# A Pipeline for Insertion Sequence Detection and Study for Bacterial Genome

## TL;DR

This paper presents a new pipeline combining existing tools for accurate detection and classification of insertion sequences in bacterial genomes, tested on Pseudomonas aeruginosa genomes.

## Contribution

The authors developed a comprehensive pipeline integrating multiple annotation tools and IS detection methods, improving accuracy and enabling detailed IS analysis in bacterial genomes.

## Key findings

- Prodigal outperforms other annotation tools for IS prediction.
- Close genomes in P. aeruginosa have similar IS family distributions.
- The pipeline effectively detects and classifies IS elements in bacterial genomes.

## Abstract

Insertion Sequences (ISs) are small DNA segments that have the ability of moving themselves into genomes. These types of mobile genetic elements (MGEs) seem to play an essential role in genomes rearrangements and evolution of prokaryotic genomes, but the tools that deal with discovering ISs in an efficient and accurate way are still too few and not totally precise. Two main factors have big effects on IS discovery, namely: genes annotation and functionality prediction. Indeed, some specific genes called "transposases" are enzymes that are responsible of the production and catalysis for such transposition, but there is currently no fully accurate method that could decide whether a given predicted gene is either a real transposase or not. This is why authors of this article aim at designing a novel pipeline for ISs detection and classification, which embeds the most recently available tools developed in this field of research, namely OASIS (Optimized Annotation System for Insertion Sequence) and ISFinder database (an up-to-date and accurate repository of known insertion sequences). As this latter depend on predicted coding sequences, the proposed pipeline will encompass too various kinds of bacterial genes annotation tools (that is, Prokka, BASys, and Prodigal). A complete IS detection and classification pipeline is then proposed and tested on a set of 23 complete genomes of Pseudomonas aeruginosa. This pipeline can also be used as an investigator of annotation tools performance, which has led us to conclude that Prodigal is the best software for IS prediction. A deepen study regarding IS elements in P.aeruginosa has then been conducted, leading to the conclusion that close genomes inside this species have also a close numbers of IS families and groups.