendly cross-platform tool to detect ICO sequences from a predefined ICO database in samples early during a MinION sequencing run. The data provided by sequ-into empowers the user to quickly take action to preserve sample material and chip capacity. sequ-into is available from https://github.com/mjoppich/sequ-into

Original languageEnglish
Pages (from-to)1342-1351
Number of pages10
JournalComputational and Structural Biotechnology Journal
Volume18
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Bioinformatics
  • Contamination
  • Nanopore Sequencing
  • User-friendly

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