Year: 2026
Type: article
Abstract: Pangenome graphs are increasingly used in genetic diversity analyses because they reduce reference bias in read mapping and enhance variant discovery and genotyping from SNPs to structural variants. In pangenome graphs, variants appear as bubbles, which can be detected by dedicated bubble calling tools. Although these tools report essential information on the variant bubbles, such as their position and allele walks in the graph, they do not annotate the type of the detected variants. While simple SNPs, insertions, and deletions are easily distinguishable by allele size, large balanced variants like inversions are harder to differentiate among the large number of unannotated bubbles and remain underexplored in pangenome graph benchmarks and analyses. In this work, we focused on inversions, which have been drawing renewed attention in evolutionary genomics studies in the past years, and aimed to assess how this type of variant is handled by state of the art pangenome graph pipelines. We identified two distinct topological motifs for inversion bubbles: one path-explicit and one alignment-rescued, and developed a tool to annotate them from bubble-caller outputs. We constructed pangenome graphs with both simulated data and real data using four state of the art pipelines, and assessed the impact of inversion size, genome divergence, and variant density on inversion representation and accuracy. Our results reveal substantial differences between pipelines in simulated graphs, with some inversions either misrepresented or lost. In addition, recovery rates are strikingly low in real human datasets, highlighting major challenges in analyzing inversions through pangenomic approaches.
Source: NAR Genomics and Bioinformatics
Institutions: Centre National de la Recherche Scientifique, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes, École Nationale Vétérinaire de Toulouse, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Génétique Physiologie et Systèmes d'Elevage, Université de Toulouse, Institut de Génétique, Environnement et Protection des Plantes
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,766
Funder: Agence Nationale de la Recherche
Awards: G5296751580, Diversification and adaptation along environmental gradients: identification of genes and traits involved in species differentiation in alpine butterflies, Genomic and functional characterization of domestic plant and animal genetic diversity as a keystone for agroecology: linking genome to phenome
OpenAlex ID: W7167205543