Extended Data Fig. 4: Probing the nucleolar proteome with 47S O-MAP-MS.
a, Receiving-Operator Characteristic (ROC) analysis of the 47S vs 7SK O-MAP-MS experiment. True Positive and False Positive proteins were defined using lists of exclusively nucleolar and exclusively nucleoplasmic proteins, respectively, as reported by the Human Protein Atlas (HPA). An Area Under the Curve (AUC) of nearly 1.0 suggests strong and highly sensitive selectivity for nucleolar proteins over the nucleoplasmic proteome. b, These data were used to derive an optimal Log2(fold change, 47S/7SK) cutoff value of 0.523, and to define a putative list of 258 O-MAP core nucleolar proteins, as described in (Fig. 3). c–e, Parallel analysis using (47S/Scramble controls), instead of (47S/7SK). c, Volcano plot and histograms of showing the enrichment of HPA-nucleolar, HPA-Nucleoplasmic, and HPA-bilocalized proteins, using the same protein marker reference lists as in (a, b), and (Fig. 3c, d). Benjamini Hochberg corrected p-values (FDR). d, ROC analysis of the (47S/Scramble) data demonstrates slightly lower sensitivity than that of the (47S/7SK) analysis, though still exceptionally. e, As in (b), these data were used to determine an optimal Log2(fold change, 47S/Scramble) cutoff value of 2.201, defining a putative cohort of 286 O-MAP core nucleolar proteins. f, The putative nucleolar proteomes derived from the (47S/7SK) and (47S/Scramble) ROC analyses show considerable overlap (66–73%). Outliers were used for Gene Ontology (GO)-term analysis. Factors uniquely captured by the (47S/7SK) analysis were highly enriched for ribosome biogenesis factors, while those unique to the (47S/Scramble) analysis were enriched for nucleoplasmic functions. This suggests that the (47S/7SK) comparison more precisely captures the nucleolar proteome. Hypergeometric test with Benjamini-Hochberg correction.
