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bioRxivGenomicsPreprint

simSOMA: a cell-lineage based simulator of the somatic VAF spectrum in plants

Frank M. JohannesiD

PDFDOICode

Abstract

Plants accumulate somatic mutations during growth, some of which spread into branches, organs, or reproductive tissues. These variants are of growing interest because they underlie bud-sport traits in perennial crops, contribute to within-organism selection, and are a source of heritable genetic variation. Recent genomic sequencing of bulk or layer-enriched plant tissues has revealed complex variant allele-frequency (VAF) spectra. Interpreting these spectra requires modelling how somatic mutations are filtered or amplified by shoot growth, branching, and organ formation, a problem that is difficult to derive analytically. Here, we present simSOMA, a modular simulator linking plant topologies to shoot apical meristem cell-lineage dynamics. simSOMA models mutation accumulation during stem-cell self-renewal, clonal expansion to the meristem periphery, branch founding, and organ formation. We demonstrate how simSOMA isolates developmental processes that shape organ-level VAF spectra and among-organ variant sharing, and transforms spectra for bulk or layer-enriched sampling, phased or unphased readouts, and read-level sequencing noise. SAM layers can be simulated as independent cell lineages and combined into bulk tissue samples. simSOMA can be used to explore developmental hypotheses about the origin of somatic variation, and to design somatic sequencing experiments and variant-detection strategies. simSOMA is available at https://github.com/jlab-code/simSOMA.

In-depth summary

Claude Opus 5.5 · xhigh effort · 8 Nov 2026 · from the full text of version 2 (12 Oct 2026) · CC BY 4.0

simSOMA links plant branching topology to meristem cell-lineage dynamics; in simulations, niche size and turnover drive fixation, while terminal organ growth produces most private low-frequency variants.

Bulk or layer-enriched sequencing of plant tissues yields VAF spectra shaped jointly by stem-cell dynamics, branching and organ-founding bottlenecks, organ growth and the assay, which are hard to treat analytically. Prior models used idealized branching, turnover fixed by niche size or phenomenological bottlenecks, and omitted the steps from niche to sequenced organ; simSOMA models each step separately on any rooted topology, deriving bottleneck strength from measurable cell numbers.

Key results

  1. SuggestedIn a factorial scan on a 20-organ branched topology, smaller niches, higher turnover, fewer branch or organ precursors and greater developmental depth all raised the fixed fraction and lowered the intermediate fraction, so these parameters act in overlapping ways.

    Grid of m from 2 to 20, 16 ρ values between 0 and 1, 12 Pb values (1 to 20) and 12 Po values (1 to 30), with 50 replicates per combination; C = 64, organs of 10^4 cells with 1% (100 cells) sampled, organs on branch orders 1 to 5. Organs at developmental depth 6 with small m gave bimodal spectra; depth 2 with larger m kept more unfixed variants at or above τ = 0.05. · Global parameter scan identifies key VAF…

  2. SuggestedTerminal organ growth produced most private variants, concentrated at low VAF, with the cumulative count above frequency q linear in 1/q; the slope reflects the per-division mutation rate during organ growth, while Po mainly shaped variants already present at organ initiation.

    m = 4, ρ = 0, C = 64 and Pb = 4 held fixed on the 20-organ topology while Po and O varied. Growing from Po to O cells takes O − Po divisions (2(O − Po) daughter cells); about 2(1/q − Po) daughters seed at least a fraction q of the organ, a prediction that agreed closely with full simulations (Supplementary Fig. S3). Private fraction rose strongly with O and stayed high across Po for large O. · Organ growth is the main source of private…

  3. ShownWithin the model, the chance that a branch is founded by more than one clonal sector depends only on ϕ = (Peff − 1)m/C, with Peff = min(Pb, m) (for C ≥ m), so branch founding is predominantly monoclonal unless C < m(m − 1), and Pb cannot be identified from mutation data beyond m.

    Topology with five lateral branches, one sampled organ each; fixed fraction scanned over Pb and C at m = 3 and m = 12 fell with Pb and plateaued once Pb reached m. With a uniform focal position and C divisible by m, π ≤ (m − 1)m/C, so monoclonal founding predominates unless C < m(m − 1); organ founding, where Po is not capped by m, can be strongly polyclonal. · Branching bottlenecks depend on precursor number…; Conclusion and Discussion; Figure legends

  4. SuggestedLayer mixing and unphased readout rescale layer-fixed variants to lower VAFs, and read-level sampling mainly removes the low-frequency and minor-layer signal: in simulated unphased bulk data at mean depth 60 only the L2-fixed peak stayed clearly resolvable, and most private organ-growth variants go undetected.

    Ten simulated trees, three independent layers with contributions (0.10, 0.70, 0.20); the exact unphased bulk transformation places layer-fixed variants at 0.05, 0.35 and 0.10. At mean depth 60, L1- and L3-fixed variants were still 78% and 93% detected but overlapped low-frequency variants. True VAF at which half of variant-organ occurrences were detected: about 0.09, 0.03 and 0.013 at mean depths 20, 60 and 150. · From developmental to observed VAF spectra; Thus, for a three-layer bulk sample with…; Read-level observation; Figure legends

  5. SuggestedOn a single 200-year axis, niche size m and turnover ρ dominated the fixed, intermediate, private and sharedness statistics; higher ρ raised both private fraction and sharedness, while spiral phyllotaxy left these marginals nearly unchanged but added structure to pairwise organ sharing.

    20 organs sampled at regular positions; smaller m gave higher fixed fractions and higher ρ raised fixation for most m. With spiral phyllotaxy, off-diagonal pairwise Jaccard sharing appeared at ρ = 0 and was strongly reduced at ρ = 1. Values of m up to 20 were simulated, but the paper treats m ≤ 4 as the typical range (2 to 4 persistent ASCs per layer). · Stem-cell turnover shapes VAF spectra and…; Figure legends

Methods, data and reproducibility

Forward simulator that traverses a user-defined rooted acyclic plant topology, running modules for stem-cell self-renewal (niche size m, turnover ρ), clonal expansion to a sectorized periphery of C cells, contiguous recruitment of Pb branch or Po organ precursors, and organ expansion to O cells; developmental VAFs are rescaled post hoc for layer mix, phasing and read-level noise.

  • Simulated 200-year branched topology with sampled organs on branch orders 1 to 5 (global scan, organ-formation and read-level runs) · n = 20 sampled organs
  • Simulated single-axis 200-year topology with organs at regular positions (turnover and phyllotaxy runs) · n = 20 organs
  • Simplified branching topology: main axis with lateral branches, each ending in one sampled organ (branch-founding runs) · n = five lateral branches
  • Three independently simulated SAM layers on the branched topology for read-level observation runs · n = ten trees
  • Topologies and configuration files (Supplementary files 1 and 2) and Fig. 6C-I settings and scripts (Supplementary file 3)
  • Archived simSOMA v0.2.3 release (Zenodo) · 10.5281/zenodo.23274014
Methods & tools
simSOMA, Python, NumPy, pandas, Matplotlib, pip, Zenodo
Software & environment
Python ≥3.10 with NumPy, pandas and Matplotlib; pip-installable; run from configuration files via a CLI (simsoma run config.json). Release v0.2.3 archived on Zenodo; Fig. 6C-I and Supp. Figs. S1 to S4 used v0.2, with simulation code identical to v0.2.3.
Reproducibility gaps
Topologies and configs are given as Supplementary files 1 to 3, with no repository URL. Figs. 2 to 5 used v0.1.0-beta (commit 4ec934e), whose displacement rule for ρ > 0 differs from the current release; the paper reports fraction changes below 0.005 only in the settings it checked.
Limitations (6)
  • A weak bottleneck needs few amplification divisions between niches (small C/m), so bottleneck strength cannot be set independently of the mutational input during amplification. · stated by the authors
  • Branch and organ founding draw on one shared amplified periphery, so precursors that divide less than their neighbours (reported for detached-meristem initiation) cannot be modelled without event-specific amplification. · stated by the authors
  • SAM layers are simulated as independent lineages sharing topology and event positions but not cells, so lineage exchange between layers, occasional in angiosperms and more frequent in gymnosperms, is not modelled. · stated by the authors
  • Simulated spectra were not compared with empirical sequencing data; the paper describes the simulator and does not fit or validate it against real plants. · stated by the authors
  • For branch founding, mutation data constrain only the compound quantity (Peff − 1)m/C, not its components; the authors note that pinning down parameters measurable through histology or imaging, such as niche size, would lessen this redundancy. · stated by the authors
  • All results come from a few author-designed topologies (a 20-organ branched tree, a single axis, a five-branch tree), with C and mutation rate fixed in the global scan, so the quantitative fractions may not transfer to real tree architectures. · noted in this summary

Read this if you sequence somatic mutations in trees or other plants and want a forward model to interpret bulk or layer-enriched VAF spectra or to plan sequencing depth and organ sampling.

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