Nanopore sequencers can be used to selectively sequence certain DNA molecules in a pool by reversing the voltage across individual nanopores to reject specific sequences, enabling enrichment and depletion to address biological questions. Previously, we achieved this using dynamic time warping to map the signal to a reference genome, but the method required substantial computational resources and did not scale to gigabase-sized references. Here we overcome this limitation by using GPU base calling. We show enrichment of specific chromosomes from the human genome and of low-abundance organisms in mixed populations without a priori knowledge of sample composition. Finally, we enrich targeted panels comprising 25,600 exons from 10,000 human genes and 717 genes implicated in cancer, identifying PML-RARA fusions in the NB4 cell line in <15 hours sequencing. These methods can be used to efficiently screen any target panel of genes without specialised sample preparation using any computer and suitable GPU. Our toolkit, readfish, is available at https://www.github.com/looselab/readfish .
Nanopore sequencers enable selective sequencing of single molecules in real time by individually reversing the voltage across specific nanopores. Thus DNA molecules can be rejected and replaced with new molecules enabling targeted sequencing to enrich, deplete or achieve specific coverage in a set of reads to address a biological question. We previously demonstrated this method worked using dynamic time warping mapping signal to reference, but required significant compute and did not scale to gigabase references. Using direct base calling with GPU we can now scale to gigabase references. We enrich for specific chromosomes mapping against the human genome and we develop pipelines enriching low abundance organisms from mixed populations without prior knowledge of sample composition. Finally, we enrich panels including 25,600 exon targets from 10,000 human genes and 717 genes implicated in cancer. Using this approach we identify PML-RARA fusions in the NB4 cell line in under 15 hours sequencing. These methods can be used to efficiently screen any target panel of genes without specialised sample preparation using a single computer and suitably powerful GPU.
Nanopore sequencers can select which DNA molecules to sequence, rejecting a molecule after analysis of a small initial part. Currently, selection is based on predetermined regions of interest that remain constant throughout an experiment. Sequencing efforts, thus, cannot be re-focused on molecules likely contributing most to experimental success. Here we present BOSS-RUNS, an algorithmic framework and software to generate dynamically updated decision strategies. We quantify uncertainty at each genome position with real-time updates from data already observed. For each DNA fragment, we decide whether the expected decrease in uncertainty that it would provide warrants fully sequencing it, thus optimizing information gain. BOSS-RUNS mitigates coverage bias between and within members of a microbial community, leading to improved variant calling; for example, low-coverage sites of a species at 1% abundance were reduced by 87.5%, with 12.5% more single-nucleotide polymorphisms detected. Such data-driven updates to molecule selection are applicable to many sequencing scenarios, such as enriching for regions with increased divergence or low coverage, reducing time-to-answer.
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