2025/08/30 by Victor Loegler, Anne Friedrich, Joseph Schacherer · 1 voice
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · #Chromosomal and Genetic Variations #CRISPR and Genetic Engineering #Genomics and Phylogenetic Studies
paper · pdf · doi:10.1101/2025.08.26.672342
openalex publication_date 2025/08/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/15
Abstract The emergence of graph pangenomes has significantly advanced the study of structural variants (SVs) across diverse species. However, the impact of complex polyploidization events, particularly allopolyploidy, on SV landscapes remains poorly explored. Brettanomyces bruxellensis , a yeast species shaped by multiple allopolyploidization events, offers a compelling model due to its well-characterized genomic and phenotypic diversity. Here, we integrated subgenome-resolved assemblies with population-scale genomic and transcriptomic datasets to characterize SVs distribution and their functional impact at the species level. Leveraging a constructed reference graph pangenome, we identified sequences that are unique to each subgenome, and detected 212,177 SVs across 1,060 sequenced isolates. Allopolyploid genomes harbored significantly more SVs (320 on average) than diploid genomes (116 on average), reflecting the extensive impact of hybridization on the genome architecture. A subset of SVs originating from ancestral divergence between subgenomes (hybridization-associated SVs) formed distinct hotspots of structural diversity. Furthermore, functional association analysis revealed that 27.5% of SVs exert local regulatory effects on gene expression. Interestingly, hybridization-associated structural variants disproportionately affect gene expression, with a greater proportion of associated variants and a significantly larger effect size compared to other SVs. Overall, these findings underscore the role of allopolyploidization in driving both structural and functional genomic diversification. Our study also highlights the value of graph-based approaches in dissecting complex genome evolution.