RNA-Seq mapping and detection of gene fusions with a suffix array algorithm

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• High-throughput RNA sequencing (RNA-Seq) allows comprehensive transcript analysis.
• Detecting low-abundance gene fusions is challenging with short sequencing reads.

Purpose of the Study:

• To implement an improved RNA-Seq mapping pipeline for accurate gene fusion detection.
• To identify novel and low-abundance chimeric transcripts in breast cancer.

Main Methods:

• Development of an RNA-Seq mapping pipeline with novel features like junction mapping and pairing rescue.
• Integration with a Suffix Array Spliced Read (SASR) aligner for chimeric transcript detection.
• Paired-end RNA-Seq on the MCF-7 breast cancer cell line using the SOLiD system.

Main Results:

• Identified 40 gene fusions from over 120,000 splicing junctions.
• Validated 36 of the 40 identified fusions using TaqMan assays.
• Discovered recurrent fusions involving ESR1 and RPS6KB1 in breast cancer cell lines and a clinical sample.

Conclusions:

• The enhanced RNA-Seq pipeline effectively detects low-abundance gene fusions.
• The identified gene fusions, particularly those involving ESR1 and RPS6KB1, are significant in breast cancer.
• This approach advances the discovery of fusion transcripts in cancer genomics.