Nanopore sequencing technology, bioinformatics and applications

Abstract

Rapid advances in nanopore technologies for sequencing single long DNA and RNA molecules have led to substantial improvements in accuracy, read length and throughput. These breakthroughs have required extensive development of experimental and bioinformatics methods to fully exploit nanopore long reads for investigations of genomes, transcriptomes, epigenomes and epitranscriptomes. Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance. Many opportunities remain for improving data quality and analytical approaches through the development of new nanopores, base-calling methods and experimental protocols tailored to particular applications.

Fig. 1 |. Principle of nanopore sequencing.

A MinION flow cell contains 512 channels with 4 nanopores in each channel, for a total of 2,048 nanopores used to sequence DNA or RNA. The wells are inserted into an electrically resistant polymer membrane supported by an array of microscaffolds connected to a sensor chip. Each channel associates with a separate electrode in the sensor chip and is controlled and measured individually by the application-specific integration circuit (ASIC). Ionic current passes through the nanopore because a constant voltage is applied across the membrane, where the trans side is positively charged. Under the control of a motor protein, a double-stranded DNA (dsDNA) molecule (or an RNA–DNA hybrid duplex) is first unwound, then single-stranded DNA or RNA with negative charge is ratcheted through the nanopore, driven by the voltage. As nucleotides pass through the nanopore, a characteristic current change is measured and is used to determine the corresponding nucleotide type at ~450 bases per s (R9.4 nanopore).

Fig. 2 |. ONT sequencing data improvement over time.

a, Timeline of the major chemistry and platform releases by ONT. b, Accuracy of 1D, 2D and 1D² reads. c, Average and maximum read lengths. Special efforts have been made in some studies to achieve ultralong read length. For example, by late 2019, the highest average sequencing length achieved has been 23.8 kilobases (kb) using a specific DNA extraction protocol. The longest individual read is 2,273 kb, rescued by correcting an error in the software MinKNOW. The DNA extraction and purification methods used in these independent studies are summarized in Supplementary Table 1. Read lengths are reported for 1D reads. d, Yield per flow cell (in log₁₀) scale for y axis). Yields are reported for 1D reads. Data points shown in b (accuracy), c (read length) and d (yield) are from independent studies. Details for these data points are summarized in Supplementary Table 1.

Fig. 3 |. Library preparation workflow for ONT sequencing.

a, Special experimental techniques for ultralong genomic DNA sequencing, including HMW DNA extraction, fragmentation and size selection. b, Full-length cDNA synthesis for direct cDNA sequencing (without a PCR amplification step) and PCR-cDNA sequencing (with a PCR amplification step). c, Direct RNA-sequencing library preparation with or without a reverse transcription step, where only the RNA strand is ligated with an adapter and thus only the RNA strand is sequenced. d, Different library preparation strategies for DNA/cDNA sequencing, including 2D (where the template strand is sequenced, followed by a hairpin adapter and the complement strand), 1D (where each strand is ligated with an adapter and sequenced independently) and 1D² (where each strand is ligated with a special adapter such that there is a high probability that one strand will immediately be captured by the same nanopore following sequencing of the other strand of dsDNA); SRE, short read eliminator kit (Circulomics).

Fig. 4 |. Analyses of ONT sequencing data.

Typical bioinformatics analyses of ONT sequencing data, including the raw current data-specific approaches (for example, quality control, base calling and DNA/RNA modification detection), and error-prone long read-specific approaches (in dashed boxes; for example, error correction, de novo genome assembly, haplotyping/phasing, structural variation (SV) detection, repetitive region analyses and transcriptome analyses).

Fig. 5 |. Applications of ONT sequencing.

ONT sequencing applications are classified into three major groups (basic research, clinical usage and on-site applications) and are shown as a pie chart. The classifications are further categorized by specific topics, and the slice area is proportional to the number of publications (in log₂ scale). Some applications span two categories, such as SV detection and rapid pathogen detection. The applications are also organized by the corresponding strengths of ONT sequencing as three layers of the pie chart: (1) long read length, (2) native single molecule and (3) portable, affordable and real time. The width of each layer is proportional to the number of publications (in log₂ scale). Some applications that use all three strengths span all three layers (for example, antimicrobial resistance profiling). ‘Fungus’ includes Candida auris, ‘bacterium’ includes Salmonella, Neisseria meningitidis and Klebsiella pneumoniae and ‘virus’ includes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Ebola, Zika, Venezuelan equine encephalitis, yellow fever, Lassa fever and dengue; HLA, human leukocyte antigens.