De novo detection of somatic variants in long-read single-cell RNA sequencing data

In cancer, genetic and transcriptomic variations generate clonal heterogeneity, possibly leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), copy-number alterations (CNAs), and gene fusions to reconstruct the tumor clonal heterogeneity. For SNV calling, LongSom distinguishes somatic SNVs from germline polymorphisms by reannotating marker gene expression-based cell types using called variants and applying strict filters. Applying LongSom to ovarian cancer samples, we detected clinically relevant somatic SNVs that were validated against single-cell and bulk panel DNA-seq data and could not be detected with short-read (SR) scRNA-seq. Leveraging somatic SNVs and fusions, LongSom found subclones with different predicted treatment outcomes. In summary, LongSom enables de novo SNVs, CNAs, and fusions detection, thus enabling the study of cancer evolution, clonal heterogeneity, and treatment resistance. ### Competing Interest Statement The authors have declared no competing interest. The raw sequencing files, as well as the associated analysis files reported in this study are available in the European Genome-phenome Archive (EGA) under the accession number EGAS00001006807. Gencode v36 gene annotation used in this study is available at [https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode\_human/release\_36/gencode.v36.annotation.gtf.gz][1]. All additional information will be made available upon reasonable request to the authors. Marker genes for cancer and non-cancer cells are available at [https://github.com/ETH-NEXUS/scAmpi\_single\_cell\_RNA/blob/master/required\_files/ovarian/celltype\_list\_ovarian.gmx][2]. [1]: https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_36/gencode.v36.annotation.gtf.gz [2]: https://github.com/ETH-NEXUS/scAmpi_single_cell_RNA/blob/master/required_files/ovarian/celltype_list_ovarian.gmx