ArticlePLoS computational biology2022
Learning the statistics and landscape of somatic mutation-induced insertions and deletions in antibodies.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 19 citations in OpenAlex.
- Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025Article
- Profiling antigen-binding affinity of B cell repertoires in tumors by deep learning predicts immune-checkpoint inhibitor treatment outcomes.Nature cancer · 2025Article
- Enhancing sequence alignment of adaptive immune receptors through multi-task deep learning.Nucleic acids research · 2025Article
- Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS computational biology · 2025Article
- Unveiling inverted D genes and D-D fusions in human antibody repertoires unlocks novel antibody diversity.Communications biology · 2025Article
- Rapid affinity optimization of an anti-TREM2 clinical lead antibody by cross-lineage immune repertoire mining.Nature communications · 2024Article
- Isotype-aware inference of B cell clonal lineage trees from single-cell sequencing data.Cell genomics · 2024Article
- Combining mutation and recombination statistics to infer clonal families in antibody repertoires.eLife · 2024Article
- B cell phylogenetics in the single cell era.Trends in immunology · 2024Review
- TRIBAL: Tree Inference of B cell Clonal Lineages.bioRxiv : the preprint server for biology · 2023Article
- Fast clonal family inference from large-scale B cell repertoire sequencing data.Cell reports methods · 2023Article
- Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals.PLoS genetics · 2023Article
- Lineage Reconstruction of In Vitro Identified Antigen-Specific Autoreactive B Cells from Adaptive Immune Receptor Repertoires.International journal of molecular sciences · 2022Article
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Authors and funding
4 authors at 1 institution in 3 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Affinity maturation is crucial for improving the binding affinity of antibodies to antigens. This process is mainly driven by point substitutions caused by somatic hypermutations of the immunoglobulin gene. It also includes deletions and insertions of genomic material known as indels. While the landscape of point substitutions has been extensively studied, a detailed statistical description of indels is still lacking. Here we present a probabilistic inference tool to learn the statistics of indels from repertoire sequencing data, which overcomes the pitfalls and biases of standard annotation methods. The model includes antibody-specific maturation ages to account for variable mutational loads in the repertoire. After validation on synthetic data, we applied our tool to a large dataset of human immunoglobulin heavy chains. The inferred model allows us to identify universal statistical features of indels in heavy chains. We report distinct insertion and deletion hotspots, and show that the distribution of lengths of indels follows a geometric distribution, which puts constraints on future mechanistic models of the hypermutation process.
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