bioRxivGeneticsPreprint
A Small Subset of Cytosolic dsRNAs Must Be Edited by ADAR1 to Evade MDA5-Mediated Autoimmunity
Tao SuniD, Qin LiiD, Jonathan M. GeisingeriD, Shi-Bin HuiD, Boming Fan, Shichen SuiD, Waitang Tsui, Hongchao GuoiD, Jinbiao MaiD, Jin Billy LiiD
Abstract
The innate immune system detects viral infection via pattern recognition receptors and induces defense reactions such as production of type I interferon1. One such receptor, MDA5, is activated upon the recognition of double-stranded RNAs (dsRNAs) that are often produced during viral replication2. Endogenous dsRNAs evade MDA5 activation through RNA editing by ADAR1, thus preventing autoimmunity3-5. Among the large number of endogenous dsRNAs, the key substrates whose editing is critical to evade MDA5 activation (termed as immunogenic dsRNAs) remain elusive. Here we reveal the identity of human immunogenic dsRNAs, a surprisingly small fraction of all cellular dsRNAs, to fill the gap in the ADAR1-dsRNA-MDA5 axis. We found that, in contrast to previous findings6,7, the immunogenic dsRNAs were highly enriched in mRNAs and depleted of introns, an expected indication of bona fide substrates of cytosolic MDA5. The immunogenic dsRNAs, in contrast to non-immunogenic dsRNAs, tended to have shorter loop between the stems, which may facilitate dsRNA formation. They also tended to be enriched at the GWAS signals of common inflammatory diseases, implying that they are truly immunogenic. We validated the MDA5-dependent immunogenicity of the dsRNAs, which was dampened following ADAR1-mediated RNA editing. We anticipate that a focused analysis of immunogenic dsRNAs will greatly facilitate the understanding and treatment of cancer and inflammatory diseases in which the important roles of dsRNA editing and sensing continue to be revealed8-13.
- organism: human
- assay: multiome
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- approach: statistical model
- approach: experimental assay
- Citations
- 21
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