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

Vinnu Bhardwaj, Massimo Franceschetti, Ramesh Rao, Pavel A. Pevzner, Yana Safonova

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article numbere1007837
JournalPLoS computational biology
Volume16
Issue number4
DOIs
StatePublished - Apr 2020

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

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