  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.
