ExplorATE: a new pipeline to explore active transposable elements from RNA-seq data.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Evolution

Background:

• Transposable elements (TEs) are mobile DNA sequences prevalent in genomes.
• Active TEs contribute significantly to transcriptomes and can drive genomic mutation and evolution.
• Studying TEs is challenging, especially in non-model organisms, due to identification and quantification difficulties.

Purpose of the Study:

• To develop a novel computational pipeline, ExplorATE, for accurate quantification of active transposable elements.
• To enable TE analysis in both model and non-model organisms.
• To address limitations in current TE quantification methods, particularly concerning co-transcription and multi-mapping.

Main Methods:

• Developed ExplorATE, an R/bash pipeline utilizing Selective Alignment (SA) for TE quantification.
• Created TE-specific indexes and employed SA to filter co-transcribed transposons based on alignment scores.
• Integrated Wicker-like criteria to refine target TEs and minimize spurious mapping.

Main Results:

• ExplorATE demonstrated superior accuracy in estimating non-co-transcribed elements compared to existing software using simulated and real data.
• The pipeline showed high congruence with alignment-based tools, with or without a reference genome.
• ExplorATE achieved significantly reduced execution times compared to other methods.

Conclusions:

• ExplorATE provides a robust and efficient solution for quantifying active transposable elements across diverse organisms.
• The pipeline effectively accounts for co-transcription and multi-mapping effects, enhancing TE analysis.
• ExplorATE integrates seamlessly with downstream R-based bioinformatics tools.