Elevated RNA Editing Activity Is a Major Contributor to Transcriptomic Diversity in Tumors

Transcription

1 Cell Reports Supplemental Information Elevated RNA Editing Activity Is a Major Contributor to Transcriptomic Diversity in s Nurit Paz-Yaacov, Lily Bazak, Ilana Buchumenski, Hagit T. Porath, Miri Danan-Gotthold, Binyamin A. Knisbacher, Eli Eisenberg, and Erez Y. Levanon

2 A B 1 Mismatches intersecting Refseq in sense orientation (%) Percent of SNPs in unique mismatches C D 1 1 Percent of mismatches in genes that are on sense strand Mismatches in plus orientation (%) Mismatch A2G Control

3 Figure S1, Related to Figure 2. Clean editing signal in A-to-G compared to other mismatches A clear editing signal in Alu repeats reflected in (A) A-to-G mismatches originate from the expressed strand of the Alu repeat. Percentage of mismatches intersecting Refseq in sense orientation. As the sequencing data is not stranded, generally one cannot distinct A-to-G mismatches from T-to-C ones. However, for those Alu repeats that overlap a RefSeq gene, we plot the fraction of A-to-G mismatches (A on the expressed strand) among all A-to-G and T-to-C mismatches. The clear bias towards the expressed strand (many more A-to-G than T-to-C mismatches) supports the notion that these mismatches are due to RNA editing. In contrast, the control (G-to-A) shows no dominance to the expressed strand (roughly same number of G-to-A and C-to-T) on the expressed strand. (B) Many of the non-a-to-g mismatches are known SNP. Percent of SNPs in mismatch sites for A-to-G and control mismatches detected by the hyper-editing scheme show, for the different tissues, a minute fraction of the A-to-G sites (average 2%) overlapping known SNPs. Control sites exhibit a high SNPs content (average 1%). (C) Percentage of mismatches intersecting RefSeq in sense orientation (same as panel A) for the hyper-editing detection approach. (D) Hyperediting A-to-G signal does not show read-strand preference. Mismatches in plus and minus strand of sequencing reads of A-to-G and control were analyzed. Reads are generated in the sequencing reaction from both orientation, and thus mismatches originating from the RNA molecule are expected to be equally distributed among the two sequencing directions. Indeed, A-to-G mismatches show no strand preference, while control mismatches (the second most frequent mismatch in each specific RNAseq) suffer from high and variable strand preference (and huge variation) suggesting these mismatches are partly due to a sequencing artifact.

4 A 1. BRCA p = Survival Probability..25 Index <.51 Index >= Days Index <.51 Index >= Numbers at risk B AZIN1 C Index Cutoff QuantileCutoff PValue FDR BLCA E-1 2.8E-1 BRCA E-2 1.3E-1 COAD E-1 3.5E-1 HNSC E-4 5.5E-3 KIRC E-1 3.5E-1 LIHC E-3 5.5E-3 LUAD E-1 2.4E-1 PRAD THCA E-1 3.5E-1

5 Figure S2, Related to Figure 3. Kaplan-Meier analysis for the different cancer tissues (A) Low Alu editing index correlates with a better prognosis. Kaplan-Meier curve in breast cancer, based on an index cutoff. (B) Kaplan-Meier curve for liver cancer based on AZIN1 editing level. The cutoff is 1% over editing (patients for which AZIN1 editing level increases by 1% or more in tumor compared to its matched normal sample). (C) Kaplan-Meier analysis for the different cancer tissues. Survival analysis was done for each tissue using the Kaplan-Meier curve based on AEI Values. Breast, head and neck and liver cancers revealed significant difference in survival depending on the AEI values. Note that 8/9 of the tests are below a cutoff of FDR=.35, indicating that most of the cancer types can be successfully classified using the AEI.

6 Table S1, Related to table 1. Editing differences between cancer and normal samples in the hyper-editing detection scheme BLCA (n=13) BRCA (n=95) LIHC (n=3) HNSC (n=29) LUAD (n=36) %Map_raeds Total Editing sites (ES) 7,497 1,138 11,956 17,424 1,897 17,981 3,763 1,359 7,19 9,426 uniq_eswosnp 4,792 6,421 7,87 9,864 5,926 9,721 2,3 5,93 4,759 5,824 KIRC (n=62) PRAD (n=31) THCA (n=42) COAD (n=18) %Map_raeds Total Editing sites (ES) uniq ES Without SNP 8,1 7,