Data on haplotype-supported immunoglobulin germline gene inference

Area of Science:

• Immunology
• Genomics
• Bioinformatics

Background:

• Antibody repertoire analysis is crucial for understanding immune responses.
• Accurate germline gene identification is essential for comprehensive antibody studies.
• Existing methods may not fully capture the diversity of germline genes.

Purpose of the Study:

• To describe data for inferring immunoglobulin heavy chain variable (IGHV) germline genes.
• To establish personalized germline gene sets for antibody repertoire studies.
• To enable the detection of new antibody germline genes from transcriptome data.

Main Methods:

• Utilizing IgM-encoding transcriptome sequences obtained via Illumina MiSeq technology.
• Inferring IGHV germline genes from sequencing data.
• Validating the inference process by analyzing gene association with donor haplotypes (IGHJ alleles, IGHD genes/alleles).

Main Results:

• The described data supports the inference of IGHV germline genes.
• The inference process was validated through haplotype association analysis.
• Demonstrated the utility of transcriptome data for germline gene discovery.

Conclusions:

• The data facilitates the development of validated germline gene databases.
• Enables the generation of accurate, personalized antibody germline gene repertoires.
• Highlights the value of transcriptome sequencing for advancing antibody research.