Efficient detection of transposable element insertion polymorphisms between genomes using short-read sequencing data

Transposable elements (TEs) are powerful generators of major-effect mutations, most of which are deleterious at the species level and maintained at very low frequencies within populations. As reference genomes can only capture a minor fraction of such variants, methods were developed to detect TE insertion polymorphisms (TIPs) in non-reference genomes from short-read sequencing data, which are becoming increasingly available. We present here a bioinformatic framework combining an improved version of the SPLITREADER and TEPID pipelines to detect non-reference TE presence and reference TE absence variants, respectively. We benchmark our method on ten non-reference Arabidopsis thaliana genomes and demonstrate its high specificity and sensitivity in the detection of TIPs between genomes.