Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data

Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.Author summary: B cells recognize antigens through their BCR. During adaptive immune responses, antigen-specific B cells undergo intense proliferation. This B cell clonal expansion is coupled with a process of SHM, which results in the accumulation of mutations in the DNA encoding the BCR. Within the specialized micro-environment of the germinal center, these diversified B cells compete for antigen binding and presentation to follicular helper T cells. Successful binding leads to repeated cycles of proliferation, SHM and affinity-dependent selection ultimately resulting in the generation of high-affinity memory and antibody-secreting plasma cells. Driven by dramatic improvements in high-throughput sequencing technologies, large-scale characterization of BCR repertoires is now feasible. However, a critical barrier to quantitative analysis of these large-scale BCR repertoire data is the accurate identification of B cell clones. B cells are inferred to be clonally related if the distance between their BCR sequences is close enough. This paper develops a hybrid distance function that integrates information from the V(D)J recombination process (distance between CDR3 sequences), along with information from a common history of clonal expansion (shared SHMs in the V and J segments of the BCR) to improve the ability to identify clonally related sequences.