Extended Data Fig. 2: Transcriptome-wide analysis of METTL16 methyltransferase activity.
From: METTL16 exerts an m6A-independent function to facilitate translation and tumorigenesis
a, Validate the knockdown (KD) efficiency of the shRNAs against METTL3, METTL14, or METTL16 via Western blotting. Images are representative of three biologically independent experiments with similar results. b, Expression of METTL3 and METTL14 in HEK293T (left) and HepG2 (right) cells upon METTL16 KD. Images are representative of two biologically independent experiments with similar results. c, Global changes of m6A abundance upon METTL3, METTL14, or METTL16 KD in HEK293T cells. Data are mean ± s.d. Statistics: unpaired, two-tailed t-test. n = 3 independent experiments. d, Validation of the KO efficiency of the gRNAs against METTL3, METTL14, or METTL16 via Western blotting in HEK293T cells. The RNA samples from sgMETTL3-3, sgMETTL14-3, and sgMETTL16-3 cells, along with the control cells, were collected for subsequent m6A MeRIP-Seq. The 2 independent experiments have been performed with similar results. e, Venn diagram showing the overlap of the transcripts with decreased m6A levels between the two biological replicates of sgMETTL3-3, sgMETTL14-3, and sgMETTL16-3. f, The frequency distributions of the m6A-hypo peaks caused by the KO of METTL3, METTL14, or METTL16 as detected by m6A MeRIP-Seq with poly(A) RNA from HEK293T cells. Only the significantly decreased m6A peaks (P < 0.01) were classified as m6A-hypo peaks and shown in the plot. g, Venn diagram showing the overlap analysis of the m6A-hypo transcripts induced by the KO of METTL3, METTL14, and/or METTL16 (left panel). Gene set enrichment analysis (GSEA) of the 334 METTL16-specific targets was performed, and the top 10 enriched pathways were shown (right panel). h, Global distribution of specific m6A-hypo peaks induced by the KO of METTL3, METTL14, and/or METTL16. i, Venn diagram showing the overlap between the 334 METTL16-specific targets and the transcripts with m6A-hypo peaks in METTL3 KD (left panel) or METTL14 KD (right panel) cells. j, Scatterplot showing the high reproducibility of the RIP-seq replicates of METTL3, METTL14, and METTL16. The Pearson correlation coefficients (R) of the normalized RIP-seq reads across the two replicates were calculated and displayed in the plots. A smoother regression line and 2D kernel density contour bands were also presented. P values were determined by Pearson’s correlation test. k, Venn diagram showing the overlap among METTL3, METTL14, and METTL16-bound transcripts (left panel) and the top one binding motif of the 3,206 specific METTL16-bound transcripts (right panel). l, Venn diagram showing the overlap between the METTL16-bound transcripts (RIP-seq) and the METTL16 KO-mediated m6A-hypo transcripts (MeRIP-seq) (left panel). Both seq analyses were conducted with poly(A) RNA from HEK293T cells. The top one consensus binding motif identified in METTL16-bound transcripts with METTL16 KO-induced m6A-hypo peaks was shown (right panel). m, Violin plots showing the significant m6A-hypo peaks induced by METTL16 KD in nascent RNA and nuclear poly(A) RNA from HEK293T cells. For each violin, the minimum, first quartile, median, third quartile, and maximum were presented. The average value of Log2(fold change) from each group was also displayed. The P values were calculated by unpaired two-sided t-test.
