Immunoglobulin transcript sequence and somatic hypermutation computation from unselected RNA-seq reads in chronic...

Area of Science:

• Immunology
• Oncology
• Bioinformatics

Background:

• Immunoglobulins (Ig) exhibit vast diversity due to gene rearrangement and somatic hypermutation.
• B-cell malignancies, like Chronic Lymphocytic Leukemia (CLL), are characterized by clonal Ig production.
• Assessing IGHV mutation status is crucial for CLL prognosis and is currently done via Sanger sequencing.

Purpose of the Study:

• To develop and validate a computational method for determining complete IGH@ V-D-J sequences from RNA-seq data.
• To compare the accuracy of this RNA-seq based method against the current clinical standard (Sanger sequencing) for IGHV mutation status assessment in CLL.
• To explore the potential of a single RNA-seq assay for comprehensive, multidimensional data capture in CLL.

Main Methods:

• Utilized unselected RNA-sequencing reads to compute complete IGH@ V-D-J sequences.
• Employed bioinformatics analysis to reconstruct Ig heavy chain transcripts.
• Compared the computed sequences and IGHV mutation status with results from Sanger sequencing.

Main Results:

• Complete IGH@ V-D-J sequences were successfully computed from RNA-seq reads.
• The RNA-seq method achieved results equal to or superior to Sanger sequencing.
• A discordant case revealed an out-of-frame transcript by the clinical method, highlighting potential inaccuracies.

Conclusions:

• A single RNA-seq assay can accurately determine IGHV mutation status in CLL.
• This method offers a more comprehensive approach, simultaneously providing gene expression, SNP, and mutation data.
• RNA-seq based IGH@ V-D-J sequence computation may become a routine test for multidimensional data in CLL.