Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 8; pp. E862 - E870
• Main Authors: Gadala-Maria, Daniel, Yaari, Gur, Uduman, Mohamed, Kleinstein, Steven H.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 24.02.2015; National Acad Sciences
• Series: PNAS Plus
• Subjects: adaptive immunity; Alleles; Automation; B-lymphocytes; B-Lymphocytes - metabolism; Base Sequence; Biological Sciences; Cells; Databases, Genetic; Gene Rearrangement, B-Lymphocyte; Genes; Genes, Immunoglobulin; Genotype; Genotype & phenotype; germ cells; high-throughput nucleotide sequencing; High-Throughput Nucleotide Sequencing - methods; Humans; Immunoglobulin Variable Region - genetics; Immunoglobulins; Mutation - genetics; Mutation Rate; PNAS Plus; Polymorphism; Polymorphism, Genetic; receptors; Software; V(D)J Recombination - genetics; somatic hypermutation; next-generation sequencing; adaptive immunity; variable gene segment; B-cell repertoire
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.1417683112

Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.