Prime Editing Outcome Landscape (2D)

pegRNA Design

Primer-binding site (PBS) 13 nt

RT template / edit length 10 nt

Run

Set pegRNA parameters, then run an editing cycle.

Live Statistics

Predicted efficiency

—

Trials run

Edited

Indel

How it works

This is a 2D parameter-space view of the same prime-editing flap equilibrium modeled by the 3D pegRNA simulator — instead of animating one DNA molecule, it draws the whole outcome landscape at once.

Heatmap (top). Every pixel is one (PBS length, RT/edit length) combination scored independently with the model below; color encodes predicted edit probability, a red outline marks cells where indel risk is highest. The white crosshair is your current slider setting.
Flap race (middle). When you run a cycle, two bars grow in real time — the 3′ edited flap (green) versus the displaced 5′ flap (grey) — the same competitive growth the 3D view shows as spheres along the DNA backbone, here as a direct race.
Trial history (bottom). Each completed cycle appends one colored tile — green edit, grey revert, red indel — so streaks and drift become visible over many trials.

Identical literature-consistent probability model as the 3D simulator:

p_hybrid  = exp( -(PBS-13)^2 / 32 )        // Tm optimum near 13 nt
p_flap    = exp( -RT_len / 22 )            // longer edits excise less efficiently
p_edit    = min(0.95, 0.9 · p_hybrid · p_flap · (PE3 ? 1.55 : 1))
p_indel   = min(0.35, 0.015 + 0.0025·RT_len + (PE3 ? 0.045 : 0))
p_revert  = 1 − p_edit − p_indel

Real prime editors (PE2/PE3, Anzalone et al. 2019) show the same qualitative trends: an optimal PBS length around 12–14 nt, falling efficiency for longer insertions/edits, and a PE3 efficiency boost paired with a modest indel cost — the exact percentages here are illustrative, not measured values.

⚠ Couldn't load the engineSomething went wrong initializing the canvas. Reload the page.