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
Author Information
  1. Markus Joppich: LFE Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, 80333 München, Germany.
  2. Margaryta Olenchuk: LFE Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, 80333 München, Germany.
  3. Julia M Mayer: LFE Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, 80333 München, Germany.
  4. Quirin Emslander: Physics of Synthetic Biological Systems, Physics Department, Technische Universität München, 85748 Garching, Germany.
  5. Luisa F Jimenez-Soto: Walther Straub Institute for Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Goethestrasse 33, 80336 München, Germany.
  6. Ralf Zimmer: LFE Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, 80333 München, Germany.

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 , 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.

Keywords

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Word Cloud

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