Gene-Specific Substitution Profiles Describe the Types and Frequencies of Amino Acid Changes during Antibody Somatic Hypermutation

Zizhang Sheng, Chaim A. Schramm, Rui Kong, NISC Comparative Sequencing Program, James C. Mullikin, John R. Mascola, Peter D. Kwong, Lawrence Shapiro, Betty Benjamin, Gerry Bouffard, Shelise Brooks, Holly Coleman, Mila Dekhtyar, Xiaobin Guan, Joel Han, Shi- ling Ho, Richelle Legaspi, Quino Maduro, Cathy Masiello, Jenny McDowell, Casandra Montemayor, James Mullikin, Morgan Park, Nancy Riebow, Jessica Rosarda, Karen Schandler, Brian Schmidt, Christina Sison, Ray Smith, Mal Stantripop, James Thomas, Pam Thomas, Meg Vemulapalli, Alice Young

Somatic hypermutation (SHM) plays a critical role in the maturation of antibodies, optimizing recognition initiated by recombination of V(D)J genes. Previous studies have shown that the propensity to mutate is modulated by the context of surrounding nucleotides and that SHM machinery generates biased substitutions. To investigate the intrinsic mutation frequency and substitution bias of SHMs at the amino acid level, we analyzed functional human antibody repertoires and developed mGSSP (method for gene-specific substitution profile), a method to construct amino acid substitution profiles from next-generation sequencing-determined B cell transcripts. We demonstrated that these gene-specific substitution profiles (GSSPs) are unique to each V gene and highly consistent between donors. We also showed that the GSSPs constructed from functional antibody repertoires are highly similar to those constructed from antibody sequences amplified from non-productively rearranged passenger alleles, which do not undergo functional selection. This suggests the types and frequencies, or mutational space, of a majority of amino acid changes sampled by the SHM machinery to be well captured by GSSPs. We further observed the rates of mutational exchange between some amino acids to be both asymmetric and context dependent and to correlate weakly with their biochemical properties. GSSPs provide an improved, position-dependent alternative to standard substitution matrices, and can be utilized to developing software for accurately modeling the SHM process. GSSPs can also be used for predicting the amino acid mutational space available for antigen-driven selection and for understanding factors modulating the maturation pathways of antibody lineages in a gene-specific context. The mGSSP method can be used to build, compare, and plot GSSPs; we report the GSSPs constructed for 69 common human V genes (DOI: 10.6084/m9.figshare.3511083) and provide high-resolution logo plots for each (DOI: 10.6084/m9.figshare.3511085).