NetCIS: a network-based common insertion site pipeline for case-control Sleeping Beauty screens

Area of Science:

• Genetics
• Bioinformatics
• Cancer Research

Background:

• Forward genetic screens are essential for discovering genes controlling biological phenotypes.
• The Sleeping Beauty (SB) transposon system is a widely used tool for insertional mutagenesis in genetic screens.
• Previous SB screens have identified cancer drivers, drug resistance mechanisms, and immunotherapy targets.

Purpose of the Study:

• To develop a novel analysis tool for Sleeping Beauty transposon screen data.
• To enable data-driven case-control comparisons for identifying significant common insertion sites (CISes).
• To address limitations in existing tools for analyzing screens with case-control designs.

Main Methods:

• Developed NetCIS, a network-based analysis tool utilizing a graph-based algorithm.
• Implemented NetCIS for robust identification of statistically significant CISes between cases and controls.
• Benchmarked NetCIS against existing insertional mutagenesis analysis tools using a published SB dataset.

Main Results:

• NetCIS effectively identifies statistically significant CISes in case-control screens.
• The tool prioritizes biologically validated genes comparably or superiorly to existing methods.
• NetCIS uniquely identifies CISes in unannotated genomic regions, which are often missed by other tools.

Conclusions:

• NetCIS provides a robust and efficient method for analyzing Sleeping Beauty transposon screen data.
• The tool enhances the discovery of novel genes and mechanisms underlying various biological phenotypes.
• NetCIS supports advanced genetic screening designs, particularly case-control comparisons, advancing biological discovery.