NCM 2022: Profiling complex somatic rearrangements in cancer genomes using nanopore sequencing
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Structural variations (SV) are large genomic alterations from simpler indels to complex events involving multiple breakpoints and sequence gain/loss with established importance in various diseases including neurodevelopment diseases and cancer. Recent pan-cancer studies with large cohorts revealed the rich landscape of structural variants (SV) some of which shown to be involved in tumorigenesis and prognosis through direct modification of coding sequence or deregulation from copy number alterations, enhancer hijacking. However, a substantial part of the SV in the cancer genome is yet to be discovered since even the best short-read-based SV calling methods can reach 30-70% sensitivity partially due to mapping ambiguities. Long-read sequencing can overcome these limitations of short reads, however the current methods were not designed for the analysis of rearranged cancer genomes with complex copy number profiles.
We developed Breakpoint Graph Assembler (BGA), utilizes long-read assembly and breakpoint graph frameworks to increase the detection capacity to cover SVs including complex events. BGA detects split reads from previously aligned bam files then builds a breakpoint graph that characterizes the structure of derived cancer karyotypes. Complex events with multiple breakpoints form connectivity clusters and are classified based on the subgraph properties. BGA also takes advantage of phased haplotypes and can incorporate multiple related datasets (such as in tumor-normal comparison or multi-site tumor sampling).
