Biological sequence simulation for testing complex evolutionary hypotheses: indel-Seq-Gen version 2.0.

Area of Science:

• Bioinformatics
• Computational Biology
• Molecular Evolution

Background:

• Sequence simulation is vital for validating biological hypotheses and testing bioinformatics methods.
• Current methods struggle with complex hypotheses requiring heterogeneous sequence evolution models.
• Previous tool indel-Seq-Gen version 1.0 (iSGv1.0) offered improvements but remained insufficient for advanced testing.

Purpose of the Study:

• To introduce indel-Seq-Gen version 2.0 (iSGv2.0) for simulating the evolution of highly divergent DNA sequences and protein superfamilies.
• To enhance sequence simulation capabilities for complex evolutionary scenarios.
• To address and correct flaws in existing indel modeling.

Main Methods:

• iSGv2.0 incorporates lineage-specific evolution, PROSITE-like regular expression motif conservation, indel tracking, and subsequence-length constraints.
• It simulates both coding and noncoding DNA evolution.
• A novel discrete stepping procedure corrects a flaw in indel modeling, preventing simulation result bias.

Main Results:

• iSGv2.0 demonstrates improved simulation of heterogeneous protein and DNA sequence evolution.
• The new discrete stepping procedure rectifies biases in indel modeling.
• Comparative analysis shows iSGv2.0 outperforms iSGv1.0 and random models for complex evolutionary simulations.

Conclusions:

• iSGv2.0 provides a more robust and accurate tool for simulating complex sequence evolution, particularly for highly divergent sequences and protein superfamilies.
• The corrected indel modeling enhances the reliability of simulations for hypothesis testing.
• This advancement facilitates more sophisticated validation of biological hypotheses and evolutionary methods.