Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Ecole Normale Supérieure, PSL Research University, Paris, France.
Methods Mol Biol. 2021;2250:157-169. doi: 10.1007/978-1-0716-1134-0_15.
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 the short-read sequencing data that 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.
转座元件 (TEs) 是产生重大效应突变的强大因素，其中大多数在物种水平上是有害的，并且在种群中维持着非常低的频率。由于参考基因组只能捕获这些变体的一小部分，因此开发了从越来越多的短读测序数据中检测非参考基因组中转座元件插入多态性 (TIP) 的方法。我们在这里提出了一个生物信息学框架，该框架结合了 SPLITREADER 和 TEPID 管道的改进版本，分别用于检测非参考 TE 的存在和参考 TE 的缺失变体。我们在十个非参考拟南芥基因组上对我们的方法进行了基准测试，并证明了它在检测基因组之间的 TIP 方面具有很高的特异性和敏感性。
