Abstract
Most theoretical work on the origin of heredity has focused on how genetic information can be maintained without mutational degradation in the absence of error-proofing systems. A simple and parsimonious solution assumes the first gene sequences evolved inside dividing protocells, which enables selection for functional sets. But this model of information maintenance does not consider how protocells acquired their genetic information in the first place. Clues to this transition are suggested by patterns in the genetic code, which indicate a strong link to autotrophic metabolism, with early translation based on direct physical interactions between amino acids and short RNA polymers, grounded in their hydrophobicity. Here, we develop a mathematical model to investigate how random RNA polymers inside autotrophically growing protocells could evolve better coding sequences for discrete functions. The model tracks a population of protocells that evolve towards two essential functions: CO2 fixation (which drives monomer synthesis and cell growth) and copying (which amplifies replication and translation of sequences inside protocells). The model shows that distinct coding sequences can emerge from random RNA sequences driving increased protocell division. The analysis reveals an important restriction: growth-supporting functions such as CO2 fixation must be more easily attained than informational processes such as RNA copying and translation. This uncovers a fundamental constraint on the emergence of genetic heredity: growth precedes information at the origin of life.
| Original language | English |
|---|---|
| Article number | e3003544 |
| Pages (from-to) | 1-20 |
| Number of pages | 20 |
| Journal | PLoS Biology |
| Volume | 24 |
| Issue number | 3 |
| Early online date | 30 Mar 2026 |
| DOIs | |
| Publication status | Published - Mar 2026 |
Bibliographical note
Publisher Copyright:Copyright: © 2026 Nunes Palmeira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding
Natural Environment Research Council (NE/ X009734/1), https://www.ukri.org/councils/ nerc/. NL is additionally supported by funding from the Bill & Melinda Gates Foundation (INV-064683), https://www.gatesfoundation.org. Funding: RNP, MC, AP, and NL are supported by funding from the Biotechnology and Biological Sciences Research Council (BB/ V003542/1), https://www.ukri.org/councils/ bbsrc/. This funding includes ongoing salary support for RNP and previously provided salary support for MC. AP is also supported by funding from the Engineering and Physical Sciences Research Council (EP/X041921/1), https://www.ukri.org/councils/epsrc/, and RNP, MC, AP, and NL are supported by funding from the Biotechnology and Biological Sciences Research Council (BB/V003542/1), https://www.ukri.org/councils/bbsrc/. This funding includes ongoing salary support for RNP and previously provided salary support for MC. AP is also supported by funding from the Engineering and Physical Sciences Research Council (EP/X041921/1), https://www.ukri.org/councils/epsrc/, and Natural Environment Research Council (NE/X009734/1), https://www.ukri.org/councils/nerc/. NL is additionally supported by funding from the Bill & Melinda Gates Foundation (INV-064683), https://www.gatesfoundation.org. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
| Funders | Funder number |
|---|---|
| Bill & Melinda Gates Foundation | |
| Biotechnology and Biological Sciences Research Council | BB/ V003542/1 |
| Engineering and Physical Sciences Research Council | EP/X041921/1 |
| Bill and Melinda Gates Foundation | INV-064683 |
| Natural Environment Research Council | NE/X009734/1 |
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