Abstract
Background: Transposables elements (TEs) contribute to both structural and functional dynamics of most eukaryotic genomes. Because of their propensity to densely populate plant and animal genomes, the precise estimation of the impact of transposition on genomic diversity has been considered as one of the main challenges of today's genomics. The recent development of NGS (next generation sequencing) technologies has open new perspectives in population genomics by providing new methods for high throughput detection of Transposable Elements-associated Structural Variants (TEASV). However, these have relied on Illumina platform that generates short reads (up to 350 nucleotides). This limitation in size of sequence reads can cause high false discovery rate (FDR) and therefore limit the power of detection of TEASVs, especially in the case of large, complex genomes. The newest sequencing technologies, such as Oxford Nanopore Technologies (ONT) can generate kilobases-long reads thus representing a promising tool for TEASV detection in plant and animals.Results: We present the results of a pilot experiment for TEASV detection on the model plant species Arabidopsisthaliana using ONT sequencing and show that it can be used efficiently to detect TE movements. We generated a~0.8X genome coverage of a met1-derived epigenetic recombinant inbred line (epiRIL) using a MinIon device withR7 chemistry. We were able to detect nine new copies of the LTR-retrotransposon Evadé (EVD). We also evidencedthe activity of the DNA transposon CACTA, CAC1.Conclusions: Even at a low sequence coverage (0.8X), ONT sequencing allowed us to reliably detect several TEinsertions in Arabidopsis thaliana genome. The long read length allowed a precise and un-ambiguous mapping ofthe structural variations caused by the activity of TEs. This suggests that the trade-off between read length andgenome coverage for TEASV detection may be in favor of the former. Should the technology be further improvedboth in terms of lower error rate and operation costs, it could be efficiently used in diversity studies at populationlevel.