IgEvolution: clonal analysis of antibody repertoires

Constructing antibody repertoires is an important error-correcting step in analyzing immunosequencing datasets that is important for reconstructing evolutionary (clonal) development of antibodies. However, the state-of-the-art repertoire construction tools typically miss low-abundance antibodies that often represent internal nodes in clonal trees and are crucially important for clonal tree reconstruction. Thus, although repertoire construction is a prerequisite for follow up clonal tree reconstruction, the existing repertoire reconstruction algorithms are not well suited for this task. Since clonal analysis has the potential to reveal errors in the constructed repertoires and contribute to constructing more accurate repertoires, we advocate a tree-guided construction of antibody repertoires that combines error correction and clonal reconstruction as interconnected (rather than independent) tasks. We developed the IgEvolution algorithm for simultaneous repertoire and clonal tree reconstruction and applied it for analyzing multiple immunosequencing datasets representing antigen-specific immune responses. We demonstrate that analysis of clonal trees reveals highly mutable positions that correlate with antigen-binding sites and light-chain contacts in crystallized antibody-antigen complexes. We further demonstrate that this analysis leads to a new approach for identifying complementarity determining regions (CDRs) in antibodies.