Back

A circRNA-derived IRES-like element enables programmable translational activation of the endogenous chaperone HSP90

Aoun, G.; Vandelli, A.; Delli Ponti, R.; Gustincich, S.; Bechara, E.; Broglia, L.; Tartaglia, G. G.

2026-10-06 biochemistry
10.64898/2026.10.05.756760 bioRxiv
Show abstract

Circular RNAs (circRNAs) are covalently closed transcripts that lack a 5' cap, consequently their translation depends on cap-independent initiation, in most cases through Internal Ribosome Entry Sites (IRESs). Whereas IRES-mediated translation has been studied almost exclusively in cis, the use of IRES-containing circRNAs to activate translation of an independent mRNA in trans has only recently begun to be explored. Here, we characterize SynFarsa, a synthetic circRNA-derived IRES-like element that promotes cap-lindependent translation in mouse and human cells. We engineered SynFarsa into a trans-acting regulator by fusing it to a short antisense sequence complementary to a selected region of a target mRNA. This reproduces the architecture of a circular SINEUP, in which IRES activity promotes translation in trans of a transcript recognized through antisense complementarity. Directing this construct to the hsp90 3'UTR increased HSP90 protein levels approximately 1.6-lfold without altering hsp90 mRNA abundance, whereas the hsp70 3'UTR and the 5'UTRs of both transcripts were not permissive, indicating that activity depends strongly on target site selection. In a FUSP525L neuroblastoma model of Amyotrophic Lateral Sclerosis, this increase in HSP90 was accompanied by a reduction in the number and size of cytoplasmic FUS aggregates. SynFarsa thus provides a circRNA-derived effector domain for targeted translational upregulation of an endogenous protein.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.