Stephen Meyn from the Center for Human Genomics and Precision Medicine at the University of Wisconsin-Madison presented at London Calling 2024. The session title was “BadgerSeq: a deecentralized model for ultra-rapid, long-read, whole-genome sequencing.” Meyn spoke about rare genetic disorders in the NICU and the importance of diagnosis. Meyn emphasized the need for speed and how equity is an issue with institutions without, for example, sequence to genetic sequencing. They used a local children’s hospital with a two-week turnaround as an example. BadgerSeq aims to address the challenges of turnaround and cost. It is an AI-assisted patient selection and local Nanopore WGS with AI variant analysis. They are sequencing on a PromethION P24, with each genome in two flow cells. After DNA extraction and library prep (3-4 hours), sequencing is performed for 36 hours. The analysis uses a modified EPI2ME workflow on a local HPC. After that, additional analyses are cloud-based using Fabric. Meyn shared examples of clinical cases and diagnoses. They shared that they are working to improve DNA extraction/size selection/library preparation to obtain higher-yield libraries in two hours or less. They also aim to improve the transfer of files between the PromethION and the HPC… and then to the cloud. I find rapid sequencing for diagnosis a fascinating area of research. The improvements will help research labs… and educators perform exciting and powerful analyses quickly!
