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     Long Response


    Germinal-center AID-Confetti (Brainbow) clonal-dynamics visual summary

    Visualizations below use published summary statistics from AID-Confetti/Brainbow lineage-tracing and related germinal-center analyses (key numbers cited directly). Visualize-first, explain-second: three compact Plotly figures (each >=400px tall), immediate Plotly.newPlot() calls follow each container.

    The AID-Confetti study detected large clonal bursts whose parental-node fraction had mean ~0.32 Β± 0.14 across identified bursts (n=12). This indicates that when bursts occur, a single parental node can represent ~30% of sampled GC lineage reads in that event β€” a hallmark of clonal bursting under the LAST model (see citations below).

    The study reports a measured SHM rate of ~0.10 Ighv mutations per daughter cell during clonal bursts (supporting a LAST model with reduced SHM during inertial DZ proliferation), compared with canonical constant-per-division values (~0.333 per daughter) used in MANY prior models β€” this difference explains how bursts preserve affinity while expanding clone size.

    DeWitt et al. extrapolated that, under the LAST model, the largest parental burst node would correspond to ~193 Β± 186 cells in a hypothetical 2000-cell GC, versus a tiny parental representation under EACH (0.69 Β± 0.60), illustrating how LAST produces large clonal dominance when inertial divisions suppress SHM until the final DZ passage.

    Key evidence & concise interpretation (citations)

    • Observed clonal bursts, measured parental-node fractions (mean ~0.32 Β± 0.14, n=12) and low SHM per daughter (~0.10 mutations/Ighv/daughter) support a LAST model where SHM is largely restricted to the last DZ division, enabling large, high-affinity clonal expansions during bursts β€” direct data and interpretations from the AID-Confetti/Brainbow lineage-tracing study.
    • Mechanistic conclusion: transient suppression of SHM during rapid DZ proliferation preserves affinity and produces larger parental nodes when cells later re-enter selection (LZ/G0-like) β€” consistent with LAST vs EACH comparisons and simulations reported in the same study.

    Primary citation for the AID-Confetti/Brainbow clonal-burst dataset and simulations:

    Related work showing antibody feedback and epitope masking can alter clonal composition of GCs (complements interpretation of how feedback and burst dynamics interact):

    Short caveats & blindspots:

    • Data derive from mouse model Aicda-CreERT2;Rosa26-Confetti GCs using defined antigens β€” generalizability to all antigens, larger GC sizes, or human GCs is not guaranteed and was discussed by the authors (limitations include sampling fraction and model assumptions) .
    • Summary statistics plotted here are taken from published aggregates (means, SDs, point estimates) rather than raw single-cell read tables; for per-GC raw plotting/alternative metrics (phylogenies, branchwise SHM distributions, per-GC parental fractions) we can fetch raw accession (GSE285185) and produce per-GC reconstructions on demand.

    If you want: I can (via the Run AI Scientist Analysis button) fetch GSE285185 raw Igh sequences, reconstruct per-GC lineage trees, compute per-GC parental fractions and SHM distributions, and produce higher-resolution Plotly figures (phylogenetic fanplots, Sankey clone flows, per-clone mutation histograms) β€” click the button to start an automated analysis pipeline.



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    Updated: March 17, 2026

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    Fetching GSE285185 Igh VDJ raw reads, assigning clones, building per-GC phylogenies, and computing parental-node fractions and SHM-per-division metrics to reproduce DeWitt et al. figures.



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    Create Graphs: Germinal Center Clonal Dynamics Plot Using AID-Confetti Raw Data Science Art

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