Transcriptome-wide off target examining of AIM systems.
Purpose: Development of specific and precise RNA base editing toolkit. Methods: The transcriptome-wide off-target sites identification, annotation, and transcriptome-wide genes regulation of each editor were analyzed by RNA-seq data. The raw reads (.fastq) were first processed using Trim Glore (v0.6.7) to remove adapter sequences with default parameters. Then the trimmed data were used to remove rRNA data by Bowtie2 (v2.5.0) with key parameters –no-unal -I 1 -X 1000. The cleaned reads data were then aligned to the indexed human GRCh38 reference genome by STAR (v2.7.1a) with key parameters --outSAMstrandField intronMotif  --outFilterIntronMotifs RemoveNoncanonical. The aligned BAMs were added RG tag of sample information, sorted, indexed, stated by Samtools (v1.15.1) with default parameters. Then the processed BAMs were removed duplications by the Picard Markduplicates tool (v2.23.9) with key parameters ASO=coordinate REMOVE_DUPLICATES=true. Then remove duplicate BAMs were used to filter reads containing clips by Samtools with default parameters. All the cleaned BAMs were downsampled to an equivalent level for subsequent analysis to ensure a fair comparison of transcriptome-wide off-targets. The uniquely mapped reads in final BAMs were used to calculate gene expression level by Cuffdiff (v2.2.1) with default parameters. Finally, we filtered the differential expression genes using cutoff |Log2FoldChange| > 1 and P-value < 0.05, based on the Cuffdiff quantification results. Results: Our new programmable RNA base editing toolkits have high editing efficiency, flexible editing scope and high transcriptome-wide specificity. Conclusions: We deleveped verstaile RNA  editing toolkits enabling presice, specific and versatile RNA base editing. Overall design: We developed new RNA base editing toolkits using single strand RNA deaminase TadA. The RNA-seq data were used to evaluate  the transcriptome-wide off-targets of the newly developded RNA base editing toolkits.