Figure 2: Functional 3’UTR elements overlap known 3’UTR annotations.

a, Scatterplot comparing correlations between activity effects and 3’UTR structure (more negative minimum free energy, left) and percent GC (right). HMEC log₂FC activity data is representative and plotted. Pearson’s r and its statistical significance are displayed. b, (top panel) Enrichment of significantly active 3’UTRs with known 3’UTR attenuating (AU-rich, Pumillo, and miRNA) and augmenting (CU-rich Element) annotations. Average log₂FC of 3’UTR activity in MPRAu across all cell types with specified annotation plotted, significance denoted as *** p-value<0.001, ** p-value<0.01, * p-value<0.05, using a two-sided Wilcoxon rank-sum test. (bottom panel) Barplot of the allelic skews for variants that acquire 3’UTR annotations of the class listed above. c, Variants with high allelic skew (| log₂FC Skew |≥1 ) have greater in-vivo eCLIP RBP binding scores than variants with a lesser allelic skew (* p-value<0.05, using a one-sided Wilcoxon rank-sum test). d, Each box in the heatmap measures the significance of attenuation (t-test) when cell-type-specific MPRAu-measured 3’UTR activity (y-axis) is subsetted on the top 10 most abundant miRNAs across the cell types tested (x-axis). Across 4 cell types (K562, HMEC, GM12878, SK-N-SH), 3’UTR activity was most significantly attenuated when subsetting on cell-type matched miRNAs.