SimulaTE: simulating complex landscapes of transposable elements of populations

Area of Science:

• Genomics
• Population Genetics
• Bioinformatics

Background:

• Estimating transposable element (TE) abundance in populations is crucial for understanding genome evolution and function.
• Current methods for TE identification lack concordance, leading to unreliable results and hindering research progress.

Purpose of the Study:

• To develop a computational tool, SimulaTE, that generates simulated TE landscapes for populations.
• To provide a standardized approach for comparing different TE identification methods.

Main Methods:

• SimulaTE utilizes a novel domain-specific language (DSL) to create complex TE landscapes, including nested, truncated, and diverged insertions.
• The tool simulates sequencing reads from various technologies (PacBio, Illumina paired-ends) and strategies (individual or pooled sequencing).

Main Results:

• SimulaTE enables the generation of realistic TE landscapes, facilitating the comparison of simulated and observed data.
• This comparison guides researchers in selecting appropriate TE identification approaches for their specific research questions.

Conclusions:

• SimulaTE addresses the need for reliable TE abundance estimation by providing a simulation-based framework.
• The tool enhances the reproducibility and accuracy of population genomics studies involving transposable elements.