Bio Genome Engineering Prime Editing Design

Version Compatibility

Reference examples tested with: BioPython 1.83+, PrimeDesign 1.2+ (Docker), PRIDICT2.0 (web/code).

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

PrimeDesign is Docker-only (no pip) and takes the edit inline in a single string with exact parenthesis notation (below) -- the most-hallucinated thing in PE tooling; verify it against the repo, never reconstruct from memory. Outcome-prediction models are trained mostly on HEK293T + small edits (<=3 bp); their scores are priors, not measurements, and degrade off-distribution. The PE system (MMR status, expressed vs synthetic pegRNA) drives efficiency more than any oligo tweak.

Prime Editing Design

"Install a precise small edit without a double-strand break" -> Establish the edit, cell type, MMR status, and delivery; choose the nick position/strand; design a panel of PBS x RTT combinations; pick the PE system; add the free wins (PAM-disrupting + MMR-evading silent edits, a 3' motif); rank with a model; and test.

• CLI (Docker): PrimeDesign generates ranked pegRNA + nicking-guide components from a reference + edit string
• Python: assemble/sweep PBS x RTT panels with Bio.Seq; enforce the don't-end-on-C and 5'-G rules
• Web/code: PRIDICT2.0 / DeepPrime rank candidates by intended-edit and indel rate

The Single Most Important Modern Insight -- there is no universal PBS/RTT optimum, and the system choice carries the order of magnitude

Two reframes:

1. PBS and RTT length are parameters to optimize per locus, not constants to look up. The PBS x RTT optimum is locus-specific -- it depends on local GC (which sets the PBS annealing Tm), the edit, the nick-to-edit distance, and chromatin. A high-GC target wants a short PBS; a low-GC target a long one; the "13/15" that is perfect at one locus is useless 200 bp away. A hard-coded default produces a sequence that looks valid, so nothing flags it until the data come back at 2%. The correct deliverable is a ranked panel (a few PBS x a few RTT x the viable nicks), tested or model-ranked -- emitting a single pegRNA is the tell of someone who has never run PE.

2. Prime editing efficiency is a cellular-genetics problem, not just oligo design. The cell's mismatch repair (MMR; MutSalpha/MutLalpha) detects the edit:original heteroduplex and excises the edited strand, reverting it and spawning indels. The biggest post-2019 jump was not a better PBS -- it was inhibiting MMR (MLH1dn -> PE4/PE5, ~7.7x average). The second was stopping the pegRNA 3' end from being degraded (epegRNA motifs; PE7's La protein). Design now means choosing the system (PE2 vs PE3b vs PE5max+epegRNA vs PE7) as much as the sequence. First branch: what edit, what cell type, MMR-proficient or not, expressed or synthetic.

Mechanism (the design rules fall out of it)

The prime editor (Anzalone 2019) is Cas9 H840A nickase + engineered M-MLV reverse transcriptase, programmed by a pegRNA = sgRNA (spacer + scaffold) with a 3' extension read 5'->3' as [RTT][PBS]. (1) The nickase cuts the protospacer (PAM) strand ~3 nt 5' of the PAM, exposing a free 3'-OH. (2) The PBS anneals to that nicked 3' end (the genomic strand becomes the primer). (3) The RT extends through the RTT, synthesizing a new 3' DNA flap that encodes the edit. (4) FEN1-type nucleases preferentially excise the unedited 5' flap, favoring incorporation of the edited 3' flap; ligation seals it. (5) The resulting heteroduplex is resolved by MMR -- which preferentially reverts the edit (hence the MMR section below). Consequences: PBS length is tuned by annealing Tm; RTT length = nick-to-edit distance + edit + 3' homology tail (~10-16 nt); efficiency falls as the edit moves farther from the nick; the edit must lie within the RTT.

The PE System Stack -- orthogonal axes, not a "bigger number is better" ranking

The expert move is to reason about which axis the problem needs: low efficiency in an MMR-active cell -> add MLH1dn; too many indels -> drop to PE2 or design PE3b (not PE3); short pegRNA half-life -> epegRNA/PE7. Note: in MMR-deficient lines (HCT116, many tumor lines) PE2 already behaves like PE4, so MLH1dn adds nothing -- benchmark numbers from such lines overstate the gain in MMR-proficient primary cells. PE5max + epegRNA is the modern default workhorse for hard, MMR-active contexts.

pegRNA Parameters & the Free Wins

• PBS (~8-17 nt; start ~11-15): tune to annealing Tm/GC, not a fixed length. pegFinder's starting heuristic is PBS ~= 24 - (GC%/5), clamped 8-17; test a small ladder (e.g. 10/13/15/17).
• RTT: = nick-to-edit + edit + ~10-16 nt 3' homology. Shorter RTT is usually more efficient -- use the shortest that spans the edit with adequate homology, then test a couple.
• Don't end the synthesized flap on a C (a C at the +1 templated position lowers efficiency; PrimeDesign exposes --filter_c1_extension).
• 5' G for U6: prepend a G if the spacer lacks one -- prepend, do not replace the first base (replacing creates a spacer:target mismatch).
• PAM-disrupting silent edit (free win): if the edit (or an added silent change) destroys the protospacer/PAM, the editor cannot re-nick the edited strand -> fewer indels, and the change doubles as an MMR-evading mismatch. Always check whether the edit can be routed to disrupt the PAM.
• MMR-evading bystander edits (free win): add 1-2 silent substitutions next to the intended edit to make a >=3-bp edited "bubble" that MMR recognizes less efficiently -> higher correct-edit yield. Trivial in coding sequence (synonymous codons); the tactic of choice before reaching for MLH1dn.

epegRNA 3' Motifs & pegRNA Stability

The pegRNA 3' extension (RTT+PBS) is single-stranded RNA that is exonucleolytically degraded before it can prime RT -- an invisible failure (the molecule is made, just chewed back). epegRNAs append a structured pseudoknot motif to the 3' end (Nelson 2022): use tevopreQ1 by default (~3-4x gain, no added off-target); mpknot is larger and benefits most from a pegLIT-designed linker (tevopreQ1/evopreQ1 often work linker-free). PE7 (La protein) attacks the same degradation from the protein side and is partly redundant with epegRNAs (PE7's gains are largest with plain pegRNAs) -- don't stack them as if independent. For synthetic (non-expressed) pegRNAs where a folded motif is awkward, PE7 / La-optimized 3' chemistry is the lever instead.

Outcome Prediction (rank, but still test)

Limits: trained mostly on HEK293T + small edits; scores degrade for large edits, untrained cell types, primary/iPS cells, and in vivo loci. A high score says "worth synthesizing," not "will work in the target cell." Report edit:indel purity, not efficiency alone (PE3's indel liability hides when only the intended-edit rate is reported).

Large / Advanced Edits (single-pegRNA PE runs out of room)

Route "knock in a 2 kb reporter" to twinPE+integrase/PASTE (or HDR/HITI) -- a single giant-RTT pegRNA is a category error.

Decision Tree by Scenario