Accurate prediction of RNA three-dimensional (3D) structures remains an unsolved challenge. Determining RNA 3D structures is crucial for understanding their functions and informing RNA-targeting drug development and synthetic biology design. The structural flexibility of RNA, which leads to the scarcity of experimentally determined data, complicates computational prediction efforts. Here we present RhoFold+, an RNA language model-based deep learning method that accurately predicts 3D structures of single-chain RNAs from sequences. By integrating an RNA language model pretrained on ~23.7 million RNA sequences and leveraging techniques to address data scarcity, RhoFold+ offers a fully automated end-to-end pipeline for RNA 3D structure prediction. Retrospective evaluations on RNA-Puzzles and CASP15 natural RNA targets demonstrate the superiority of RhoFold+ over existing methods, including human expert groups. Its efficacy and generalizability are further validated through cross-family and cross-type assessments, as well as time-censored benchmarks. Additionally, RhoFold+ predicts RNA secondary structures and interhelical angles, providing empirically verifiable features that broaden its applicability to RNA structure and function studies.

Programmed self-assembly of nucleic acids is a powerful approach for nano-constructions. The assembled nanostructures have been explored for various applications. However, nucleic acid assembly often requires chemical or in vitro enzymatical synthesis of DNA or RNA, which is not a cost-effective production method on a large scale. In addition, the difficulty of cellular delivery limits the in vivo applications. Herein we report a strategy that mimics protein production. Gene-encoded DNA duplexes are transcribed into single-stranded RNAs, which self-fold into well-defined RNA nanostructures in the same way as polypeptide chains fold into proteins. The resulting nanostructure contains only one component RNA molecule. This approach allows both in vitro and in vivo production of RNA nanostructures. In vivo synthesized RNA strands can fold into designed nanostructures inside cells. This work not only suggests a way to synthesize RNA nanostructures on a large scale and at a low cost but also facilitates the in vivo applications.