@article{e83dc0d1f6cf469db21c02ef26821c5f,
title = "Horizontal transfer of code fragments between protocells can explain the origins of the genetic code without vertical descent",
abstract = "Theories of the origin of the genetic code typically appeal to natural selection and/or mutation of hereditable traits to explain its regularities and error robustness, yet the present translation system presupposes high-fidelity replication. Woese's solution to this bootstrapping problem was to assume that code optimization had played a key role in reducing the effect of errors caused by the early translation system. He further conjectured that initially evolution was dominated by horizontal exchange of cellular components among loosely organized protocells ({"}progenotes{"}), rather than by vertical transmission of genes. Here we simulated such communal evolution based on horizontal transfer of code fragments, possibly involving pairs of tRNAs and their cognate aminoacyl tRNA synthetases or a precursor tRNA ribozyme capable of catalysing its own aminoacylation, by using an iterated learning model. This is the first model to confirm Woese's conjecture that regularity, optimality, and (near) universality could have emerged via horizontal interactions alone.",
author = "Tom Froese and Campos, {Jorge I.} and Kosuke Fujishima and Daisuke Kiga and Nathaniel Virgo",
note = "Funding Information: T.F., J.I.C., K.F., and N.V. were supported by the ELSI Origins Network (EON), through a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. T.F. and J.I.C. were also supported by UNAM-DGAPAPAPIIT project IA104717. Lewys Brace shared with us his implementation of a population-based iterated learning model of language evolution that helped to inspire the current work. Markus Meringer shared with us his data on the basic chemical properties of the encoded amino acids. Takayuki Saitoh helped us to run the model on ELSI's high-speed computer cluster. H. James Cleaves and Shawn McGlynn provided valuable feedback during the development of the model. Funding Information: T.F., J.I.C., K.F., and N.V. were supported by the ELSI Origins Network (EON), through a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. T.F. and J.I.C. were also supported by UNAM-DGAPA-PAPIIT project IA104717. Lewys Brace shared with us his implementation of a population-based iterated learning model of language evolution that helped to inspire the current work. Markus Meringer shared with us his data on the basic chemical properties of the encoded amino acids. Takayuki Saitoh helped us to run the model on ELSI{\textquoteright}s high-speed computer cluster. H. James Cleaves and Shawn McGlynn provided valuable feedback during the development of the model. Publisher Copyright: {\textcopyright} 2018 The Author(s).",
year = "2018",
month = dec,
day = "1",
doi = "10.1038/s41598-018-21973-y",
language = "English",
volume = "8",
journal = "Scientific reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",
}