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bioRxiv · 10.1101/2024.07.31.605758

Expanding the space of self-reproducing RNAs using probabilistic generative models

Lambert, C. N.·Opuu, V.·Calvanese, F.·Zamponi, F.·Hayden, E. J.·Weigt, M. J.·Smerlak, M.·Nghe, P.
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Abstract

Estimating the plausibility of RNA self-reproduction is central to origin-of-life scenarios but self-reproduction has been shown in only a handful of systems. Here, we populated a vast sequence space of ribozymes using statistical covariation models and secondary structure prediction. Experimentally assayed sequences were found active as far as 65 mutations from a reference natural sequence. The number of potentially generated sequences together with the experimental success rate indicate that at least [~]1039 such ribozymes may exist. Randomly sampled artificial ribozymes exhibited autocatalytic self-reproduction akin to the reference sequence. The combination of high-throughput screening and probabilistic modeling considerably improves our estimation of the number of self-reproducing systems, paving the way for a statistical approach to the origin of life.

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Lambert, C. N., Opuu, V., Calvanese, F., Zamponi, F., Hayden, E. J., Weigt, M. J., Smerlak, M., Nghe, P.. 2024-07-31. Expanding the space of self-reproducing RNAs using probabilistic generative models. https://doi.org/10.1101/2024.07.31.605758

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