Fig. 4: Joint analysis of m⁶A-QTLs and other molecular QTLs.

a, The estimated fractions of m⁶A-QTLs shared with other molecular phenotypes, measured by π1, the fraction of true positives. The five bars in each panel correspond to random SNPs and m⁶A-QTLs at different P value cutoffs. Error bars show 80% confidence intervals (n = 100 bootstraps). b, Low correlations of effect sizes between m⁶A-QTLs and related molecular QTLs, estimated from linear regression (n = 709, 884, 742, 884 and 393 SNPs-gene pairs for APA, Expression, Decay, Ribosome and Protein, respectively). c, Correlations of effect sizes between m⁶A-QTLs and related molecular traits QTLs stratified by the m⁶A sites bound by different RBPs. Correlations are determined by linear regression. Shown are RBPs having at least one trait significantly correlated trait with m⁶A at FDR < 10%. Pearson correlations are shown by color code and P value by dot size. d, RNA binding proteins (RBPs) that modulate the impact of m⁶A depletion on translation efficiency. For each RBP, Welch’s two-sided t test is used to test the log₂ fold-change in translation efficiency in RBP targets vs. non-targets, upon METTL3 knockdown (n = 11,412 transcripts). RBP targets are defined by transcripts harboring m⁶A peaks that are bound by certain RBP. Shown are RBPs with FDR < 5% (Benjamini & Hochberg method). RBPs with significant correlation between m⁶A-QTL and ribosome-QTL effect sizes are highlighted in blue. e, Distribution of log₂ fold-change in translation efficiency of YBX3 targets, upon m⁶A (METTL3) depletion, in comparison with non-targets. P value is computed by Welch’s two-sided t test (n = 11,412 transcripts).