Automated analysis of immunosequencing datasets reveals novel immunoglobulin D genes across diverse species

• Published in: PLoS computational biology Vol. 16; no. 4; p. e1007837
• Main Authors: Bhardwaj, Vinnu, Franceschetti, Massimo, Rao, Ramesh, Pevzner, Pavel A., Safonova, Yana
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.04.2020; Public Library of Science (PLoS)
• Subjects: Algorithms; Animals; Antibodies; Binding sites; Biology and life sciences; Computational Biology - methods; Computer engineering; Computer science; D gene; Databases, Genetic; Datasets; Gene sequencing; Genes; Genes, Immunoglobulin - genetics; Genetic aspects; Genomes; Genomics; Humans; Immunity - genetics; Immunogenetics; Immunoglobulin D; Immunoglobulin D - genetics; Immunoglobulins; Information theory; Medicine and Health Sciences; Methods; Population; Random variables; Reconstruction; Research and Analysis Methods; Seeds; Software; Species diversity; V(D)J recombination; Whole genome sequencing; United States; United States > US; California
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1007837

Immunoglobulin genes are formed through V(D)J recombination, which joins the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics focuses on finding alleles of germline genes across various patients. Although reconstruction of V and J genes is a well-studied problem, the more challenging task of reconstructing D genes remained open until the IgScout algorithm was developed in 2019. In this work, we address limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstruction, apply it to hundreds of immunosequencing datasets from multiple species, and validate the newly inferred D genes by analyzing diverse whole genome sequencing datasets and haplotyping heterozygous V genes.