Dataset Information

ReadBouncer: precise and scalable adaptive sampling for nanopore sequencing.

ABSTRACT:

Motivation

Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications.

Results

Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without GPUs, making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background.

Availability and implementation

The C++ source code is available at https://gitlab.com/dacs-hpi/readbouncer.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Ulrich JU

PROVIDER: S-EPMC9235500 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundBlood-feeding insects are important vectors for an array of zoonotic pathogens. While previous efforts toward generating molecular resources have largely focused on major vectors of global medical and veterinary importance, molecular data across a large number of hematophagous insect taxa remain limited. Advancements in long-read sequencing technologies and associated bioinformatic pipelines provide new opportunities for targeted sequencing of insect mitochondrial (mt) genomes. For engorged hematophagous insects, such technologies can be leveraged for both insect mitogenome genome assembly and identification of vertebrate blood-meal sources.MethodsWe used nanopore adaptive sampling (NAS) to sequence genomic DNA from four species of field-collected, blood-engorged mosquitoes (Aedes and Culex spp.) and one deer fly (Chrysops sp.). NAS was used for bioinformatical enrichment of mtDNA reads of hematophagous insects and potential vertebrate blood-meal hosts using publically available mt genomes as references. We also performed an experimental control to compare results of traditional non-NAS nanopore sequencing to the mt genome enrichment by the NAS method.ResultsComplete mitogenomes were assembled and annotated for all five species sequenced with NAS: Aedes trivittatus, Aedes vexans, Culex restuans, Culex territans and the deer fly, Chrysops niger. In comparison to data generated during our non-NAS control experiment, NAS yielded a substantially higher proportion of reference-mapped mtDNA reads, greatly streamlining downstream mitogenome assembly and annotation. The NAS-assembled mitogenomes ranged in length from 15,582 to 16,045 bp, contained between 78.1% and 79.0% A + T content and shared the anticipated arrangement of 13 protein-coding genes, two ribosomal RNAs, and 22 transfer RNAs. Maximum likelihood phylogenies were generated to further characterize each insect species. Additionally, vertebrate blood-meal analysis was successful in three samples sequenced, with mtDNA-based phylogenetic analyses revealing that blood-meal sources for Chrysops niger, Culex restuans and Aedes trivittatus were human, house sparrow (Passer domesticus) and eastern cottontail rabbit (Sylvilagus floridanus), respectively.ConclusionsOur findings show that NAS has dual utility to simultaneously molecularly identify hematophagous insects and their blood-meal hosts. Moreover, our data indicate NAS can facilitate a wide array of mitogenomic systematic studies through novel 'phylogenetic capture' methods. We conclude that the NAS approach has great potential for broadly improving genomic resources used to identify blood-feeding insects, answer phylogenetic questions and elucidate complex pathways for the transmission of vector-borne pathogens.