Closing the Gaps, and Improving Somatic Structural Variant Analysis and Benchmarking Using CHM13-T2T.

The complexities of cancer genomes are becoming more easily interpreted due to advancements in sequencing technologies and improved bioinformatic analysis. Structural variants (SVs) represent an important subset of somatic events in tumors. While the detection of SVs has been markedly improved by the development of long-read sequencing, somatic variant identification and annotation remain challenging. We hypothesized that the use of a completed human reference genome (CHM13-T2T) would improve somatic SV calling. Our findings in a tumor-normal matched benchmark sample and three patient samples show that the CHM13-T2T improves SV detection accuracy compared to GRCh38 with a notable reduction in false-positive calls, and thus supports improved prioritization. We also overcame the lack of annotation resources for CHM13-T2T by lifting over CHM13-T2T-aligned reads to the GRCh38 genome, therefore combining both improved alignment and advanced annotations. In this process, we assessed the current SV benchmark set for COLO829/COLO829BL across four replicates sequenced at different centers with different long-read technologies. We discovered instability of this cell line across these replicates; 346 SVs (1.13%) were only discoverable in a single replicate. We identify 54 somatic SVs, which appear to be stable as they are consistently present across the four replicates. As such, we propose this consensus set as an updated benchmark for somatic SV calling and include both GRCh38 and CHM13-T2T coordinates in our benchmark. Our work demonstrates new approaches to optimize somatic SV detection in cancer with potential improvements in other genetic diseases.