CarrierSeq: a sequence analysis workflow for low-input nanopore sequencing

Abstract

MotivationLong-read nanopore sequencing technology is of particular significance for taxonomic identification at or below the species level. For many environmental samples, the total extractable DNA is far below the current input requirements of nanopore sequencing, preventing \"sample to sequence\" metagenomics from low-biomass or recalcitrant samples.\n\nResultsHere we address this problem by employing carrier sequencing, a method to sequence low-input DNA by preparing the target DNA with a genomic carrier to achieve ideal library preparation and sequencing stoichiometry without amplification. We then use CarrierSeq, a sequence analysis workflow to identify the low-input target reads from the genomic carrier. We tested CarrierSeq experimentally by sequencing from a combination of 0.2 ng Bacillus subtilis ATCC 6633 DNA in a background of 1 g Enterobacteria phage {lambda} DNA. After filtering of carrier, low quality, and low complexity reads, we detected target reads (B. subtilis), contamination reads, and \"high quality noise reads\" (HQNRs) not mapping to the carrier, target or known lab contaminants. These reads appear to be artifacts of the nanopore sequencing process as they are associated with specific channels (pores). By treating reads as a Poisson arrival process, we implement a statistical test to reject data from channels dominated by HQNRs while retaining target reads.\n\nAvailabilityCarrierSeq is an open-source bash script with supporting python scripts which leverage a variety of bioinformatics software packages on macOS and Ubuntu. Supplemental documentation is available from Github - https://github.com/amojarro/carrierseq. In addition, we have compiled all required dependencies in a Docker image available from - https://hub.docker.com/r/mojarro/carrierseq.