Fig. 3: Evo 2 enables accurate zero-shot human variant effect prediction.

a, Overview of zero-shot variant effect prediction using Evo 2. Evo 2 was used to assign likelihood scores to human genetic variants, distinguishing pathogenic and benign variants in both coding and noncoding regions. b,c, Zero-shot evaluation of variant pathogenicity within the coding (b; n = 14,319 SNVs, n = 1,236 non-SNVs) and noncoding (c; n = 34,761 SNVs, n = 3,894 non-SNVs) regions. Shown are the AUROCs and AUPRCs for classifying pathogenic and benign variants from ClinVar, across models. For non-SNV evaluations, a modified version of PhyloP was used (Methods). d, Zero-shot evaluation on splice-altering variants in SpliceVarDB, split by exonic (n = 1,181) and intronic (n = 3,769) scoring. e, Evo 2 and other models were used to evaluate BRCA1 variant effect predictions against BRCA1 saturation mutagenesis data, comparing classification of loss-of-function versus functional and intermediate variants in both coding (n = 2,077 SNVs) and noncoding (n = 1,125 SNVs) regions. f, Evo 2 zero-shot likelihood scores plotted for loss-of-function (LOF) versus functional/intermediate variants (n = 3,893), demonstrating the ability of Evo 2 to separate these classes. P value calculated by two-sided Wilcoxon rank sum test. g, Evo 2 embeddings were extracted and concatenated to train a supervised classifier for BRCA1 variant effect prediction. h, Predictions of the supervised classifier on functional/intermediate variants compared with true loss-of-function variants on the test set (n = 789), with decision scores on the horizontal axis. P value calculated by two-sided Wilcoxon rank sum test. i, Comparison of a supervised classifier trained on Evo 2 embeddings on the BRCA1 test set against zero-shot baselines, highlighting the value of using Evo 2 embeddings to build lightweight supervised models.