Fig. 5: Fate mapping implicates phenotypic plasticity within a clonally expanded population.

a Kinetics of viral load (shaded areas, measured in international units (IU)) and IFN- production (Spot forming unit (SFU/Million PBMC)) for the GPR- and ATD-specific CD8⁺ T cell responses identified in individual CL-MCRL. b Distribution of T cell phenotypes over time in GPR-specific cells identifying a monoclonal response (identical TCRαβ sequence). c PAGA graph representation and clustering of GPR-specific cells (N = 244) revealing ten connected clusters (line thickness represents the probability of connectivity). d PAGA graphs coloured by sample viremia, disease stage, T cell phenotype and IFN-γ ELISpot. e Dot plot of selected genes identified from differential expression analysis (derived from pairwise comparisons with a two-sided hurdle-model from MAST) on the PAGA clusters. Only significant genes are shown (p < 0.05, |log₂(FC)| ≥ 0.3, coloured). Dot size represents the proportion of cells with non-zero expression. f Trajectories derived from scRNA-seq data with coloured pseudotime values. Loess curves represent the changes along the trajectories of both single-cell protein and gene expression values. The 95% confidence intervals are denoted by shaded regions. Growth rates are estimated from the calculated size of T cell phenotypes over pseudotime values for each trajectory. g Dot plot of selected differentially expressed genes (derived from pairwise comparisons with a two-sided hurdle-model from MAST) between the early and late phases of each trajectory (p < 0.05, |log₂(FC)| ≥ 0.3). Dall size represents the proportion of cells with non-zero expression. Early ≤120 DPI, late >120 DPI.