Abderaouf Hamza from the Institut Curie in France spoke at the Nanopore London Calling event last year about “Targeted nanopore sequencing ushers in the era of routine long-read sequencing in translational research laboratories.” This ten-minute session started with how Hamza uses nanopore sequencing for cancer genomics, particularly using adaptive sampling. They use target region enrichment with adaptive sampling to sequence panels of target genes. The team set up two MinION Mk1B sequencers using R9 flow cells and the SQK LSK 110 kits. The workstations had NVIDIA Quadro RTX8000 cards. Importantly for these studies, they used DNA extracted “during routine medical care: 2 ug.” This material included extracting DNA from tumor cells manually using phenol-chloroform extraction and from blood using a column-based manual extraction or bead-based automated extraction. The target regions sequenced included a pan-cancer gene panel with 360 genes and 10 kb flanking regions totalling about 1.5% of the reference genome. They based this design on a diagnostic panel of over 500 genes. They use a custom bioinformatics pipeline with extensive polishing. Hamza summarized their sequencing attempts as 38 adaptive sampling runs with six sequencing failures. They noted that “most sub-optimal experiments still provided a wealth of data.” As I may have expected, the main factor was the sample type. Hamza noted that phenol residue inhibits nanopore sequencing. They used adaptive sampling and compared it to other methods to detect structural variants. In the future, the group will study tumor genomes and they will compare samples and reduce costs. I haven’t used adaptive sampling, though I think it will be helpful for some metagenomic tasks.
