Long-read Sequencing and Structural Variants in Precision Oncology

“Accelerating precision oncology research with nanopore sequencing” is the name of the session I watched tonight. Anna Dysko, Associate Director of Business Development with Oxford Nanopore Technologies, facilitated the discussion on April 8, 2024. Dysko explained how nanopore sequencing works: DNA or RNA is passed through a nanopore thanks to the action of a motor enzyme. The nanopore is on a supporting membrane, and tethers help catch molecules. Dysko mentioned that complex algorithms are used to deconvolute squiggles and produce base calls. Cancer research has used nanopore sequencing to explore structural variants, SNPs, indels, epigenomics, gene fusions, and chromatin conformation… Dysko stated that “precision oncology starts with the complete picture.” The first speakers included Mikhail Kolmogorov and Ayse Keskus from the National Institutes of Health. They spoke about the role of structural variation in cancer. They explained how long reads help resolve complex variants and can be phased. Osteosarcoma, explained Kolmogorov, occurs in children and is often driven by complex SV. The National Cancer Institute supports a Comparative Osteosarcoma (OS) Program. The team sequenced dog samples from tumors. The DNA was sheared, and they obtained an N50 of 30 kb. The goal was to obtain a comprehensive view of SV, SNP, methylation, and copy number. Keskus described the Severus tool they developed for long-read somatic SV calling. The tool has features for tumor only, tumor/normal, and multi-sample tumor. Severus was built on and for cancer multi-omics. Since there wasn’t a ground truth, the team created a confident call set based on two sequencing technologies. Keskus shared data comparing Illumina, ONT, and PacBio analysis with different cell lines. Structural variation can be identified and phased. Keskus shared data from Oliver’s chromosome five (dog) complex rearrangements. Wakhan is a haplotype-specific copy number caller. Kolmogorov ended by mentioning a Deep Somatic tool they are developing.

How does the Comparative Osteosarcoma Program at the NCI leverage bioinformatics and long-read sequencing? AI-generated image.