SVExpress: identifying gene features altered recurrently in expression with nearby structural variant breakpoints

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Combined whole-genome sequencing (WGS) and RNA sequencing can identify genes with altered expression due to genomic rearrangements in cancer.
• Somatic structural variants (SVs) can lead to altered gene cis-regulation, gene fusions, copy number alterations, or gene disruption.
• A lack of streamlined computational tools hinders the identification of genes recurrently altered by genomic rearrangements.

Purpose of the Study:

• To introduce SVExpress, a computational toolset for integrative analysis of structural variant (SV) and gene expression data.
• To enable systematic cataloging of genes with consistently altered expression in conjunction with nearby SV breakpoints.
• To facilitate the evaluation of SVs for mechanisms like enhancer translocation and topologically associated domain (TAD) disruption.

Main Methods:

• SVExpress processes output from common SV calling algorithms.
• The tool analyzes SV and gene expression data across large cancer sample cohorts.
• It assesses SV breakpoints in proximity to genes for potential regulatory impacts.

Main Results:

• SVExpress was used to analyze 327 cancer cell lines from the Cancer Cell Line Encyclopedia (CCLE).
• Hundreds of genes exhibited altered expression linked to nearby SV breakpoints, involving TAD disruption, enhancer hijacking, and gene fusions.
• Significant overlap was observed in SV-altered genes between cancer cell lines and human tumors, with some dataset-specific findings.

Conclusions:

• SVExpress empowers computational biologists to integrate gene expression and SV breakpoint data for identifying recurrently altered genes.
• The SVExpress tools are freely available for academic and commercial use.
• The software is implemented in R code and Excel macros, with all source code accessible.