Tonight I watched the Nanopore Community Meeting 2021 recording featuring Areeba Patel and titled “Rapid-CNS2: rapid, comprehensive adaptive nanopore sequencing of central nervous system (CNS) tumours.” Patel is at the German Cancer Research Center (DKFZ) and the University Hospital Heidelberg, Germany. Patel spoke about the use of molecular diagnostics for CNS tumors. They noted the timeline for conventional next-gen sequencing molecular diagnostics for CNS tumors. The proposed solution, Patel noted, is adaptive sampling .They used RapidFish, NVIDIA RTX 2080Ti 8Gb GPU, 1 sample per flow cell, and did 72 ht runs. They used the MinION Mk1B, MIN 106 R9.4.1 flow cells, and the SQK-LSK 109 ligation sequencing kit. The adaptive sampling is used to sequence targets from the panel and surrounding areas. Patel compared the conventional NGS timeline and the one using Nanopore sequencing. The bioinformatics pipeline used the NVIDIA RTX 2080Ti and a 64 core CPU. Patel and team processed 35 diffuse glioma samples. They compared the NGS panel sequencing, EPIC array, and the Rapid-CNS2 pipeline they developed. The concordance was very promising: they found complete concordance with key targets. While the system can be run on a MinION (pictured with an awesome Minion sticker!), the team plans on optimizing the workflow for the GridION. I wonder how they set up their adaptive sampling, and also how different the GridION library prep and turnaround will be.
