Fig. 5. Identification of potential downstream targets of ALKBH5 in MM cells.

A, B RNA-seq analysis of MM cells upon ALKBH5 KD. Heatmap (A) shows differential expression of indicated KEGG pathway genes in RPMI-8226 (left panel) and CAG (right panel) upon ALKBH5 KD. Venn diagram (B) shows the number of genes with significant changes in expression (fold change > 1.5) upon ALKBH5 KD in RPMI-8226 and CAG cells. C, D m⁶A-seq analysis of ALKBH5 KD in RPMI-8226 cells. Distribution of total m⁶A peaks in the indicated regions of mRNA transcripts in the control and ALKBH5 KD cells (C). Bubble plot (D) shows KEGG pathway analysis of the genes with significantly increased m⁶A abundance in ALKBH5 KD cells (P < 0.05). E Integrative analysis of RNA-seq and m⁶A-seq to identify the potential targets of ALKBH5 in MM. Up or Down indicates genes with significantly increased or decreased expression upon ALKBH5 KD in both RPMI-8226 and CAG cells as detected by RNA-seq (fold change > 1.5), respectively. Hyper indicates genes with significantly higher m⁶A abundance in m⁶A-Seq (P < 0.05). F, G Heatmap shows differential expression of overlapped genes in RMPI-8226 (F) and CAG (G) upon ALKBH5 KD. H Kaplan–Meier survival analysis in the Arkansas myeloma dataset [31]. The cutoff value was determined by the maximum standardized log-rank statistic. P-value was detected using the log-rank test. I Pearson’s correlation between ALKBH5 and TRAF1 mRNA expression in the indicated datasets [35–38]. The expression values were log₂ transformed.