Identification, assembly and characterization of tumor immunoglobulin transcripts from RNA sequencing data using...

Area of Science:

• Immunology
• Genomics
• Bioinformatics

Background:

• Immunoglobulin gene analysis is crucial for understanding B cell receptor function and B cell tumor characteristics.
• Current methods like PCR and Sanger sequencing are time-consuming and limited in detecting diverse sequences.
• High-throughput RNA-sequencing (RNA-seq) offers a faster alternative for extracting tumor immunoglobulin transcripts.

Purpose of the Study:

• To present a rapid, user-friendly protocol for analyzing immunoglobulin gene sequences from RNA-seq data.
• To enable accurate characterization of full tumor immunoglobulin transcripts, including templated and non-templated sequences.
• To facilitate the integration of immunoglobulin sequence data with other tumor features for comprehensive analysis.

Main Methods:

• Development of a protocol for rapid (~1 hour) de novo assembly and identification of immunoglobulin transcripts from RNA-seq data.
• Utilizing a provided bioinformatics tool (https://github.com/ForconiLab/IgSeqR) for sequence acquisition and characterization.
• Analysis of physicochemical characteristics of derived amino acid sequences and prediction of tumor glycan types in specific lymphomas.

Main Results:

• Successful rapid (~1 hour) de novo assembly and accurate characterization of full tumor immunoglobulin transcripts from RNA-seq data.
• The protocol allows for the extraction of both templated and non-templated immunoglobulin sequences.
• Derived amino acid sequences can be analyzed for physicochemical properties and potential glycan site prediction.

Conclusions:

• This RNA-seq based protocol significantly speeds up immunoglobulin gene analysis in B cell tumors.
• The method enhances the ability to combine immunoglobulin characteristics with tumor transcriptome data.
• The findings support refined diagnosis, prognosis, and therapeutic targeting strategies for common lymphomas.