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Class-switch recombination (CSR) is an integral part of B cell maturation. Steady-state analyses of isotype distribution (e.g. B cell receptor [BCR] repertoire analysis of snapshots during an immune response) do not directly measure CSR dynamics, which is crucial in understanding how B cell maturation is regulated across time. We present sciCSR (pronounced ‘scissor’, single-cell inference of class switch recombination), a computational pipeline which analyses CSR events and dynamics of B cells from single-cell RNA-sequencing (scRNA-seq) experiments. sciCSR re-analyses transcriptomic sequence alignments to differentiate productive heavy-chain immunoglobulin transcripts from germline “sterile” transcripts. From a snapshot of B cell scRNA-seq data, a Markov state model is built by the pipeline to infer the dynamics and direction of CSR. Applying sciCSR on SARS-CoV-2 vaccination time-course scRNA-seq data, we observe that sciCSR predicts, using data from an earlier timepoint in the collected time-course, the isotype distribution of BCR repertoires of subsequent timepoints with high accuracy (cosine similarity ∼ 0.9). sciCSR also recapitulates CSR patterns in mouse models where B cell maturation was perturbed using gene knockouts. sciCSR infers cell state transitions using processes specific to B cells, identifies transitions which are often missed by conventional RNA velocity analyses, and can reveal insights into the regulation of CSR and the dynamics of B cell maturation during an immune response.

Background: Known endogenous mutators include certain APOBEC family members, whose mRNA levels have been implicated in various cancers. Other important nucleic acid deaminases include ADAR family of proteins, with some recent evidence supporting their potential mutator activity. Some external mutators have also been reported to act through endogenous ones. Although the ADAR and particularly APOBEC mutations are infrequent among cancer genomes, their potential contributions in cancer mutagenesis might not be underestimated. Methods: We assessed 10,294 exomes from 32 TCGA cancer types for mutations among fourteen APOBEC/ADAR family members. The mean number of single nucleotide variants (SNVs) and insertions/deletions (indels) was compared among those exomes with nonsilent APOBEC/ADAR mutations and those with wild-type APOBEC/ADAR or silent mutations. Multivariate analyses identified the relative impacts of APOBEC/ADAR mutations and mRNA levels as well as DNA repair/replication defects, as determined by mutations in KEGG pathway genes, on main variant classes across pancancer exomes. Results: Preliminary analysis identified higher mean number of both SNVs and indels among those exomes with any of the fourteen APOBEC/ADAR genes mutated compared to those with wild-type ones. Further analyses showed higher mean number of certain indel variants among those exomes with nonsilent APOBEC1 (A1; 6.1 fold), A3B (5.1 fold), A3C (20.5 fold), or ADAR (2.2 fold) mutations, and higher mean number of T>N SNVs (2.8 fold) among those with nonsilent ADARB1 mutations compared to silent ones, suggesting their true implication in cancer hypermutation. Besides DNA repair/replication defects, multivariate analyses revealed that C>G variants were determined mostly by APOBEC (A3B, A3A, A3G) mRNA levels, while other SNV classes determined mainly by various APOBEC/ADAR mutations. Indels were found to be determined mainly by mutations in A1, A3B, ADAR, and ADARB1, with a small impact of A1 mRNA level. The impacts of DNA repair/replication defects were more prominent on indels as well as C>G SNVs. Conclusions: These results provide a landscape of cancer variants as correlated with endogenous mutators and DNA repair defects. They propose the implication of certain APOBEC/ADAR mutations in most SNV classes as well as indels, in contrast to C>G SNVs mostly determined by APOBEC overexpression. These potentially reflect the gain/ loss of function impacts of various mutations and/or oligomerization capacities of both families. Further analyses linking APOBEC/ADAR mutations and mRNA levels with distinct mutational signatures are shown in the accompanying abstract “Distinct pancancer mutational signatures are determined by APOBEC/ADAR aberrations”. Citation Format: Ahmadreza Niavarani, Milad Bagheri, Joseph CF Ng, Franca Fraternali, Reza Malekzadeh. APOBEC/ADAR aberrations are potentially implicated in certain pancancer hypermutation patterns [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1318.