Nanopore Adaptive Sampling for pneumococcal surveillance
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PROVIDER: PRJEB72455 | ENA |
REPOSITORIES: ENA
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Project description:DNA sequencing using nanopore technologies with the affordable MinION device is useful for the identification and characterization of structural variants, long haplotypes, sequencing of repetitive regions and identification of epigenetic modifications. The main limitation of this approach is the low coverage obtained, which might be avoided by adaptive sampling, a computationally controlled method of enrichment for targeted genomic regions. This study dissects the factors involved in the enrichment by adaptive sampling of a panel of 18 human genome regions containing 20 genes implicated in breast cancer sequenced in 16 patients with familial breast cancer negative for NGS screening. An average coverage of 2.0x was obtained for the whole genome and 5.1x for selected regions. Sequencing time was the main factor improving coverage. The selection of long reads (>1 Kb) did not improve the enrichment. The length of the selected region, which in our study ranged from 126 to 565 Kb, did not play a significant role in enrichment. However, the region containing PMS2 showed significantly lower coverage, which could be explained by the high number of PMS2 pseudogenes (N = 14), which were also enriched. Our study shows new evidence of enrichment obtained by adaptive sampling in a panel of genomic regions and shows parameters, the relevance of sequencing time and the role of pseudogenes, that improve the enrichment yield with no library reloading or GPU use, data useful for a more efficient application of this procedure in future studies.
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Project description:MotivationNanopore 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.ResultsHere, 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 implementationThe C++ source code is available at https://gitlab.com/dacs-hpi/readbouncer.Supplementary informationSupplementary data are available at Bioinformatics online.
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2013-01-01 | GSE41098 | GEO