Transposable element finder (TEF): finding active transposable elements from next generation sequencing data.

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Detecting transposable element (TE) transposition events in next-generation sequencing (NGS) data is challenging due to numerous existing TE copies.
• Previous tools like Transposon Insertion Finder (TIF) require known TE sequences, limiting their application.

Purpose of the Study:

• To develop a novel algorithm, Transposable Element Finder (TEF), for detecting TE transpositions, including those with unknown sequences.
• To identify both ends and target site duplications (TSDs) associated with TE transposition events.

Main Methods:

• Developed TEF, employing two algorithms: one grouping TSDs and comparing k-mers from NGS data, and another using junction mapping of TE end sequence candidates.
• Validated methods on rice, Arabidopsis, and Drosophila datasets, comparing NGS data between samples.

Main Results:

• TEF successfully detected both ends and TSDs of known active TEs across multiple species.
• Identified several novel TE insertions in new genomic locations.
• PCR confirmed transposition events in rice samples.

Conclusions:

• TEF effectively detects transposed TEs, their TSDs, sequences, and insertion positions by comparing NGS data.
• The algorithm's genotype verification and independence from TE libraries make it valuable for discovering unknown TEs.
• TEF offers a user-friendly solution for identifying TE insertions missed by standard annotation pipelines.