TrEMOLO

TrEMOLO detects and estimates allele frequencies of transposable elements (TEs) from long-read sequencing data by integrating assembly- and mapping-based analyses.

Key Features:

• Hybrid Approach: Combines assembly-based detection and mapping-based approaches to identify TE insertions and deletions from long reads.
• Versatility in Genome Quality: Processes both high-quality and low-quality genome assemblies.
• Population-Level Analysis: Estimates allele frequencies of TEs within populations.
• Benchmarking: Comparative analyses on simulated data reported higher accuracy and efficiency than other tested tools.
• Validation with Diverse Data: Validated using both simulated and experimental datasets to assess detection and frequency estimation performance.

Scientific Applications:

• Evolutionary Biology: Characterizing TE insertion and deletion dynamics to study their role in genome evolution.
• Population Genetics: Estimating TE allele frequencies across populations to investigate TE-driven genetic variation.
• Genomics: Annotating and profiling TE insertions and deletions in genome assemblies using long-read data.

Methodology:

TrEMOLO integrates assembly-based detection (reconstructing genomes from long-read data) with mapping-based approaches (aligning reads to reference genomes) to profile known and novel TE insertions and deletions and estimate their allele frequencies.