Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress

Hugging Face Daily Papers Papers
crispr single-cell genomics perturbation geometric-analysis foundation-models bioinformatics

Summary

This paper introduces Shesha, a geometric stability metric that quantifies directional coherence of single-cell CRISPR perturbation responses using mean cosine similarity, revealing regulatory architecture and predicting cellular stress across 2,200+ perturbations in five CRISPR datasets.

Genome engineering has achieved remarkable sequence-level precision, yet predicting the transcriptomic state that a cell will occupy after perturbation remains an open problem. Single-cell CRISPR screens measure how far cells move from their unperturbed state, but this effect magnitude ignores a fundamental question: do the cells move together? Two perturbations with identical magnitude can produce qualitatively different outcomes if one drives cells coherently along a shared trajectory while the other scatters them across expression space. We introduce a geometric stability metric, Shesha, that quantifies the directional coherence of single-cell perturbation responses as the mean cosine similarity between individual cell shift vectors and the mean perturbation direction. Across five CRISPR datasets (2,200+ perturbations spanning CRISPRa, CRISPRi, and pooled screens), stability correlates strongly with effect magnitude (Spearman ρ=0.75-0.97), with a calibrated cross-dataset correlation of 0.97. Crucially, discordant cases where the two metrics decouple expose regulatory architecture: pleiotropic master regulators such as CEBPA and GATA1 pay a "geometric tax," producing large but incoherent shifts, while lineage-specific factors such as KLF1 produce tightly coordinated responses. After controlling for magnitude, geometric instability is independently associated with elevated chaperone activation (HSPA5/BiP; ρ_{partial}=-0.34 and -0.21 across datasets), and the high-stability/high-stress quadrant is systematically depleted. The magnitude-stability relationship persists in scGPT foundation model embeddings, confirming it is a property of biological state space rather than linear projection. Perturbation stability provides a complementary axis for hit prioritization in screens, phenotypic quality control in cell manufacturing, and evaluation of in silico perturbation predictions.
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Paper page - Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress

Source: https://huggingface.co/papers/2604.16642

Abstract

Genomeengineeringhasachievedremarkablesequence-levelprecision,yetpredictingthetranscriptomicstatethatacellwilloccupyafterperturbationremainsanopenproblem.Single-cellCRISPRscreensmeasurehowfarcellsmovefromtheirunperturbedstate,butthiseffectmagnitudeignoresafundamentalquestion:dothecellsmovetogether?Twoperturbationswithidenticalmagnitudecanproducequalitativelydifferentoutcomesifonedrivescellscoherentlyalongasharedtrajectorywhiletheotherscattersthemacrossexpressionspace.Weintroduceageometricstabilitymetric,Shesha,thatquantifiesthedirectionalcoherenceofsingle-cellperturbationresponsesasthemeancosinesimilaritybetweenindividualcellshiftvectorsandthemeanperturbationdirection.AcrossfiveCRISPRdatasets(2,200+perturbationsspanningCRISPRa,CRISPRi,andpooledscreens),stabilitycorrelatesstronglywitheffectmagnitude(Spearmanρ=0.75-0.97),withacalibratedcross-datasetcorrelationof0.97.Crucially,discordantcaseswherethetwometricsdecoupleexposeregulatoryarchitecture:pleiotropicmasterregulatorssuchasCEBPAandGATA1paya“geometrictax,“producinglargebutincoherentshifts,whilelineage-specificfactorssuchasKLF1producetightlycoordinatedresponses.Aftercontrollingformagnitude,geometricinstabilityisindependentlyassociatedwithelevatedchaperoneactivation(HSPA5/BiP;ρ_{partial}=-0.34and-0.21acrossdatasets),andthehigh-stability/high-stressquadrantissystematicallydepleted.Themagnitude-stabilityrelationshippersistsinscGPTfoundationmodelembeddings,confirmingitisapropertyofbiologicalstatespaceratherthanlinearprojection.Perturbationstabilityprovidesacomplementaryaxisforhitprioritizationinscreens,phenotypicqualitycontrolincellmanufacturing,andevaluationofinsilicoperturbationpredictions.

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