B-G.52: Somatic variant detection using a personalized pangenome reference: a study of a paediatric acute myeloid leukaemia patient
Authors
Mark van Roosmalen
Prinses Máxima Centrum for Pediatric Oncology and Oncode Institute
Rico Hagelaar
Prinses Máxima Centrum for Pediatric Oncology and Oncode Institute
Eline Bertrums
Prinses Máxima Centrum for Pediatric Oncology and Oncode Institute
Andrea Guarracino
Bioinnovation and Genome Sciences, Translational Genomics Research Institute (TGen), part of City of Hope
Ruben van Boxtel
Prinses Máxima Centrum for Pediatric Oncology and Oncode Institute
Keywords
Pangenomics; cancer genomics; pediatric cancer; somatic variant calling
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Current clinical pipelines using linear reference genomes cause reads carrying mutations to be misaligned or lost, which is particularly problematic for low-coverage assays like single-cell whole-genome sequencing (scWGS), where technical noise can interfere with true somatic events. To overcome this, we applied a haplotype-resolved pangenome reference to a paediatric acute myeloid leukaemia (pAML) case and assessed the clinical utility of this approach.
We constructed a personalized pangenome from long-read Nanopore sequencing of healthy haematopoietic stem and progenitor cells, incorporating two haplotype-resolved assemblies with Minigraph-Cactus. This added 36.3 Mb of novel sequence, 42% of which represented variation absent from the standard hg38 reference. We compared somatic variant calling across bulk, clonally expanded, and single-cell WGS data of healthy and cancerous cells. Reference bias in pangenome alignments was quantified using Biastools and found to be significantly reduced compared to linear alignments.
The personalized pangenome reduced reads with mates mapped to different chromosomes up to 8,000-fold which allowed more accurate split-read event detection and remapping of previously ambiguous alignments. It also rescued SNVs previously filtered out by mapping quality thresholds and eliminated up to 80% of short indels in low-complexity regions. Driver analysis revealed that frameshift insertion artifacts in scWGS data were largely removed, and the medically relevant and computationally challenging PRSS1 locus was substantially disentangled due to reduced misalignment.
Our findings provide systematic evidence that personalized pangenome improves somatic variant detection in cancer genomics with the most benefit for scWGS data and complex genomic regions previously misaligned due to linear reference bias.
Co-authors: Mark van Roosmalen, Rico Hagelaar, Eline Bertrums, Andrea Guarracino, Ruben van Boxtel
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