Graphical pangenomics-enabled characterization of structural variant impact on gene expression in Brassica napus

Pangenome graphs enable population-scale genotyping and improve expression analysis, revealing that structural variations (SVs), particularly transposable elements (TEs), significantly contribute to gene expression variation in winter oilseed rape. Structural variations (SVs) impact important traits, from yield to flowering behaviour and stress responses. Pangenome graphs capture population-level diversity, including SVs, within a single data structure and provide a robust framework for downstream applications. They have the potential to serve as unbiased references for SV genotyping, pan-transcriptomic analyses, and association studies, offering significant advantages over single reference genomes. However, their full potential for expression quantitative trait locus (eQTL) analysis is yet to be explored. We combined long and short-read whole genome sequencing data with expression profiling of Brassica napus (oilseed rape) to assess the impact of SVs on gene expression regulation and explored the utility of pangenome graphs for eQTL analysis. Over 90,000 SVs were discovered from 57 long-read datasets. Pangenome graph as reference was evaluated and used for SV genotyping with short reads and transcript expression quantification. Using SVs genotyped from the graph and 100 expression datasets, we identified 267 gene proximal (cis) SV-eQTLs. Over 70% of eQTL-SVs had similarity to transposable elements (TEs), especially Helitrons. The highest proportion of cis-eQTL-SVs were found in promoter regions. About a third of transcripts whose expression was associated with SVs, had no associated SNPs, suggesting that including SVs allows capturing of relationship which would be missed in SNP-only analyses. This study demonstrated that pangenome graphs provide a unifying framework for eQTL analysis by allowing population-scale SV genotyping and gene expression quantification. We also showed that SVs make an appreciable contribution to gene expression variation in winter oilseed rape.