A unified framework to analyze transposable element insertion polymorphisms using graph genomes

• DOI: 10.1038/s41467-024-53294-2
• Publication Date: 2024-10-16T13:02:30Z
• Authors: Cristian Groza; Xun Chen; Travis J. Wheeler; Guillaume Bourque; Clément Goubert
• Keywords: DNA Transposable Elements

Transposable elements are ubiquitous mobile DNA sequences generating insertion polymorphisms, contributing to genomic diversity. We present GraffiTE, a flexible pipeline analyze polymorphic insertions. By integrating state-of-the-art structural variant detection algorithms and graph genomes, GraffiTE identifies from assemblies or long-read sequencing data, genotypes these variants using short long read sets. Benchmarking on simulated real datasets reports high precision recall rates. is designed allow non-expert users perform comprehensive analyses, including in models with limited transposable element knowledge compatible various technologies. Here, we demonstrate the versatility of by analyzing human, Drosophila melanogaster, maize, Cannabis sativa pangenome data. These analyses reveal landscapes their frequency variations across individuals, strains, cultivars.