Genome Therapy

Sequence-to-expression "oracles" (Enformer, Borzoi, AlphaGenome, Evo2) and the generative-DNA designers built on them all aim to predict how cis-regulatory DNA sets a gene's expression. But they are rarely scored on the quantity that matters for regulatory therapeutics: the change in expression (Δ) a real perturbation produces, measured against experimental ground truth and against a trivial baseline. CIS-Δ is a reproducible benchmark that does exactly that. It scores a model's predicted Δ for a (cell-context, cis-intervention) pair against experimental truth — single-cell CRISPRi/CRISPRa, eQTL fine-mapping, reporter MPRA — across seven scoring axes, anchored on 90,955 K562 CRISPRi pairs. We ship a one-file submission format, a scoring harness with gene-clustered bootstrap CIs and DeLong tests, an auto-generated leaderboard, and a self-test that round-trips committed truth to one part in a million. The finding is a carefully-bounded negative result. On distal-enhancer CRISPRi, a naive distance-to-TSS baseline out-ranks Borzoi and Enformer (AUROC 0.87), because 71–88% of real regulatory links fall outside the models' receptive field. On natural-variation eQTLs the oracles do clear the distance prior (AlphaGenome, significant after FDR correction) — but statistical fine-mapping still out-ranks them. And cell-type specificity can't be demonstrated at all: the eQTL ground truth is 93–96% shared across tissues, so that axis is under-powered by construction. Even the 2026 state of the art does not close the gap. Why it matters: before trusting a sequence model to design a regulatory edit, you need to know it can score one better than distance-to-TSS. CIS-Δ is the instrument that checks — and a living leaderboard the field can submit to.