ISEScan: automated identification of insertion sequence elements in prokaryotic genomes

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Insertion sequence (IS) elements are abundant mobile genetic elements crucial for prokaryotic genome evolution.
• Accurate and automated annotation of IS elements is vital for analyzing vast prokaryotic genomic datasets.
• Existing annotation tools often provide incomplete results or depend on prior genome annotations.

Purpose of the Study:

• To develop a novel, accurate, and automated pipeline for IS element annotation in prokaryotic genomes.
• To overcome limitations of current IS annotation systems, particularly their reliance on existing annotations.

Main Methods:

• Developed ISEScan, a software pipeline utilizing profile hidden Markov models.
• Profile HMMs were constructed from manually curated IS element sequences.
• The pipeline is implemented in Python and available as open-source software.

Main Results:

• ISEScan demonstrates superior performance compared to existing IS annotation systems.
• Tested on 2784 prokaryotic genomes, ISEScan provides highly sensitive IS element annotation.
• The study reports the global distribution of IS families across archaeal and bacterial taxonomic groups.

Conclusions:

• ISEScan offers a robust solution for accurate and automated IS element annotation.
• The pipeline facilitates large-scale genomic analysis and evolutionary studies of IS elements.
• Findings provide insights into the prevalence and distribution of IS families in prokaryotes.