Fig. 2.

Decitabine treatment of HL-60 cells results in global m⁶A hypermethylation. (a) Validation of CRISPRi decitabine screen hits shows that knockdown of m⁶A-reader/writer complex genes promotes resistance to decitabine treatment in HL-60i cells. HL-60i cells were transduced with a control sgRNA (black) or an active sgRNA (red or pink) and treated with DMSO or decitabine, and the proportion of sgRNA + cells in the decitabine condition relative to DMSO was observed over time. Data are shown as means ± SD, two sgRNAs per gene and two replicates per sgRNA. (b) Schematic of MeRIP-seq experimental design and computational workflow. (c) The FIRE algorithm (in non-discovery mode) shows the known m⁶A motif RGAC ([AG]GAC) is enriched among predicted MeRIP-seq peaks relative to randomly generated sequences with similar dinucleotide frequencies. Data are shown as a heatmap, where yellow indicates over-representation and blue represents under-representation. Color intensity indicates the magnitude of enrichment. (d) Metagene plot shows distribution of m⁶A sites along transcripts with differential regional methylation and enrichment of m⁶A sites near the end codon. Transcripts are grouped into CDS (protein coding region), 5’ UTR (untranslated region) and 3’ UTR methylation based on the identified m⁶A sites. (e) Differential methylation analysis shows significant changes in RNA methylation peaks in HL-60 cells treated with decitabine (relative to DMSO). Peaks are called using the RADAR algorithm and visualized as annotated volcano plots. Wilcoxon and t-tests are used to assess statistical significance of global hypermethylation.