Barnacle: detecting and characterizing tandem duplications and fusions in transcriptome assemblies

Area of Science:

• Genomics
• Bioinformatics
• Cancer Research

Background:

• Chimeric transcripts, such as partial tandem duplications (PTDs), internal tandem duplications (ITDs), and gene fusions, play a crucial role in cancer detection, prognosis, and treatment.
• Identifying these genetic alterations is vital for understanding cancer biology and developing targeted therapies.

Purpose of the Study:

• To introduce Barnacle, a novel analysis tool designed for detecting chimeric transcripts in de novo RNA-seq assemblies.
• To enable prioritization of detected chimeras for efficient review and validation by quantifying their relative coverage against wild-type transcripts.

Main Methods:

• Barnacle analyzes RNA-sequencing data from de novo assemblies to identify various types of chimeric transcripts.
• The tool calculates the relative coverage of chimeric versus wild-type transcripts to aid in prioritization.
• The performance of Barnacle was evaluated using real and simulated datasets, including acute myeloid leukemia (AML) samples.

Main Results:

• Barnacle successfully identified PTDs in MLL, ITDs in FLT3, and PML-RARA fusions in AML RNA-seq datasets.
• The tool demonstrated high specificity in predicting PTDs, ITDs, and gene fusions with optimized filter settings.
• Barnacle's ability to prioritize findings enhances the efficiency of manual review and validation processes.

Conclusions:

• Barnacle is a robust tool for the specific detection of key chimeric transcripts relevant to a wide range of cancers.
• The high specificity of Barnacle facilitates efficient manual review and validation, crucial for large-scale genomic studies.
• Further characterization of diverse chimera types using Barnacle can provide deeper insights into cancer progression, treatment strategies, and patient outcomes.