RNA language models predict mutations that improve RNA function

Shulgina, Yekaterina; Trinidad, Marena I.; Langeberg, Conner J.; Nisonoff, Hunter; Chithrananda, Seyone; Skopintsev, Petr; Nissley, Amos J.; Patel, Jaymin; Boger, Ron S.; Shi, Honglue; Yoon, Peter H.; Doherty, Erin E.; Pande, Tara; Iyer, Aditya M.; Doudna, Jennifer A.; Cate, Jamie H. D.

doi:10.1038/s41467-024-54812-y

Title: RNA language models predict mutations that improve RNA function

Journal Article · 04 December 2024 · Nature Communications

DOI: https://doi.org/10.1038/s41467-024-54812-y · OSTI ID:2497287

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^[1]; Iyer, Aditya M. ^[1];

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University of California, Berkeley, CA (United States)
University of California, Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: National Institutes of Health (NIH); National Science Foundation (NSF); Swiss National Science Foundation (SNSF); USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2497287

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 15; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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