Yutaka Suzuki presented from the University of Tokyo, Japan at the Nanopore Community Meeting 2021 on “Phasing analysis of lung cancer genomes using PromethION R10.4.” Suzuki is in charge of the sequencing core lab at the University of Tokyo. The core uses a lot of PromethION flow cells, as was apparent by the photo they shared. They also work with the National Cancer Center East Hospital for clinical trials. From the academic side, Suzuki’s lab supports research laboratories and they have published on long read methylation. Suzuki has published reviews on long-read sequencing technologies. Suzuki and team wanted to learn about the chromosomal background of cancerous mutations by asking:
- Are homologous chromosomes found in an equivalent condition?
- Are cancerous mutations (SNVs/SVs) evenly distributed on homologous chromosomes?
To address these questions, they prepared a dataset analyzed with PromethION and NovaSeq sequencing. The dataset included tumorous and healthy whole genome sequencing. They focused on the phasing results of tumor and healthy samples. They compared tumor and healthy patient samples. Suzuki and team compared several datasets. Interestingly, they concluded that “Q20 may not contribute to improved phasing: Limited contribution to the phase length?” They also reviewed deletions of key genes and compared chromosomal backgrounds from different samples. Using PromethION sequencing run, the team also studied haplotype-specific transcription and methylation patterns for their samples. They then looked for “mutation signatures” of “haplotype-biased” SNVs. Summarizing their efforts analysing phasing of 20 cases of lung invasive lung cancers, the SVs and SNVs identified previously could be phased along with transcriptome and epigenome information. Interestingly, they detected biased distribution of SNVs and SVs which “may be caused by an allele specific event, which resembles chromothripsis or kataegis)”. Their raw data sets are available at: http://dbkero.hgc.jp/ Suzuki and team have done extensive sequencing of this and other datasets and identified SNVs and phasing events. The dataset they created and shared may be useful for student activities.
