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Oxford nanopore technologies

What is nanopore sequencing?

Oxford Nanopore Technologies, as the name suggests, use biological nanopores embedded in silicon for long read sequencing of DNA and RNA. Sequencing is performed by the nucleic acid passing through the nanopore, causing changes in current depending on the sequence of bases that go through. Realtime computation can then call the bases (and potentially epigenetic base modifications such as methylation too).

How it works »

Long-read review article »

What we offer

In Exeter, we offer sequencing on the MinION for standard scale experiments and the ProMethION for larger scale sequencing. Most applications will benefit from shearing to between 5-20kb which increases the molarity and throughput. However, longer reads in the order of hundreds of kilobases or higher are possible but with reduced yield.

Nanopore sequencing offers:

  • Direct sequencing of DNA and RNA
  • Read accuracy of ~95% for DNA but multiple reads can lead to 99%+ consensus accuracy
  • Ability to predict base modifications, e.g. for DNA methylation of Adenine (m6A) and Cytosine (m5C)
  • Scalability: our equipment includes a Flongle, MinION, and PromethION. See below for more details.
  • Realtime basecalling

Scalability overview (from nanopore website):

 FlongleMinION Mk1BPromethION 24
Number of channels per flow cell 126 512 3000
Maximum number of flow cells per device run (Max flowcells with live basecalling) 1 (1) 1 (1) 24 (4)
Run time 1 min - 16 hours 1 min - 48 hours 1 min - 72 hours
DNA sequencing yield per flow cell (typical in field - best in field (BIF). Yields are also dependent on chosen sample and preparation methods) 0.5 - 2 Gb  15 - 30 Gb 50 - 180 Gb
Suitable applications include
  • Amplicons
  • Panels/targeted sequencing
  • Quality testing
  • Small sequencing tests
  • Whole genomes/exomes
  • Metagenomics
  • Targeted sequencing
  • Whole transcriptome (cDNA)
  • Smaller transcriptomes (direct RNA)
  • Multiplexing for smaller samples
  • Very large genomes or projects
  • Population-scale human
  • Whole transcriptomes
  • Very large numbers of samples